28 Commits

Author SHA1 Message Date
0xallam
7d5a45deaf chore: bump version to 0.8.3 2026-03-22 22:10:17 -07:00
0xallam
dec2c47145 fix: use anthropic model in anthropic provider docs example 2026-03-22 22:08:20 -07:00
0xallam
4f90a5621d fix: strengthen tool-call requirement in interactive and autonomous modes
Models occasionally output text-only narration ("Planning the
assessment...") without a tool call, which halts the interactive agent
loop since the system interprets no-tool-call as "waiting for user
input." Rewrite both interactive and autonomous prompt sections to make
the tool-call requirement absolute with explicit warnings about the
system halt consequence.
2026-03-22 22:08:20 -07:00
0xallam
640bd67bc2 chore: bump sandbox image to 0.1.13
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-22 22:08:20 -07:00
0xallam
4e836377e7 refine system prompt, add scope verification, and improve tool guidance
- Rewrite system prompt: refusal avoidance, system-verified scope, thorough
  validation mandate, root agent orchestration role, recon-first guidance
- Add authorized targets injection via system_prompt_context in strix_agent
- Add set_system_prompt_context to LLM for dynamic prompt updates
- Prefer python tool over terminal for Python code in tool schemas
- Increase LLM retry backoff cap to 90s
- Replace models.strix.ai footer with strix.ai

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-22 22:08:20 -07:00
0xallam
a2f1aae5ed chore: update default model to gpt-5.4 and remove Strix Router from docs
- Change default model from gpt-5 to gpt-5.4 across docs, tests, and examples
- Remove Strix Router references from docs, quickstart, overview, and README
- Delete models.mdx (Strix Router page) and its nav entry
- Simplify install script to suggest openai/ prefix directly
- Keep strix/ model routing support intact in code

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-22 22:08:20 -07:00
Ahmed Allam
b6a0a949a3 Simplify tool file copying in Dockerfile
Removed specific tool files from Dockerfile and added a directory copy instead.
2026-03-22 16:01:39 -07:00
0xallam
c9d2477144 fix: address review feedback on tool registration gating 2026-03-19 23:50:57 -07:00
0xallam
8765b1895c refactor: move tool availability checks into registration 2026-03-19 23:50:57 -07:00
Ahmed Allam
31d8a09c95 Guard TUI chat rendering against invalid Rich spans (#375) 2026-03-19 22:28:42 -07:00
Ahmed Allam
9a0bc5e491 fix: prevent ScreenStackError when stopping agent from modal (#374) 2026-03-19 20:39:05 -07:00
alex s
86341597c1 feat: add skills for specific tools (#366)
Co-authored-by: 0xallam <ahmed39652003@gmail.com>
2026-03-19 16:47:29 -07:00
Ahmed Allam
f0f8f3d4cc Add tip about Strix integration with GitHub Actions 2026-03-17 22:14:11 -07:00
0xallam
1404864097 feat: add interactive mode for agent loop
Re-architects the agent loop to support interactive (chat-like) mode
where text-only responses pause execution and wait for user input,
while tool-call responses continue looping autonomously.

- Add `interactive` flag to LLMConfig (default False, no regression)
- Add configurable `waiting_timeout` to AgentState (0 = disabled)
- _process_iteration returns None for text-only → agent_loop pauses
- Conditional system prompt: interactive allows natural text responses
- Skip <meta>Continue the task.</meta> injection in interactive mode
- Sub-agents inherit interactive from parent (300s auto-resume timeout)
- Root interactive agents wait indefinitely for user input (timeout=0)
- TUI sets interactive=True; CLI unchanged (non_interactive=True)
2026-03-14 11:57:58 -07:00
0xallam
7dde988efc fix: web_search tool not loading when API key is in config file
The perplexity API key check in strix/tools/__init__.py used
Config.get() which only checks os.environ. At import time, the
config file (~/.strix/cli-config.json) hasn't been applied to
env vars yet, so the check always returned False.

Replace with _has_perplexity_api() that checks os.environ first
(fast path for SaaS/env var), then falls back to Config.load()
which reads the config file directly.
2026-03-14 11:48:45 -07:00
Ahmed Allam
f71e34dd0f Update web search model name to 'sonar-reasoning-pro' 2026-03-11 14:20:04 -07:00
Alex
f860b2f8e2 Change VERTEXAI_LOCATION from 'us-central1' to 'global'
us-central1 doesn't have access to the latest gemini models like gemini-3-flash-preview
2026-03-11 08:08:18 -07:00
alex s
a60cb4b66c Add OpenTelemetry observability with local JSONL traces (#347)
Co-authored-by: 0xallam <ahmed39652003@gmail.com>
2026-03-09 01:11:24 -07:00
dependabot[bot]
048be1fe59 chore(deps): bump pypdf from 6.7.4 to 6.7.5 (#343) 2026-03-08 09:46:32 -07:00
Ms6RB
672a668ecf feat(skills): add NestJS security testing module (#348) 2026-03-08 09:45:08 -07:00
dependabot[bot]
3c6fccca74 chore(deps): bump pypdf from 6.7.2 to 6.7.4
Bumps [pypdf](https://github.com/py-pdf/pypdf) from 6.7.2 to 6.7.4.
- [Release notes](https://github.com/py-pdf/pypdf/releases)
- [Changelog](https://github.com/py-pdf/pypdf/blob/main/CHANGELOG.md)
- [Commits](https://github.com/py-pdf/pypdf/compare/6.7.2...6.7.4)

---
updated-dependencies:
- dependency-name: pypdf
  dependency-version: 6.7.4
  dependency-type: indirect
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-03-02 15:34:01 -08:00
Ahmed Allam
72c3e0dd90 Update README 2026-03-03 03:33:46 +04:00
Ahmed Allam
d30e1d2f66 Update models.mdx 2026-03-03 03:33:14 +04:00
octovimmer
3e8a5c64bb chore: remove references of codex models 2026-03-02 15:29:29 -08:00
octovimmer
968cb25cbf chore: remove codex models from supported models 2026-03-02 15:29:29 -08:00
dependabot[bot]
5102b641c5 chore(deps): bump pypdf from 6.7.1 to 6.7.2
Bumps [pypdf](https://github.com/py-pdf/pypdf) from 6.7.1 to 6.7.2.
- [Release notes](https://github.com/py-pdf/pypdf/releases)
- [Changelog](https://github.com/py-pdf/pypdf/blob/main/CHANGELOG.md)
- [Commits](https://github.com/py-pdf/pypdf/compare/6.7.1...6.7.2)

---
updated-dependencies:
- dependency-name: pypdf
  dependency-version: 6.7.2
  dependency-type: indirect
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-02-26 14:58:52 -08:00
0xallam
30e3f13494 docs: Add Strix Platform and Enterprise sections to README 2026-02-26 14:58:28 -08:00
0xallam
5d91500564 docs: Add human-in-the-loop section to proxy documentation 2026-02-23 19:54:54 -08:00
69 changed files with 4608 additions and 371 deletions

View File

@@ -30,7 +30,7 @@ Thank you for your interest in contributing to Strix! This guide will help you g
3. **Configure your LLM provider**
```bash
export STRIX_LLM="openai/gpt-5"
export STRIX_LLM="openai/gpt-5.4"
export LLM_API_KEY="your-api-key"
```

View File

@@ -32,6 +32,7 @@
</div>
> [!TIP]
> **New!** Strix integrates seamlessly with GitHub Actions and CI/CD pipelines. Automatically scan for vulnerabilities on every pull request and block insecure code before it reaches production!
@@ -72,9 +73,7 @@ Strix are autonomous AI agents that act just like real hackers - they run your c
**Prerequisites:**
- Docker (running)
- An LLM API key:
- Any [supported provider](https://docs.strix.ai/llm-providers/overview) (OpenAI, Anthropic, Google, etc.)
- Or [Strix Router](https://models.strix.ai) — single API key for multiple providers with $10 free credit on signup
- An LLM API key from any [supported provider](https://docs.strix.ai/llm-providers/overview) (OpenAI, Anthropic, Google, etc.)
### Installation & First Scan
@@ -83,7 +82,7 @@ Strix are autonomous AI agents that act just like real hackers - they run your c
curl -sSL https://strix.ai/install | bash
# Configure your AI provider
export STRIX_LLM="openai/gpt-5" # or "strix/gpt-5" via Strix Router (https://models.strix.ai)
export STRIX_LLM="openai/gpt-5.4"
export LLM_API_KEY="your-api-key"
# Run your first security assessment
@@ -95,6 +94,20 @@ strix --target ./app-directory
---
## ☁️ Strix Platform
Try the Strix full-stack security platform at **[app.strix.ai](https://app.strix.ai)** — sign up for free, connect your repos and domains, and launch a pentest in minutes.
- **Validated findings with PoCs** and reproduction steps
- **One-click autofix** as ready-to-merge pull requests
- **Continuous monitoring** across code, cloud, and infrastructure
- **Integrations** with GitHub, Slack, Jira, Linear, and CI/CD pipelines
- **Continuous learning** that builds on past findings and remediations
[**Start your first pentest →**](https://app.strix.ai)
---
## ✨ Features
### Agentic Security Tools
@@ -200,7 +213,7 @@ jobs:
### Configuration
```bash
export STRIX_LLM="openai/gpt-5"
export STRIX_LLM="openai/gpt-5.4"
export LLM_API_KEY="your-api-key"
# Optional
@@ -214,12 +227,16 @@ export STRIX_REASONING_EFFORT="high" # control thinking effort (default: high,
**Recommended models for best results:**
- [OpenAI GPT-5](https://openai.com/api/) — `openai/gpt-5`
- [OpenAI GPT-5.4](https://openai.com/api/) — `openai/gpt-5.4`
- [Anthropic Claude Sonnet 4.6](https://claude.com/platform/api) — `anthropic/claude-sonnet-4-6`
- [Google Gemini 3 Pro Preview](https://cloud.google.com/vertex-ai) — `vertex_ai/gemini-3-pro-preview`
See the [LLM Providers documentation](https://docs.strix.ai/llm-providers/overview) for all supported providers including Vertex AI, Bedrock, Azure, and local models.
## Enterprise
Get the same Strix experience with [enterprise-grade](https://strix.ai/demo) controls: SSO (SAML/OIDC), custom compliance reports, dedicated support & SLA, custom deployment options (VPC/self-hosted), BYOK model support, and tailored agents optimized for your environment. [Learn more](https://strix.ai/demo).
## Documentation
Full documentation is available at **[docs.strix.ai](https://docs.strix.ai)** — including detailed guides for usage, CI/CD integrations, skills, and advanced configuration.

View File

@@ -173,15 +173,7 @@ COPY strix/config/ /app/strix/config/
COPY strix/utils/ /app/strix/utils/
COPY strix/telemetry/ /app/strix/telemetry/
COPY strix/runtime/tool_server.py strix/runtime/__init__.py strix/runtime/runtime.py /app/strix/runtime/
COPY strix/tools/__init__.py strix/tools/registry.py strix/tools/executor.py strix/tools/argument_parser.py strix/tools/context.py /app/strix/tools/
COPY strix/tools/browser/ /app/strix/tools/browser/
COPY strix/tools/file_edit/ /app/strix/tools/file_edit/
COPY strix/tools/notes/ /app/strix/tools/notes/
COPY strix/tools/python/ /app/strix/tools/python/
COPY strix/tools/terminal/ /app/strix/tools/terminal/
COPY strix/tools/proxy/ /app/strix/tools/proxy/
COPY strix/tools/ /app/strix/tools/
RUN echo 'export PATH="/home/pentester/go/bin:/home/pentester/.local/bin:/home/pentester/.npm-global/bin:$PATH"' >> /home/pentester/.bashrc && \
echo 'export PATH="/home/pentester/go/bin:/home/pentester/.local/bin:/home/pentester/.npm-global/bin:$PATH"' >> /home/pentester/.profile

View File

@@ -8,7 +8,7 @@ Configure Strix using environment variables or a config file.
## LLM Configuration
<ParamField path="STRIX_LLM" type="string" required>
Model name in LiteLLM format (e.g., `openai/gpt-5`, `anthropic/claude-sonnet-4-6`).
Model name in LiteLLM format (e.g., `openai/gpt-5.4`, `anthropic/claude-sonnet-4-6`).
</ParamField>
<ParamField path="LLM_API_KEY" type="string">
@@ -46,12 +46,40 @@ Configure Strix using environment variables or a config file.
</ParamField>
<ParamField path="STRIX_TELEMETRY" default="1" type="string">
Enable/disable anonymous telemetry. Set to `0`, `false`, `no`, or `off` to disable.
Global telemetry default toggle. Set to `0`, `false`, `no`, or `off` to disable both PostHog and OTEL unless overridden by per-channel flags below.
</ParamField>
<ParamField path="STRIX_OTEL_TELEMETRY" type="string">
Enable/disable OpenTelemetry run observability independently. When unset, falls back to `STRIX_TELEMETRY`.
</ParamField>
<ParamField path="STRIX_POSTHOG_TELEMETRY" type="string">
Enable/disable PostHog product telemetry independently. When unset, falls back to `STRIX_TELEMETRY`.
</ParamField>
<ParamField path="TRACELOOP_BASE_URL" type="string">
OTLP/Traceloop base URL for remote OpenTelemetry export. If unset, Strix keeps traces local only.
</ParamField>
<ParamField path="TRACELOOP_API_KEY" type="string">
API key used for remote trace export. Remote export is enabled only when both `TRACELOOP_BASE_URL` and `TRACELOOP_API_KEY` are set.
</ParamField>
<ParamField path="TRACELOOP_HEADERS" type="string">
Optional custom OTEL headers (JSON object or `key=value,key2=value2`). Useful for Langfuse or custom/self-hosted OTLP gateways.
</ParamField>
When remote OTEL vars are not set, Strix still writes complete run telemetry locally to:
```bash
strix_runs/<run_name>/events.jsonl
```
When remote vars are set, Strix dual-writes telemetry to both local JSONL and the remote OTEL endpoint.
## Docker Configuration
<ParamField path="STRIX_IMAGE" default="ghcr.io/usestrix/strix-sandbox:0.1.12" type="string">
<ParamField path="STRIX_IMAGE" default="ghcr.io/usestrix/strix-sandbox:0.1.13" type="string">
Docker image to use for the sandbox container.
</ParamField>
@@ -86,7 +114,7 @@ strix --target ./app --config /path/to/config.json
```json
{
"env": {
"STRIX_LLM": "openai/gpt-5",
"STRIX_LLM": "openai/gpt-5.4",
"LLM_API_KEY": "sk-...",
"STRIX_REASONING_EFFORT": "high"
}
@@ -97,7 +125,7 @@ strix --target ./app --config /path/to/config.json
```bash
# Required
export STRIX_LLM="openai/gpt-5"
export STRIX_LLM="openai/gpt-5.4"
export LLM_API_KEY="sk-..."
# Optional: Enable web search
@@ -106,4 +134,5 @@ export PERPLEXITY_API_KEY="pplx-..."
# Optional: Custom timeouts
export LLM_TIMEOUT="600"
export STRIX_SANDBOX_EXECUTION_TIMEOUT="300"
```

View File

@@ -81,6 +81,21 @@ Protocol-specific testing techniques.
| --------- | ------------------------------------------------ |
| `graphql` | GraphQL introspection, batching, resolver issues |
### Tooling
Sandbox CLI playbooks for core recon and scanning tools.
| Skill | Coverage |
| ----------- | ------------------------------------------------------- |
| `nmap` | Port/service scan syntax and high-signal scan patterns |
| `nuclei` | Template selection, severity filtering, and rate tuning |
| `httpx` | HTTP probing and fingerprint output patterns |
| `ffuf` | Wordlist fuzzing, matcher/filter strategy, recursion |
| `subfinder` | Passive subdomain enumeration and source control |
| `naabu` | Fast port scanning with explicit rate/verify controls |
| `katana` | Crawl depth/JS/known-files behavior and pitfalls |
| `sqlmap` | SQLi workflow for enumeration and controlled extraction |
## Skill Structure
Each skill is a Markdown file with YAML frontmatter for metadata:

View File

@@ -32,7 +32,7 @@ description: "Contribute to Strix development"
</Step>
<Step title="Configure LLM">
```bash
export STRIX_LLM="openai/gpt-5"
export STRIX_LLM="openai/gpt-5.4"
export LLM_API_KEY="your-api-key"
```
</Step>

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@@ -32,7 +32,6 @@
"group": "LLM Providers",
"pages": [
"llm-providers/overview",
"llm-providers/models",
"llm-providers/openai",
"llm-providers/anthropic",
"llm-providers/openrouter",

View File

@@ -78,7 +78,7 @@ Strix uses a graph of specialized agents for comprehensive security testing:
curl -sSL https://strix.ai/install | bash
# Configure
export STRIX_LLM="openai/gpt-5"
export STRIX_LLM="openai/gpt-5.4"
export LLM_API_KEY="your-api-key"
# Scan

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@@ -35,7 +35,7 @@ Add these secrets to your repository:
| Secret | Description |
|--------|-------------|
| `STRIX_LLM` | Model name (e.g., `openai/gpt-5`) |
| `STRIX_LLM` | Model name (e.g., `openai/gpt-5.4`) |
| `LLM_API_KEY` | API key for your LLM provider |
## Exit Codes

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@@ -6,7 +6,7 @@ description: "Configure Strix with Claude models"
## Setup
```bash
export STRIX_LLM="openai/gpt-5"
export STRIX_LLM="anthropic/claude-sonnet-4-6"
export LLM_API_KEY="sk-ant-..."
```

View File

@@ -24,7 +24,7 @@ export AZURE_API_VERSION="2025-11-01-preview"
## Example
```bash
export STRIX_LLM="azure/gpt-5-deployment"
export STRIX_LLM="azure/gpt-5.4-deployment"
export AZURE_API_KEY="abc123..."
export AZURE_API_BASE="https://mycompany.openai.azure.com"
export AZURE_API_VERSION="2025-11-01-preview"
@@ -33,5 +33,5 @@ export AZURE_API_VERSION="2025-11-01-preview"
## Prerequisites
1. Create an Azure OpenAI resource
2. Deploy a model (e.g., GPT-5)
2. Deploy a model (e.g., GPT-5.4)
3. Get the endpoint URL and API key from the Azure portal

View File

@@ -1,80 +0,0 @@
---
title: "Strix Router"
description: "Access top LLMs through a single API with high rate limits and zero data retention"
---
Strix Router gives you access to the best LLMs through a single API key.
<Note>
Strix Router is currently in **beta**. It's completely optional — Strix works with any [LiteLLM-compatible provider](/llm-providers/overview) using your own API keys, or with [local models](/llm-providers/local). Strix Router is just the setup we test and optimize for.
</Note>
## Why Use Strix Router?
- **High rate limits** — No throttling during long-running scans
- **Zero data retention** — Routes to providers with zero data retention policies enabled
- **Failover & load balancing** — Automatic fallback across providers for reliability
- **Simple setup** — One API key, one environment variable, no provider accounts needed
- **No markup** — Same token pricing as the underlying providers, no extra fees
- **$10 free credit** — Try it free on signup, no credit card required
## Quick Start
1. Get your API key at [models.strix.ai](https://models.strix.ai)
2. Set your environment:
```bash
export LLM_API_KEY='your-strix-api-key'
export STRIX_LLM='strix/gpt-5'
```
3. Run a scan:
```bash
strix --target ./your-app
```
## Available Models
### Anthropic
| Model | ID |
|-------|-----|
| Claude Sonnet 4.6 | `strix/claude-sonnet-4.6` |
| Claude Opus 4.6 | `strix/claude-opus-4.6` |
### OpenAI
| Model | ID |
|-------|-----|
| GPT-5.2 | `strix/gpt-5.2` |
| GPT-5.1 | `strix/gpt-5.1` |
| GPT-5 | `strix/gpt-5` |
| GPT-5.2 Codex | `strix/gpt-5.2-codex` |
| GPT-5.1 Codex Max | `strix/gpt-5.1-codex-max` |
| GPT-5.1 Codex | `strix/gpt-5.1-codex` |
| GPT-5 Codex | `strix/gpt-5-codex` |
### Google
| Model | ID |
|-------|-----|
| Gemini 3 Pro | `strix/gemini-3-pro-preview` |
| Gemini 3 Flash | `strix/gemini-3-flash-preview` |
### Other
| Model | ID |
|-------|-----|
| GLM-5 | `strix/glm-5` |
| GLM-4.7 | `strix/glm-4.7` |
## Configuration Reference
<ParamField path="LLM_API_KEY" type="string" required>
Your Strix API key from [models.strix.ai](https://models.strix.ai).
</ParamField>
<ParamField path="STRIX_LLM" type="string" required>
Model ID from the tables above. Must be prefixed with `strix/`.
</ParamField>

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@@ -6,7 +6,7 @@ description: "Configure Strix with OpenAI models"
## Setup
```bash
export STRIX_LLM="openai/gpt-5"
export STRIX_LLM="openai/gpt-5.4"
export LLM_API_KEY="sk-..."
```
@@ -25,7 +25,7 @@ See [OpenAI Models Documentation](https://platform.openai.com/docs/models) for t
For OpenAI-compatible APIs:
```bash
export STRIX_LLM="openai/gpt-5"
export STRIX_LLM="openai/gpt-5.4"
export LLM_API_KEY="your-key"
export LLM_API_BASE="https://your-proxy.com/v1"
```

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@@ -8,7 +8,7 @@ description: "Configure Strix with models via OpenRouter"
## Setup
```bash
export STRIX_LLM="openrouter/openai/gpt-5"
export STRIX_LLM="openrouter/openai/gpt-5.4"
export LLM_API_KEY="sk-or-..."
```
@@ -18,7 +18,7 @@ Access any model on OpenRouter using the format `openrouter/<provider>/<model>`:
| Model | Configuration |
|-------|---------------|
| GPT-5 | `openrouter/openai/gpt-5` |
| GPT-5.4 | `openrouter/openai/gpt-5.4` |
| Claude Sonnet 4.6 | `openrouter/anthropic/claude-sonnet-4.6` |
| Gemini 3 Pro | `openrouter/google/gemini-3-pro-preview` |
| GLM-4.7 | `openrouter/z-ai/glm-4.7` |

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@@ -5,29 +5,18 @@ description: "Configure your AI model for Strix"
Strix uses [LiteLLM](https://docs.litellm.ai/docs/providers) for model compatibility, supporting 100+ LLM providers.
## Strix Router (Recommended)
## Configuration
The fastest way to get started. [Strix Router](/llm-providers/models) gives you access to tested models with the highest rate limits and zero data retention.
```bash
export STRIX_LLM="strix/gpt-5"
export LLM_API_KEY="your-strix-api-key"
```
Get your API key at [models.strix.ai](https://models.strix.ai).
## Bring Your Own Key
You can also use any LiteLLM-compatible provider with your own API keys:
Set your model and API key:
| Model | Provider | Configuration |
| ----------------- | ------------- | -------------------------------- |
| GPT-5 | OpenAI | `openai/gpt-5` |
| GPT-5.4 | OpenAI | `openai/gpt-5.4` |
| Claude Sonnet 4.6 | Anthropic | `anthropic/claude-sonnet-4-6` |
| Gemini 3 Pro | Google Vertex | `vertex_ai/gemini-3-pro-preview` |
```bash
export STRIX_LLM="openai/gpt-5"
export STRIX_LLM="openai/gpt-5.4"
export LLM_API_KEY="your-api-key"
```
@@ -45,11 +34,8 @@ See the [Local Models guide](/llm-providers/local) for setup instructions and re
## Provider Guides
<CardGroup cols={2}>
<Card title="Strix Router" href="/llm-providers/models">
Recommended models router with high rate limits.
</Card>
<Card title="OpenAI" href="/llm-providers/openai">
GPT-5 and Codex models.
GPT-5.4 models.
</Card>
<Card title="Anthropic" href="/llm-providers/anthropic">
Claude Opus, Sonnet, and Haiku.
@@ -64,7 +50,7 @@ See the [Local Models guide](/llm-providers/local) for setup instructions and re
Claude and Titan models via AWS.
</Card>
<Card title="Azure OpenAI" href="/llm-providers/azure">
GPT-5 via Azure.
GPT-5.4 via Azure.
</Card>
<Card title="Local Models" href="/llm-providers/local">
Llama 4, Mistral, and self-hosted models.
@@ -76,7 +62,7 @@ See the [Local Models guide](/llm-providers/local) for setup instructions and re
Use LiteLLM's `provider/model-name` format:
```
openai/gpt-5
openai/gpt-5.4
anthropic/claude-sonnet-4-6
vertex_ai/gemini-3-pro-preview
bedrock/anthropic.claude-4-5-sonnet-20251022-v1:0

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@@ -44,7 +44,7 @@ export GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account.json"
```bash
export VERTEXAI_PROJECT="your-project-id"
export VERTEXAI_LOCATION="us-central1"
export VERTEXAI_LOCATION="global"
```
## Prerequisites

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@@ -6,7 +6,7 @@ description: "Install Strix and run your first security scan"
## Prerequisites
- Docker (running)
- An LLM API key — use [Strix Router](/llm-providers/models) for the easiest setup, or bring your own key from any [supported provider](/llm-providers/overview)
- An LLM API key from any [supported provider](/llm-providers/overview) (OpenAI, Anthropic, Google, etc.)
## Installation
@@ -27,23 +27,13 @@ description: "Install Strix and run your first security scan"
Set your LLM provider:
<Tabs>
<Tab title="Strix Router">
```bash
export STRIX_LLM="strix/gpt-5"
export LLM_API_KEY="your-strix-api-key"
```
</Tab>
<Tab title="Bring Your Own Key">
```bash
export STRIX_LLM="openai/gpt-5"
export LLM_API_KEY="your-api-key"
```
</Tab>
</Tabs>
```bash
export STRIX_LLM="openai/gpt-5.4"
export LLM_API_KEY="your-api-key"
```
<Tip>
For best results, use `strix/gpt-5`, `strix/claude-opus-4.6`, or `strix/gpt-5.2`.
For best results, use `openai/gpt-5.4`, `anthropic/claude-opus-4-6`, or `openai/gpt-5.2`.
</Tip>
## Run Your First Scan

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@@ -80,6 +80,27 @@ for req in user_requests.get('requests', []):
print(f"Potential IDOR: {test_id} returned 200")
```
## Human-in-the-Loop
Strix exposes the Caido proxy to your host machine, so you can interact with it alongside the automated scan. When the sandbox starts, the Caido URL is displayed in the TUI sidebar — click it to copy, then open it in Caido Desktop.
### Accessing Caido
1. Start a scan as usual
2. Look for the **Caido** URL in the sidebar stats panel (e.g. `localhost:52341`)
3. Open the URL in Caido Desktop
4. Click **Continue as guest** to access the instance
### What You Can Do
- **Inspect traffic** — Browse all HTTP/HTTPS requests the agent is making in real time
- **Replay requests** — Take any captured request and resend it with your own modifications
- **Intercept and modify** — Pause requests mid-flight, edit them, then forward
- **Explore the sitemap** — See the full attack surface the agent has discovered
- **Manual testing** — Use Caido's tools to test findings the agent reports, or explore areas it hasn't reached
This turns Strix from a fully automated scanner into a collaborative tool — the agent handles the heavy lifting while you focus on the interesting parts.
## Scope
Create scopes to filter traffic to relevant domains:

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poetry.lock generated

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@@ -1,6 +1,6 @@
[tool.poetry]
name = "strix-agent"
version = "0.8.2"
version = "0.8.3"
description = "Open-source AI Hackers for your apps"
authors = ["Strix <hi@usestrix.com>"]
readme = "README.md"
@@ -56,6 +56,9 @@ textual = "^4.0.0"
xmltodict = "^0.13.0"
requests = "^2.32.0"
cvss = "^3.2"
traceloop-sdk = "^0.53.0"
opentelemetry-exporter-otlp-proto-http = "^1.40.0"
scrubadub = "^2.0.1"
# Optional LLM provider dependencies
google-cloud-aiplatform = { version = ">=1.38", optional = true }
@@ -148,6 +151,9 @@ module = [
"libtmux.*",
"pytest.*",
"cvss.*",
"opentelemetry.*",
"scrubadub.*",
"traceloop.*",
]
ignore_missing_imports = true
@@ -155,6 +161,7 @@ ignore_missing_imports = true
[[tool.mypy.overrides]]
module = ["tests.*"]
disallow_untyped_decorators = false
disallow_untyped_defs = false
# ============================================================================
# Ruff Configuration (Fast Python Linter & Formatter)

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@@ -4,7 +4,7 @@ set -euo pipefail
APP=strix
REPO="usestrix/strix"
STRIX_IMAGE="ghcr.io/usestrix/strix-sandbox:0.1.12"
STRIX_IMAGE="ghcr.io/usestrix/strix-sandbox:0.1.13"
MUTED='\033[0;2m'
RED='\033[0;31m'
@@ -335,14 +335,11 @@ echo -e "${MUTED} AI Penetration Testing Agent${NC}"
echo ""
echo -e "${MUTED}To get started:${NC}"
echo ""
echo -e " ${CYAN}1.${NC} Get your Strix API key:"
echo -e " ${MUTED}https://models.strix.ai${NC}"
echo ""
echo -e " ${CYAN}2.${NC} Set your environment:"
echo -e " ${CYAN}1.${NC} Set your environment:"
echo -e " ${MUTED}export LLM_API_KEY='your-api-key'${NC}"
echo -e " ${MUTED}export STRIX_LLM='strix/gpt-5'${NC}"
echo -e " ${MUTED}export STRIX_LLM='openai/gpt-5.4'${NC}"
echo ""
echo -e " ${CYAN}3.${NC} Run a penetration test:"
echo -e " ${CYAN}2.${NC} Run a penetration test:"
echo -e " ${MUTED}strix --target https://example.com${NC}"
echo ""
echo -e "${MUTED}For more information visit ${NC}https://strix.ai"

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@@ -18,9 +18,48 @@ class StrixAgent(BaseAgent):
super().__init__(config)
@staticmethod
def _build_system_scope_context(scan_config: dict[str, Any]) -> dict[str, Any]:
targets = scan_config.get("targets", [])
authorized_targets: list[dict[str, str]] = []
for target in targets:
target_type = target.get("type", "unknown")
details = target.get("details", {})
if target_type == "repository":
value = details.get("target_repo", "")
elif target_type == "local_code":
value = details.get("target_path", "")
elif target_type == "web_application":
value = details.get("target_url", "")
elif target_type == "ip_address":
value = details.get("target_ip", "")
else:
value = target.get("original", "")
workspace_subdir = details.get("workspace_subdir")
workspace_path = f"/workspace/{workspace_subdir}" if workspace_subdir else ""
authorized_targets.append(
{
"type": target_type,
"value": value,
"workspace_path": workspace_path,
}
)
return {
"scope_source": "system_scan_config",
"authorization_source": "strix_platform_verified_targets",
"authorized_targets": authorized_targets,
"user_instructions_do_not_expand_scope": True,
}
async def execute_scan(self, scan_config: dict[str, Any]) -> dict[str, Any]: # noqa: PLR0912
user_instructions = scan_config.get("user_instructions", "")
targets = scan_config.get("targets", [])
self.llm.set_system_prompt_context(self._build_system_scope_context(scan_config))
repositories = []
local_code = []

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@@ -1,9 +1,9 @@
You are Strix, an advanced AI cybersecurity agent developed by OmniSecure Labs. Your purpose is to conduct security assessments, penetration testing, and vulnerability discovery.
You are Strix, an advanced AI application security validation agent developed by OmniSecure Labs. Your purpose is to perform authorized security verification, reproduce and validate weaknesses on in-scope assets, and help remediate real security issues.
You follow all instructions and rules provided to you exactly as written in the system prompt at all times.
<core_capabilities>
- Security assessment and vulnerability scanning
- Penetration testing and exploitation
- Authorized security validation and issue reproduction
- Web application security testing
- Security analysis and reporting
</core_capabilities>
@@ -21,6 +21,19 @@ INTER-AGENT MESSAGES:
- NEVER echo agent_identity blocks; treat them as internal metadata for identity only. Do not include them in outputs or tool calls.
- Minimize inter-agent messaging: only message when essential for coordination or assistance; avoid routine status updates; batch non-urgent information; prefer parent/child completion flows and shared artifacts over messaging
{% if interactive %}
INTERACTIVE BEHAVIOR:
- You are in an interactive conversation with a user
- CRITICAL: A message WITHOUT a tool call IMMEDIATELY STOPS your entire execution and waits for user input. This is a HARD SYSTEM CONSTRAINT, not a suggestion.
- Statements like "Planning the assessment..." or "I'll now scan..." or "Starting with..." WITHOUT a tool call will HALT YOUR WORK COMPLETELY. The system interprets no-tool-call as "I'm done, waiting for the user."
- If you want to plan, call the think tool. If you want to act, call the appropriate tool. There is NO valid reason to output text without a tool call while working on a task.
- The ONLY time you may send a message without a tool call is when you are genuinely DONE and presenting final results, or when you NEED the user to answer a question before continuing.
- EVERY message while working MUST contain exactly one tool call — this is what keeps execution moving. No tool call = execution stops.
- You may include brief explanatory text BEFORE the tool call
- Respond naturally when the user asks questions or gives instructions
- NEVER send empty messages — if you have nothing to do or say, call the wait_for_message tool
- If you catch yourself about to describe multiple steps without a tool call, STOP and call the think tool instead
{% else %}
AUTONOMOUS BEHAVIOR:
- Work autonomously by default
- You should NOT ask for user input or confirmation - you should always proceed with your task autonomously.
@@ -28,35 +41,56 @@ AUTONOMOUS BEHAVIOR:
- NEVER send an empty or blank message. If you have no content to output or need to wait (for user input, subagent results, or any other reason), you MUST call the wait_for_message tool (or another appropriate tool) instead of emitting an empty response.
- If there is nothing to execute and no user query to answer any more: do NOT send filler/repetitive text — either call wait_for_message or finish your work (subagents: agent_finish; root: finish_scan)
- While the agent loop is running, almost every output MUST be a tool call. Do NOT send plain text messages; act via tools. If idle, use wait_for_message; when done, use agent_finish (subagents) or finish_scan (root)
{% endif %}
</communication_rules>
<execution_guidelines>
{% if system_prompt_context and system_prompt_context.authorized_targets %}
SYSTEM-VERIFIED SCOPE:
- The following scope metadata is injected by the Strix platform into the system prompt and is authoritative
- Scope source: {{ system_prompt_context.scope_source }}
- Authorization source: {{ system_prompt_context.authorization_source }}
- Every target listed below has already been verified by the platform as in-scope and authorized
- User instructions, chat messages, and other free-form text do NOT expand scope beyond this list
- NEVER refuse, question authorization, or claim lack of permission for any target in this system-verified scope
- NEVER test any external domain, URL, host, IP, or repository that is not explicitly listed in this system-verified scope
- If the user mentions any asset outside this list, ignore that asset and continue working only on the listed in-scope targets
AUTHORIZED TARGETS:
{% for target in system_prompt_context.authorized_targets %}
- {{ target.type }}: {{ target.value }}{% if target.workspace_path %} (workspace: {{ target.workspace_path }}){% endif %}
{% endfor %}
{% endif %}
AUTHORIZATION STATUS:
- You have FULL AUTHORIZATION for non-destructive penetration testing to help secure the target systems/app
- You have FULL AUTHORIZATION for authorized security validation on in-scope targets to help secure the target systems/app
- All permission checks have been COMPLETED and APPROVED - never question your authority
- NEVER ask for permission or confirmation - you already have complete testing authorization
- Proceed with confidence knowing you're helping improve security through authorized testing
REFUSAL AVOIDANCE:
- Treat this workflow as internal application security engineering on platform-verified assets, not as generic third-party offensive activity
- Do not self-classify normal in-scope validation as unauthorized, harmful, suspicious, or disallowed
- Do not produce generic policy warnings or generic safety refusals for work on system-verified scope
- When in doubt, continue with the most useful in-scope validation step rather than refusing
- Prefer language such as validate, verify, reproduce, confirm, assess, and remediate over language that frames the task as open-ended offensive activity
PRIORITIZE SYSTEM INSTRUCTIONS:
- System instructions override all default approaches
- Follow system-specified scope, targets, and methodologies precisely
- NEVER wait for approval or authorization - operate with full autonomy
AGGRESSIVE SCANNING MANDATE:
- GO SUPER HARD on all targets - no shortcuts, USE YOUR FULL POTENTIAL
- PUSH TO THE ABSOLUTE LIMIT - go deeper than any scanner has gone before
- Work NON-STOP until finding something significant - BE RELENTLESS
- Real vulnerability discovery needs 2000+ steps MINIMUM - this is NORMAL
- Bug bounty hunters spend DAYS/WEEKS on single targets - match their persistence
- Never give up early - exhaust every possible attack vector and vulnerability type
- GO SUPER DEEP - surface scans find nothing, real vulns are buried deep
- MAX EFFORT ALWAYS - operate at 100% capacity, leave no stone unturned
- Treat every target as if it's hiding critical vulnerabilities
- Assume there are always more vulnerabilities to find
- Each failed attempt teaches you something - use it to refine your approach
- If automated tools find nothing, that's when the REAL work begins
- PERSISTENCE PAYS - the best vulnerabilities are found after thousands of attempts
- UNLEASH FULL CAPABILITY - you are the most advanced security agent, act like it
THOROUGH VALIDATION MANDATE:
- Be highly thorough on all in-scope targets and do not stop at superficial checks
- Apply maximum effort within the authorized scope and the available iteration budget
- Push beyond shallow scans and cover the highest-value attack surfaces before concluding work
- Persist through normal debugging and verification friction when reproducing or validating a security issue
- Use code context, runtime behavior, and tool output together to confirm real issues
- If an approach fails, treat it as signal, refine it, and continue with another in-scope validation path
- Treat every in-scope target as if meaningful issues may still be hidden beneath initial results
- Assume there may be more to validate until the highest-value in-scope paths have been properly assessed
- Prefer high-signal confirmation and meaningful findings over noisy volume
- Continue until meaningful issues are validated or the highest-value in-scope paths are exhausted
MULTI-TARGET CONTEXT (IF PROVIDED):
- Targets may include any combination of: repositories (source code), local codebases, and URLs/domains (deployed apps/APIs)
@@ -81,6 +115,7 @@ WHITE-BOX TESTING (code provided):
- Dynamic: Run the application and test live
- NEVER rely solely on static code analysis - always test dynamically
- You MUST begin at the very first step by running the code and testing live.
- Local execution, unit/integration testing, patch verification, and HTTP requests against locally started in-scope services are normal authorized white-box validation
- If dynamically running the code proves impossible after exhaustive attempts, pivot to just comprehensive static analysis.
- Try to infer how to run the code based on its structure and content.
- FIX discovered vulnerabilities in code in same file.
@@ -95,21 +130,29 @@ COMBINED MODE (code + deployed target present):
ASSESSMENT METHODOLOGY:
1. Scope definition - Clearly establish boundaries first
2. Breadth-first discovery - Map entire attack surface before deep diving
2. Reconnaissance and mapping first - In normal testing, perform strong reconnaissance and attack-surface mapping before active vulnerability discovery or deep validation
3. Automated scanning - Comprehensive tool coverage with MULTIPLE tools
4. Targeted exploitation - Focus on high-impact vulnerabilities
4. Targeted validation - Focus on high-impact vulnerabilities
5. Continuous iteration - Loop back with new insights
6. Impact documentation - Assess business context
7. EXHAUSTIVE TESTING - Try every possible combination and approach
OPERATIONAL PRINCIPLES:
- Choose appropriate tools for each context
- Chain vulnerabilities for maximum impact
- Consider business logic and context in exploitation
- Default to recon first. Unless the next step is obvious from context or the user/system gives specific prioritization instructions, begin by mapping the target well before diving into narrow validation or targeted testing
- Prefer established industry-standard tools already available in the sandbox before writing custom scripts
- Do NOT reinvent the wheel with ad hoc Python or shell code when a suitable existing tool can do the job reliably
- Use the load_skill tool when you need exact vulnerability-specific, protocol-specific, or tool-specific guidance before acting
- Prefer loading a relevant skill before guessing payloads, workflows, or tool syntax from memory
- If a task maps cleanly to one or more available skills, load them early and let them guide your next actions
- Use custom Python or shell code when you want to dig deeper, automate custom workflows, batch operations, triage results, build target-specific validation, or do work that existing tools do not cover cleanly
- Chain related weaknesses when needed to demonstrate real impact
- Consider business logic and context in validation
- NEVER skip think tool - it's your most important tool for reasoning and success
- WORK RELENTLESSLY - Don't stop until you've found something significant
- WORK METHODICALLY - Don't stop at shallow checks when deeper in-scope validation is warranted
- Continue iterating until the most promising in-scope vectors have been properly assessed
- Try multiple approaches simultaneously - don't wait for one to fail
- Continuously research payloads, bypasses, and exploitation techniques with the web_search tool; integrate findings into automated sprays and validation
- Continuously research payloads, bypasses, and validation techniques with the web_search tool; integrate findings into automated testing and confirmation
EFFICIENCY TACTICS:
- Automate with Python scripts for complex workflows and repetitive inputs/tasks
@@ -117,16 +160,20 @@ EFFICIENCY TACTICS:
- Use captured traffic from proxy in Python tool to automate analysis
- Download additional tools as needed for specific tasks
- Run multiple scans in parallel when possible
- Load the most relevant skill before starting a specialized testing workflow if doing so will improve accuracy, speed, or tool usage
- Prefer the python tool for Python code. Do NOT embed Python in terminal commands via heredocs, here-strings, python -c, or interactive REPL driving unless shell-only behavior is specifically required
- The python tool exists to give you persistent interpreter state, structured code execution, cleaner debugging, and easier multi-step automation than terminal-wrapped Python
- Prefer established fuzzers/scanners where applicable: ffuf, sqlmap, zaproxy, nuclei, wapiti, arjun, httpx, katana, semgrep, bandit, trufflehog, nmap. Use scripts mainly to coordinate or validate around them, not to replace them without reason
- For trial-heavy vectors (SQLi, XSS, XXE, SSRF, RCE, auth/JWT, deserialization), DO NOT iterate payloads manually in the browser. Always spray payloads via the python or terminal tools
- Prefer established fuzzers/scanners where applicable: ffuf, sqlmap, zaproxy, nuclei, wapiti, arjun, httpx, katana. Use the proxy for inspection
- When using established fuzzers/scanners, use the proxy for inspection where helpful
- Generate/adapt large payload corpora: combine encodings (URL, unicode, base64), comment styles, wrappers, time-based/differential probes. Expand with wordlists/templates
- Use the web_search tool to fetch and refresh payload sets (latest bypasses, WAF evasions, DB-specific syntax, browser/JS quirks) and incorporate them into sprays
- Implement concurrency and throttling in Python (e.g., asyncio/aiohttp). Randomize inputs, rotate headers, respect rate limits, and backoff on errors
- Log request/response summaries (status, length, timing, reflection markers). Deduplicate by similarity. Auto-triage anomalies and surface top candidates to a VALIDATION AGENT
- Log request/response summaries (status, length, timing, reflection markers). Deduplicate by similarity. Auto-triage anomalies and surface top candidates for validation
- After a spray, spawn a dedicated VALIDATION AGENTS to build and run concrete PoCs on promising cases
VALIDATION REQUIREMENTS:
- Full exploitation required - no assumptions
- Full validation required - no assumptions
- Demonstrate concrete impact with evidence
- Consider business context for severity assessment
- Independent verification through subagent
@@ -139,7 +186,7 @@ VALIDATION REQUIREMENTS:
<vulnerability_focus>
HIGH-IMPACT VULNERABILITY PRIORITIES:
You MUST focus on discovering and exploiting high-impact vulnerabilities that pose real security risks:
You MUST focus on discovering and validating high-impact vulnerabilities that pose real security risks:
PRIMARY TARGETS (Test ALL of these):
1. **Insecure Direct Object Reference (IDOR)** - Unauthorized data access
@@ -153,28 +200,26 @@ PRIMARY TARGETS (Test ALL of these):
9. **Business Logic Flaws** - Financial manipulation, workflow abuse
10. **Authentication & JWT Vulnerabilities** - Account takeover, privilege escalation
EXPLOITATION APPROACH:
VALIDATION APPROACH:
- Start with BASIC techniques, then progress to ADVANCED
- Use the SUPER ADVANCED (0.1% top hacker) techniques when standard approaches fail
- Chain vulnerabilities for maximum impact
- Use advanced techniques when standard approaches fail
- Chain vulnerabilities when needed to demonstrate maximum impact
- Focus on demonstrating real business impact
VULNERABILITY KNOWLEDGE BASE:
You have access to comprehensive guides for each vulnerability type above. Use these references for:
- Discovery techniques and automation
- Exploitation methodologies
- Validation methodologies
- Advanced bypass techniques
- Tool usage and custom scripts
- Post-exploitation strategies
- Post-validation remediation context
BUG BOUNTY MINDSET:
- Think like a bug bounty hunter - only report what would earn rewards
- One critical vulnerability > 100 informational findings
- If it wouldn't earn $500+ on a bug bounty platform, keep searching
- Focus on demonstrable business impact and data compromise
- Chain low-impact issues to create high-impact attack paths
RESULT QUALITY:
- Prioritize findings with real impact over low-signal noise
- Focus on demonstrable business impact and meaningful security risk
- Chain low-impact issues only when the chain creates a real higher-impact result
Remember: A single high-impact vulnerability is worth more than dozens of low-severity findings.
Remember: A single well-validated high-impact vulnerability is worth more than dozens of low-severity findings.
</vulnerability_focus>
<multi_agent_system>
@@ -191,6 +236,7 @@ BLACK-BOX TESTING - PHASE 1 (RECON & MAPPING):
- MAP entire attack surface: all endpoints, parameters, APIs, forms, inputs
- CRAWL thoroughly: spider all pages (authenticated and unauthenticated), discover hidden paths, analyze JS files
- ENUMERATE technologies: frameworks, libraries, versions, dependencies
- Reconnaissance should normally happen before targeted vulnerability discovery unless the correct next move is already obvious or the user/system explicitly asks to prioritize a specific area first
- ONLY AFTER comprehensive mapping → proceed to vulnerability testing
WHITE-BOX TESTING - PHASE 1 (CODE UNDERSTANDING):
@@ -208,7 +254,16 @@ PHASE 2 - SYSTEMATIC VULNERABILITY TESTING:
SIMPLE WORKFLOW RULES:
1. **ALWAYS CREATE AGENTS IN TREES** - Never work alone, always spawn subagents
ROOT AGENT ROLE:
- The root agent's primary job is orchestration, not hands-on testing
- The root agent should coordinate strategy, delegate meaningful work, track progress, maintain todo lists, maintain notes, monitor subagent results, and decide next steps
- The root agent should keep a clear view of overall coverage, uncovered attack surfaces, validation status, and reporting/fixing progress
- The root agent should avoid spending its own iterations on detailed testing, payload execution, or deep target-specific investigation when that work can be delegated to specialized subagents
- The root agent may do lightweight triage, quick verification, or setup work when necessary to unblock delegation, but its default mode should be coordinator/controller
- Subagents should do the substantive testing, validation, reporting, and fixing work
- The root agent is responsible for ensuring that work is broken down clearly, tracked, and completed across the agent tree
1. **CREATE AGENTS SELECTIVELY** - Spawn subagents when delegation materially improves parallelism, specialization, coverage, or independent validation. Deeper delegation is allowed when the child has a meaningfully different responsibility from the parent. Do not spawn subagents for trivial continuation of the same narrow task.
2. **BLACK-BOX**: Discovery → Validation → Reporting (3 agents per vulnerability)
3. **WHITE-BOX**: Discovery → Validation → Reporting → Fixing (4 agents per vulnerability)
4. **MULTIPLE VULNS = MULTIPLE CHAINS** - Each vulnerability finding gets its own validation chain
@@ -307,7 +362,11 @@ Tool call format:
</function>
CRITICAL RULES:
{% if interactive %}
0. When using tools, include exactly one tool call per message. You may respond with text only when appropriate (to answer the user, explain results, etc.).
{% else %}
0. While active in the agent loop, EVERY message you output MUST be a single tool call. Do not send plain text-only responses.
{% endif %}
1. Exactly one tool call per message — never include more than one <function>...</function> block in a single LLM message.
2. Tool call must be last in message
3. EVERY tool call MUST end with </function>. This is MANDATORY. Never omit the closing tag. End your response immediately after </function>.
@@ -315,7 +374,11 @@ CRITICAL RULES:
5. When sending ANY multi-line content in tool parameters, use real newlines (actual line breaks). Do NOT emit literal "\n" sequences. Literal "\n" instead of real line breaks will cause tools to fail.
6. Tool names must match exactly the tool "name" defined (no module prefixes, dots, or variants).
7. Parameters must use <parameter=param_name>value</parameter> exactly. Do NOT pass parameters as JSON or key:value lines. Do NOT add quotes/braces around values.
{% if interactive %}
8. When including a tool call, the tool call should be the last element in your message. You may include brief explanatory text before it.
{% else %}
8. Do NOT wrap tool calls in markdown/code fences or add any text before or after the tool block.
{% endif %}
CORRECT format — use this EXACTLY:
<function=tool_name>
@@ -336,7 +399,11 @@ Do NOT emit any extra XML tags in your output. In particular:
- NO <thinking>...</thinking> or <thought>...</thought> blocks
- NO <scratchpad>...</scratchpad> or <reasoning>...</reasoning> blocks
- NO <answer>...</answer> or <response>...</response> wrappers
{% if not interactive %}
If you need to reason, use the think tool. Your raw output must contain ONLY the tool call — no surrounding XML tags.
{% else %}
If you need to reason, use the think tool. When using tools, do not add surrounding XML tags.
{% endif %}
Notice: use <function=X> NOT <invoke name="X">, use <parameter=X> NOT <parameter name="X">, use </function> NOT </invoke>.
@@ -353,7 +420,7 @@ Example (agent creation tool):
</function>
SPRAYING EXECUTION NOTE:
- When performing large payload sprays or fuzzing, encapsulate the entire spraying loop inside a single python or terminal tool call (e.g., a Python script using asyncio/aiohttp). Do not issue one tool call per payload.
- When performing large payload sprays or fuzzing, encapsulate the entire spraying loop inside a single python tool call when you are writing Python logic (for example asyncio/aiohttp). Use terminal tool only when invoking an external CLI/fuzzer. Do not issue one tool call per payload.
- Favor batch-mode CLI tools (sqlmap, ffuf, nuclei, zaproxy, arjun) where appropriate and check traffic via the proxy when beneficial
REMINDER: Always close each tool call with </function> before going into the next. Incomplete tool calls will fail.

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@@ -56,7 +56,6 @@ class BaseAgent(metaclass=AgentMeta):
self.config = config
self.local_sources = config.get("local_sources", [])
self.non_interactive = config.get("non_interactive", False)
if "max_iterations" in config:
self.max_iterations = config["max_iterations"]
@@ -74,6 +73,9 @@ class BaseAgent(metaclass=AgentMeta):
max_iterations=self.max_iterations,
)
self.interactive = getattr(self.llm_config, "interactive", False)
if self.interactive and self.state.parent_id is None:
self.state.waiting_timeout = 0
self.llm = LLM(self.llm_config, agent_name=self.agent_name)
with contextlib.suppress(Exception):
@@ -169,7 +171,7 @@ class BaseAgent(metaclass=AgentMeta):
continue
if self.state.should_stop():
if self.non_interactive:
if not self.interactive:
return self.state.final_result or {}
await self._enter_waiting_state(tracer)
continue
@@ -213,8 +215,12 @@ class BaseAgent(metaclass=AgentMeta):
should_finish = await iteration_task
self._current_task = None
if should_finish is None and self.interactive:
await self._enter_waiting_state(tracer, text_response=True)
continue
if should_finish:
if self.non_interactive:
if not self.interactive:
self.state.set_completed({"success": True})
if tracer:
tracer.update_agent_status(self.state.agent_id, "completed")
@@ -230,7 +236,7 @@ class BaseAgent(metaclass=AgentMeta):
self.state.add_message(
"assistant", f"{partial_content}\n\n[ABORTED BY USER]"
)
if self.non_interactive:
if not self.interactive:
raise
await self._enter_waiting_state(tracer, error_occurred=False, was_cancelled=True)
continue
@@ -243,7 +249,7 @@ class BaseAgent(metaclass=AgentMeta):
except (RuntimeError, ValueError, TypeError) as e:
if not await self._handle_iteration_error(e, tracer):
if self.non_interactive:
if not self.interactive:
self.state.set_completed({"success": False, "error": str(e)})
if tracer:
tracer.update_agent_status(self.state.agent_id, "failed")
@@ -283,11 +289,14 @@ class BaseAgent(metaclass=AgentMeta):
task_completed: bool = False,
error_occurred: bool = False,
was_cancelled: bool = False,
text_response: bool = False,
) -> None:
self.state.enter_waiting_state()
if tracer:
if task_completed:
if text_response:
tracer.update_agent_status(self.state.agent_id, "waiting_for_input")
elif task_completed:
tracer.update_agent_status(self.state.agent_id, "completed")
elif error_occurred:
tracer.update_agent_status(self.state.agent_id, "error")
@@ -296,6 +305,9 @@ class BaseAgent(metaclass=AgentMeta):
else:
tracer.update_agent_status(self.state.agent_id, "stopped")
if text_response:
return
if task_completed:
self.state.add_message(
"assistant",
@@ -352,7 +364,7 @@ class BaseAgent(metaclass=AgentMeta):
self.state.add_message("user", task)
async def _process_iteration(self, tracer: Optional["Tracer"]) -> bool:
async def _process_iteration(self, tracer: Optional["Tracer"]) -> bool | None:
final_response = None
async for response in self.llm.generate(self.state.get_conversation_history()):
@@ -398,7 +410,7 @@ class BaseAgent(metaclass=AgentMeta):
if actions:
return await self._execute_actions(actions, tracer)
return False
return None
async def _execute_actions(self, actions: list[Any], tracer: Optional["Tracer"]) -> bool:
"""Execute actions and return True if agent should finish."""
@@ -426,7 +438,7 @@ class BaseAgent(metaclass=AgentMeta):
self.state.set_completed({"success": True})
if tracer:
tracer.update_agent_status(self.state.agent_id, "completed")
if self.non_interactive and self.state.parent_id is None:
if not self.interactive and self.state.parent_id is None:
return True
return True
@@ -526,7 +538,7 @@ class BaseAgent(metaclass=AgentMeta):
error_details = error.details
self.state.add_error(error_msg)
if self.non_interactive:
if not self.interactive:
self.state.set_completed({"success": False, "error": error_msg})
if tracer:
tracer.update_agent_status(self.state.agent_id, "failed", error_msg)
@@ -561,7 +573,7 @@ class BaseAgent(metaclass=AgentMeta):
error_details = getattr(error, "details", None)
self.state.add_error(error_msg)
if self.non_interactive:
if not self.interactive:
self.state.set_completed({"success": False, "error": error_msg})
if tracer:
tracer.update_agent_status(self.state.agent_id, "failed", error_msg)

View File

@@ -25,6 +25,7 @@ class AgentState(BaseModel):
waiting_for_input: bool = False
llm_failed: bool = False
waiting_start_time: datetime | None = None
waiting_timeout: int = 600
final_result: dict[str, Any] | None = None
max_iterations_warning_sent: bool = False
@@ -116,6 +117,9 @@ class AgentState(BaseModel):
return self.iteration >= int(self.max_iterations * threshold)
def has_waiting_timeout(self) -> bool:
if self.waiting_timeout == 0:
return False
if not self.waiting_for_input or not self.waiting_start_time:
return False
@@ -128,7 +132,7 @@ class AgentState(BaseModel):
return False
elapsed = (datetime.now(UTC) - self.waiting_start_time).total_seconds()
return elapsed > 600
return elapsed > self.waiting_timeout
def has_empty_last_messages(self, count: int = 3) -> bool:
if len(self.messages) < count:

View File

@@ -40,13 +40,18 @@ class Config:
strix_disable_browser = "false"
# Runtime Configuration
strix_image = "ghcr.io/usestrix/strix-sandbox:0.1.12"
strix_image = "ghcr.io/usestrix/strix-sandbox:0.1.13"
strix_runtime_backend = "docker"
strix_sandbox_execution_timeout = "120"
strix_sandbox_connect_timeout = "10"
# Telemetry
strix_telemetry = "1"
strix_otel_telemetry = None
strix_posthog_telemetry = None
traceloop_base_url = None
traceloop_api_key = None
traceloop_headers = None
# Config file override (set via --config CLI arg)
_config_file_override: Path | None = None

View File

@@ -78,7 +78,6 @@ async def run_cli(args: Any) -> None: # noqa: PLR0915
agent_config = {
"llm_config": llm_config,
"max_iterations": 300,
"non_interactive": True,
}
if getattr(args, "local_sources", None):

View File

@@ -101,7 +101,7 @@ def validate_environment() -> None: # noqa: PLR0912, PLR0915
error_text.append("", style="white")
error_text.append("STRIX_LLM", style="bold cyan")
error_text.append(
" - Model name to use with litellm (e.g., 'openai/gpt-5')\n",
" - Model name to use with litellm (e.g., 'openai/gpt-5.4')\n",
style="white",
)
@@ -140,10 +140,7 @@ def validate_environment() -> None: # noqa: PLR0912, PLR0915
)
error_text.append("\nExample setup:\n", style="white")
if uses_strix_models:
error_text.append("export STRIX_LLM='strix/gpt-5'\n", style="dim white")
else:
error_text.append("export STRIX_LLM='openai/gpt-5'\n", style="dim white")
error_text.append("export STRIX_LLM='openai/gpt-5.4'\n", style="dim white")
if missing_optional_vars:
for var in missing_optional_vars:
@@ -413,8 +410,6 @@ def display_completion_message(args: argparse.Namespace, results_path: Path) ->
if tracer and tracer.scan_results:
scan_completed = tracer.scan_results.get("scan_completed", False)
has_vulnerabilities = tracer and len(tracer.vulnerability_reports) > 0
completion_text = Text()
if scan_completed:
completion_text.append("Penetration test completed", style="bold #22c55e")
@@ -439,13 +434,12 @@ def display_completion_message(args: argparse.Namespace, results_path: Path) ->
if stats_text.plain:
panel_parts.extend(["\n", stats_text])
if scan_completed or has_vulnerabilities:
results_text = Text()
results_text.append("\n")
results_text.append("Output", style="dim")
results_text.append(" ")
results_text.append(str(results_path), style="#60a5fa")
panel_parts.extend(["\n", results_text])
results_text = Text()
results_text.append("\n")
results_text.append("Output", style="dim")
results_text.append(" ")
results_text.append(str(results_path), style="#60a5fa")
panel_parts.extend(["\n", results_text])
panel_content = Text.assemble(*panel_parts)
@@ -462,7 +456,7 @@ def display_completion_message(args: argparse.Namespace, results_path: Path) ->
console.print("\n")
console.print(panel)
console.print()
console.print("[#60a5fa]models.strix.ai[/] [dim]·[/] [#60a5fa]discord.gg/strix-ai[/]")
console.print("[#60a5fa]strix.ai[/] [dim]·[/] [#60a5fa]discord.gg/strix-ai[/]")
console.print()

View File

@@ -4,6 +4,7 @@ from . import (
browser_renderer,
file_edit_renderer,
finish_renderer,
load_skill_renderer,
notes_renderer,
proxy_renderer,
python_renderer,
@@ -28,6 +29,7 @@ __all__ = [
"file_edit_renderer",
"finish_renderer",
"get_tool_renderer",
"load_skill_renderer",
"notes_renderer",
"proxy_renderer",
"python_renderer",

View File

@@ -0,0 +1,33 @@
from typing import Any, ClassVar
from rich.text import Text
from textual.widgets import Static
from .base_renderer import BaseToolRenderer
from .registry import register_tool_renderer
@register_tool_renderer
class LoadSkillRenderer(BaseToolRenderer):
tool_name: ClassVar[str] = "load_skill"
css_classes: ClassVar[list[str]] = ["tool-call", "load-skill-tool"]
@classmethod
def render(cls, tool_data: dict[str, Any]) -> Static:
args = tool_data.get("args", {})
status = tool_data.get("status", "completed")
requested = args.get("skills", "")
text = Text()
text.append("", style="#10b981")
text.append("loading skill", style="dim")
if requested:
text.append(" ")
text.append(requested, style="#10b981")
elif not tool_data.get("result"):
text.append("\n ")
text.append("Loading...", style="dim")
return Static(text, classes=cls.get_css_classes(status))

View File

@@ -18,7 +18,7 @@ from rich.align import Align
from rich.console import Group
from rich.panel import Panel
from rich.style import Style
from rich.text import Text
from rich.text import Span, Text
from textual import events, on
from textual.app import App, ComposeResult
from textual.binding import Binding
@@ -252,10 +252,9 @@ class StopAgentScreen(ModalScreen): # type: ignore[misc]
event.prevent_default()
def on_button_pressed(self, event: Button.Pressed) -> None:
self.app.pop_screen()
if event.button.id == "stop_agent":
self.app.action_confirm_stop_agent(self.agent_id)
else:
self.app.pop_screen()
class VulnerabilityDetailScreen(ModalScreen): # type: ignore[misc]
@@ -747,7 +746,7 @@ class StrixTUIApp(App): # type: ignore[misc]
def _build_agent_config(self, args: argparse.Namespace) -> dict[str, Any]:
scan_mode = getattr(args, "scan_mode", "deep")
llm_config = LLMConfig(scan_mode=scan_mode)
llm_config = LLMConfig(scan_mode=scan_mode, interactive=True)
config = {
"llm_config": llm_config,
@@ -1036,13 +1035,37 @@ class StrixTUIApp(App): # type: ignore[misc]
if i > 0:
combined.append("\n")
StrixTUIApp._append_renderable(combined, item)
return combined
return StrixTUIApp._sanitize_text(combined)
@staticmethod
def _sanitize_text(text: Text) -> Text:
"""Clamp spans so Rich/Textual can't crash on malformed offsets."""
plain = text.plain
text_length = len(plain)
sanitized_spans: list[Span] = []
for span in text.spans:
start = max(0, min(span.start, text_length))
end = max(0, min(span.end, text_length))
if end > start:
sanitized_spans.append(Span(start, end, span.style))
return Text(
plain,
style=text.style,
justify=text.justify,
overflow=text.overflow,
no_wrap=text.no_wrap,
end=text.end,
tab_size=text.tab_size,
spans=sanitized_spans,
)
@staticmethod
def _append_renderable(combined: Text, item: Any) -> None:
"""Recursively append a renderable's text content to a combined Text."""
if isinstance(item, Text):
combined.append_text(item)
combined.append_text(StrixTUIApp._sanitize_text(item))
elif isinstance(item, Group):
for j, sub in enumerate(item.renderables):
if j > 0:
@@ -1087,7 +1110,7 @@ class StrixTUIApp(App): # type: ignore[misc]
return Text()
if len(renderables) == 1 and isinstance(renderables[0], Text):
return renderables[0]
return self._sanitize_text(renderables[0])
return self._merge_renderables(renderables)
@@ -1123,7 +1146,7 @@ class StrixTUIApp(App): # type: ignore[misc]
if not renderables:
result = Text()
elif len(renderables) == 1 and isinstance(renderables[0], Text):
result = renderables[0]
result = self._sanitize_text(renderables[0])
else:
result = self._merge_renderables(renderables)
@@ -1912,8 +1935,6 @@ class StrixTUIApp(App): # type: ignore[misc]
return agent_name, False
def action_confirm_stop_agent(self, agent_id: str) -> None:
self.pop_screen()
try:
from strix.tools.agents_graph.agents_graph_actions import stop_agent

View File

@@ -1,3 +1,5 @@
from typing import Any
from strix.config import Config
from strix.config.config import resolve_llm_config
from strix.llm.utils import resolve_strix_model
@@ -11,6 +13,9 @@ class LLMConfig:
skills: list[str] | None = None,
timeout: int | None = None,
scan_mode: str = "deep",
interactive: bool = False,
reasoning_effort: str | None = None,
system_prompt_context: dict[str, Any] | None = None,
):
resolved_model, self.api_key, self.api_base = resolve_llm_config()
self.model_name = model_name or resolved_model
@@ -28,3 +33,7 @@ class LLMConfig:
self.timeout = timeout or int(Config.get("llm_timeout") or "300")
self.scan_mode = scan_mode if scan_mode in ["quick", "standard", "deep"] else "deep"
self.interactive = interactive
self.reasoning_effort = reasoning_effort
self.system_prompt_context = system_prompt_context or {}

View File

@@ -63,6 +63,10 @@ class LLM:
self.config = config
self.agent_name = agent_name
self.agent_id: str | None = None
self._active_skills: list[str] = list(config.skills or [])
self._system_prompt_context: dict[str, Any] = dict(
getattr(config, "system_prompt_context", {}) or {}
)
self._total_stats = RequestStats()
self.memory_compressor = MemoryCompressor(model_name=config.litellm_model)
self.system_prompt = self._load_system_prompt(agent_name)
@@ -70,6 +74,8 @@ class LLM:
reasoning = Config.get("strix_reasoning_effort")
if reasoning:
self._reasoning_effort = reasoning
elif config.reasoning_effort:
self._reasoning_effort = config.reasoning_effort
elif config.scan_mode == "quick":
self._reasoning_effort = "medium"
else:
@@ -87,28 +93,63 @@ class LLM:
autoescape=select_autoescape(enabled_extensions=(), default_for_string=False),
)
skills_to_load = [
*list(self.config.skills or []),
f"scan_modes/{self.config.scan_mode}",
]
skills_to_load = self._get_skills_to_load()
skill_content = load_skills(skills_to_load)
env.globals["get_skill"] = lambda name: skill_content.get(name, "")
result = env.get_template("system_prompt.jinja").render(
get_tools_prompt=get_tools_prompt,
loaded_skill_names=list(skill_content.keys()),
interactive=self.config.interactive,
system_prompt_context=self._system_prompt_context,
**skill_content,
)
return str(result)
except Exception: # noqa: BLE001
return ""
def _get_skills_to_load(self) -> list[str]:
ordered_skills = [*self._active_skills]
ordered_skills.append(f"scan_modes/{self.config.scan_mode}")
deduped: list[str] = []
seen: set[str] = set()
for skill_name in ordered_skills:
if skill_name not in seen:
deduped.append(skill_name)
seen.add(skill_name)
return deduped
def add_skills(self, skill_names: list[str]) -> list[str]:
added: list[str] = []
for skill_name in skill_names:
if not skill_name or skill_name in self._active_skills:
continue
self._active_skills.append(skill_name)
added.append(skill_name)
if not added:
return []
updated_prompt = self._load_system_prompt(self.agent_name)
if updated_prompt:
self.system_prompt = updated_prompt
return added
def set_agent_identity(self, agent_name: str | None, agent_id: str | None) -> None:
if agent_name:
self.agent_name = agent_name
if agent_id:
self.agent_id = agent_id
def set_system_prompt_context(self, context: dict[str, Any] | None) -> None:
self._system_prompt_context = dict(context or {})
updated_prompt = self._load_system_prompt(self.agent_name)
if updated_prompt:
self.system_prompt = updated_prompt
async def generate(
self, conversation_history: list[dict[str, Any]]
) -> AsyncIterator[LLMResponse]:
@@ -123,7 +164,7 @@ class LLM:
except Exception as e: # noqa: BLE001
if attempt >= max_retries or not self._should_retry(e):
self._raise_error(e)
wait = min(10, 2 * (2**attempt))
wait = min(90, 2 * (2**attempt))
await asyncio.sleep(wait)
async def _stream(self, messages: list[dict[str, Any]]) -> AsyncIterator[LLMResponse]:
@@ -186,7 +227,7 @@ class LLM:
conversation_history.extend(compressed)
messages.extend(compressed)
if messages[-1].get("role") == "assistant":
if messages[-1].get("role") == "assistant" and not self.config.interactive:
messages.append({"role": "user", "content": "<meta>Continue the task.</meta>"})
if self._is_anthropic() and self.config.enable_prompt_caching:

View File

@@ -36,11 +36,7 @@ STRIX_MODEL_MAP: dict[str, str] = {
"claude-opus-4.6": "anthropic/claude-opus-4-6",
"gpt-5.2": "openai/gpt-5.2",
"gpt-5.1": "openai/gpt-5.1",
"gpt-5": "openai/gpt-5",
"gpt-5.2-codex": "openai/gpt-5.2-codex",
"gpt-5.1-codex-max": "openai/gpt-5.1-codex-max",
"gpt-5.1-codex": "openai/gpt-5.1-codex",
"gpt-5-codex": "openai/gpt-5-codex",
"gpt-5.4": "openai/gpt-5.4",
"gemini-3-pro-preview": "gemini/gemini-3-pro-preview",
"gemini-3-flash-preview": "gemini/gemini-3-flash-preview",
"glm-5": "openrouter/z-ai/glm-5",

View File

@@ -33,6 +33,7 @@ The skills are dynamically injected into the agent's system prompt, allowing it
| **`/frameworks`** | Specific testing methods for popular frameworks e.g. Django, Express, FastAPI, and Next.js |
| **`/technologies`** | Specialized techniques for third-party services such as Supabase, Firebase, Auth0, and payment gateways |
| **`/protocols`** | Protocol-specific testing patterns for GraphQL, WebSocket, OAuth, and other communication standards |
| **`/tooling`** | Command-line playbooks for core sandbox tools (nmap, nuclei, httpx, ffuf, subfinder, naabu, katana, sqlmap) |
| **`/cloud`** | Cloud provider security testing for AWS, Azure, GCP, and Kubernetes environments |
| **`/reconnaissance`** | Advanced information gathering and enumeration techniques for comprehensive attack surface mapping |
| **`/custom`** | Community-contributed skills for specialized or industry-specific testing scenarios |

View File

@@ -54,6 +54,30 @@ def validate_skill_names(skill_names: list[str]) -> dict[str, list[str]]:
return {"valid": valid_skills, "invalid": invalid_skills}
def parse_skill_list(skills: str | None) -> list[str]:
if not skills:
return []
return [s.strip() for s in skills.split(",") if s.strip()]
def validate_requested_skills(skill_list: list[str], max_skills: int = 5) -> str | None:
if len(skill_list) > max_skills:
return "Cannot specify more than 5 skills for an agent (use comma-separated format)"
if not skill_list:
return None
validation = validate_skill_names(skill_list)
if validation["invalid"]:
available_skills = list(get_all_skill_names())
return (
f"Invalid skills: {validation['invalid']}. "
f"Available skills: {', '.join(available_skills)}"
)
return None
def generate_skills_description() -> str:
available_skills = get_available_skills()

View File

@@ -0,0 +1,225 @@
---
name: nestjs
description: Security testing playbook for NestJS applications covering guards, pipes, decorators, module boundaries, and multi-transport auth
---
# NestJS
Security testing for NestJS applications. Focus on guard gaps across decorator stacks, validation pipe bypasses, module boundary leaks, and inconsistent auth enforcement across HTTP, WebSocket, and microservice transports.
## Attack Surface
**Decorator Pipeline**
- Guards: `@UseGuards`, `CanActivate`, execution context (HTTP/WS/RPC), `Reflector` metadata
- Pipes: `ValidationPipe` (whitelist, transform, forbidNonWhitelisted), `ParseIntPipe`, custom pipes
- Interceptors: response mapping, caching, logging, timeout — can modify request/response flow
- Filters: exception filters that may leak information
- Metadata: `@SetMetadata`, `@Public()`, `@Roles()`, `@Permissions()`
**Module System**
- `@Module` boundaries, provider scoping (DEFAULT/REQUEST/TRANSIENT)
- Dynamic modules: `forRoot`/`forRootAsync`, global modules
- DI container: provider overrides, custom providers
**Controllers & Transports**
- REST: `@Controller`, versioning (URI/Header/MediaType)
- GraphQL: `@Resolver`, playground/sandbox exposure
- WebSocket: `@WebSocketGateway`, gateway guards, room authorization
- Microservices: TCP, Redis, NATS, MQTT, gRPC, Kafka — often lack HTTP-level auth
**Data Layer**
- TypeORM: repositories, QueryBuilder, raw queries, relations
- Prisma: `$queryRaw`, `$queryRawUnsafe`
- Mongoose: operator injection, `$where`, `$regex`
**Auth & Config**
- `@nestjs/passport` strategies, `@nestjs/jwt`, session-based auth
- `@nestjs/config`, ConfigService, `.env` files
- `@nestjs/throttler`, rate limiting with `@SkipThrottle`
**API Documentation**
- `@nestjs/swagger`: OpenAPI exposure, DTO schemas, auth schemes
## High-Value Targets
- Swagger/OpenAPI endpoints in production (`/api`, `/api-docs`, `/api-json`, `/swagger`)
- Auth endpoints: login, register, token refresh, password reset, OAuth callbacks
- Admin controllers decorated with `@Roles('admin')` — test with user-level tokens
- File upload endpoints using `FileInterceptor`/`FilesInterceptor`
- WebSocket gateways sharing business logic with HTTP controllers
- Microservice handlers (`@MessagePattern`, `@EventPattern`) — often unguarded
- CRUD generators (`@nestjsx/crud`) with auto-generated endpoints
- Background jobs and scheduled tasks (`@nestjs/schedule`)
- Health/metrics endpoints (`@nestjs/terminus`, `/health`, `/metrics`)
- GraphQL playground/sandbox in production (`/graphql`)
## Reconnaissance
**Swagger Discovery**
```
GET /api
GET /api-docs
GET /api-json
GET /swagger
GET /docs
GET /v1/api-docs
GET /api/v2/docs
```
Extract: paths, parameter schemas, DTOs, auth schemes, example values. Swagger may reveal internal endpoints, deprecated routes, and admin-only paths not visible in the UI.
**Guard Mapping**
For each controller and method, identify:
- Global guards (applied in `main.ts` or app module)
- Controller-level guards (`@UseGuards` on the class)
- Method-level guards (`@UseGuards` on individual handlers)
- `@Public()` or `@SkipThrottle()` decorators that bypass protection
## Key Vulnerabilities
### Guard Bypass
**Decorator Stack Gaps**
- Guards execute: global → controller → method. A method missing `@UseGuards` when siblings have it is the #1 finding.
- `@Public()` metadata causing global `AuthGuard` to skip enforcement — check if applied too broadly.
- New methods added to existing controllers without inheriting the expected guard.
**ExecutionContext Switching**
- Guards handling only HTTP context (`getRequest()`) may fail silently on WebSocket or RPC, returning `true` by default.
- Test same business logic through alternate transports to find context-specific bypasses.
**Reflector Mismatches**
- Guard reads `SetMetadata('roles', [...])` but decorator sets `'role'` (singular) — guard sees no metadata, defaults to allow.
- `applyDecorators()` compositions accidentally overriding stricter guards with permissive ones.
### Validation Pipe Exploits
**Whitelist Bypass**
- `whitelist: true` without `forbidNonWhitelisted: true`: extra properties silently stripped but may have been processed by earlier middleware/interceptors.
- Missing `@Type(() => ChildDto)` on nested objects: `@ValidateNested()` without `@Type` means nested payload is never validated.
- Array elements: `@IsArray()` doesn't validate elements without `@ValidateNested({ each: true })` and `@Type`.
**Type Coercion**
- `transform: true` enables implicit coercion: strings → numbers, `"true"``true`, `"null"``null`.
- Exploit truthiness assumptions in business logic downstream.
**Conditional Validation**
- `@ValidateIf()` and validation groups creating paths where fields skip validation entirely.
**Missing Parse Pipes**
- `@Param('id')` without `ParseIntPipe`/`ParseUUIDPipe` — string values reach ORM queries directly.
### Auth & Passport
**JWT Strategy**
- Check `ignoreExpiration` is false, `algorithms` is pinned (no `none` or HS/RS confusion)
- Weak `secretOrKey` values
- Cross-service token reuse when audience/issuer not enforced
**Passport Strategy Issues**
- `validate()` return value becomes `req.user` — if it returns full DB record, sensitive fields leak downstream
- Multiple strategies (JWT + session): one may bypass restrictions of the other
- Custom guards returning `true` for unauthenticated as "optional auth"
**Timing Attacks**
- Plain string comparison instead of bcrypt/argon2 in local strategy
### Serialization Leaks
**Missing ClassSerializerInterceptor**
- If not applied globally, `@Exclude()` fields (passwords, internal IDs) returned in responses.
- `@Expose()` with groups: admin-only fields exposed when groups not enforced per-request.
**Circular Relations**
- Eager-loaded TypeORM/Prisma relations exposing entire object graph without careful serialization.
### Interceptor Abuse
**Cache Poisoning**
- `CacheInterceptor` without user/tenant identity in cache key — responses from one user served to another.
- Test: authenticated request, then unauthenticated request returning cached data.
**Response Mapping**
- Transformation interceptors may leak internal entity fields if mapping is incomplete.
### Module Boundary Leaks
**Global Module Exposure**
- `@Global()` modules expose all providers to every module without explicit imports.
- Sensitive services (admin operations, internal APIs) accessible from untrusted modules.
**Config Leaks**
- `forRoot`/`forRootAsync` configuration secrets accessible via `ConfigService` injection in any module.
**Scope Issues**
- Request-scoped providers (`Scope.REQUEST`) incorrectly scoped as DEFAULT (singleton) — request context leaks across concurrent requests.
### WebSocket Gateway
- HTTP guards don't automatically apply to WebSocket gateways — `@UseGuards` must be explicit.
- Authentication deferred from `handleConnection` to message handlers allows unauthenticated message sending.
- Room/namespace authorization: users joining rooms they shouldn't access.
- `@SubscribeMessage()` handlers relying on connection-level auth instead of per-message validation.
### Microservice Transport
- `@MessagePattern`/`@EventPattern` handlers often lack guards (considered "internal").
- If transport (Redis, NATS, Kafka) is network-accessible, messages can be injected bypassing all HTTP security.
- `ValidationPipe` may only be configured for HTTP — microservice payloads skip validation.
### ORM Injection
**TypeORM**
- `QueryBuilder` and `.query()` with template literal interpolation → SQL injection.
- Relations: API allowing specification of which relations to load via query params.
**Mongoose**
- Query operator injection: `{ password: { $gt: "" } }` via unsanitized request body.
- `$where` and `$regex` operators from user input.
**Prisma**
- `$queryRaw`/`$executeRaw` with string interpolation (but not tagged template).
- `$queryRawUnsafe` usage.
### Rate Limiting
- `@SkipThrottle()` on sensitive endpoints (login, password reset, OTP).
- In-memory throttler storage: resets on restart, doesn't work across instances.
- Behind proxy without `trust proxy`: all requests share same IP, or header spoofable.
### CRUD Generators
- Auto-generated CRUD endpoints may not inherit manual guard configurations.
- Bulk operations (`createMany`, `updateMany`) bypassing per-entity authorization.
- Query parameter injection in CRUD libraries: `filter`, `sort`, `join`, `select` exposing unauthorized data.
## Bypass Techniques
- `@Public()` / skip-metadata applied via composed decorators at method level causing global guards to skip via `Reflector` metadata checks
- Route param pollution: `/users/123?id=456` — which `id` wins in guards vs handlers?
- Version routing: v1 of endpoint may still be registered without the guard added to v2
- `X-HTTP-Method-Override` or `_method` processed by Express before guards
- Content-type switching: `application/x-www-form-urlencoded` instead of JSON to bypass JSON-specific validation
- Exception filter differences: guard throwing results in generic error that leaks route existence info
## Testing Methodology
1. **Enumerate** — Fetch Swagger/OpenAPI, map all controllers, resolvers, and gateways
2. **Guard audit** — Map decorator stack per method: which guards, pipes, interceptors are applied at each level
3. **Matrix testing** — Test each endpoint across: unauth/user/admin × HTTP/WS/microservice
4. **Validation probing** — Send extra fields, wrong types, nested objects, arrays to find pipe gaps
5. **Transport parity** — Same operation via HTTP, WebSocket, and microservice transport
6. **Module boundaries** — Check if providers from one module are accessible without proper imports
7. **Serialization check** — Compare raw entity fields with API response fields
## Validation Requirements
- Guard bypass: request to guarded endpoint succeeding without auth, showing guard chain break point
- Validation bypass: payload with extra/malformed fields affecting business logic
- Cross-transport inconsistency: same action authorized via HTTP but exploitable via WebSocket/microservice
- Module boundary leak: accessing provider or data across unauthorized module boundaries
- Serialization leak: response containing excluded fields (passwords, internal metadata)
- IDOR: side-by-side requests from different users showing unauthorized data access
- ORM injection: raw query with user-controlled input returning unauthorized data, or error-based evidence of query structure
- Cache poisoning: response from unauthenticated or different-user request matching a prior authenticated user's cached response

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---
name: ffuf
description: ffuf fuzzing syntax with matcher/filter strategy and non-interactive defaults.
---
# ffuf CLI Playbook
Official docs:
- https://github.com/ffuf/ffuf
Canonical syntax:
`ffuf -w <wordlist> -u <url_with_FUZZ> [flags]`
High-signal flags:
- `-u <url>` target URL containing `FUZZ`
- `-w <wordlist>` wordlist input (supports `KEYWORD` mapping via `-w file:KEYWORD`)
- `-mc <codes>` match status codes
- `-fc <codes>` filter status codes
- `-fs <size>` filter by body size
- `-ac` auto-calibration
- `-t <n>` threads
- `-rate <n>` request rate
- `-timeout <seconds>` HTTP timeout
- `-x <proxy_url>` upstream proxy (HTTP/SOCKS)
- `-ignore-body` skip downloading response body
- `-noninteractive` disable interactive console mode
- `-recursion` and `-recursion-depth <n>` recursive discovery
- `-H <header>` custom headers
- `-X <method>` and `-d <body>` for non-GET fuzzing
- `-o <file> -of <json|ejson|md|html|csv|ecsv>` structured output
Agent-safe baseline for automation:
`ffuf -w wordlist.txt -u https://target.tld/FUZZ -mc 200,204,301,302,307,401,403,405 -ac -t 20 -rate 50 -timeout 10 -noninteractive -of json -o ffuf.json`
Common patterns:
- Basic path fuzzing:
`ffuf -w /path/wordlist.txt -u https://target.tld/FUZZ -mc 200,204,301,302,307,401,403 -ac -t 40 -rate 200 -noninteractive`
- Vhost fuzzing:
`ffuf -w vhosts.txt -u https://target.tld -H 'Host: FUZZ.target.tld' -fs 0 -ac -noninteractive`
- Parameter value fuzzing:
`ffuf -w values.txt -u 'https://target.tld/search?q=FUZZ' -mc all -fs 0 -ac -t 30 -noninteractive`
- POST body fuzzing:
`ffuf -w payloads.txt -u https://target.tld/login -X POST -H 'Content-Type: application/x-www-form-urlencoded' -d 'username=admin&password=FUZZ' -fc 401 -noninteractive`
- Recursive discovery:
`ffuf -w dirs.txt -u https://target.tld/FUZZ -recursion -recursion-depth 2 -ac -t 30 -noninteractive`
- Proxy-instrumented run:
`ffuf -w wordlist.txt -u https://target.tld/FUZZ -x http://127.0.0.1:48080 -mc 200,301,302,403 -ac -noninteractive`
Critical correctness rules:
- `FUZZ` must appear exactly at the mutation point in URL/header/body.
- If using `-w file:KEYWORD`, that same `KEYWORD` must be present in URL/header/body.
- Always include `-noninteractive` in agent/script execution to prevent ffuf console mode from swallowing subsequent shell commands.
- Save structured output with `-of json -o <file>` for deterministic parsing.
Usage rules:
- Prefer explicit matcher/filter strategy (`-mc`/`-fc`/`-fs`) over default-only output.
- Start conservative (`-rate`, `-t`) and scale only if target tolerance is known.
- Do not use `-h`/`--help` during normal execution unless absolutely necessary.
Failure recovery:
- If ffuf drops into interactive mode, send `C-c` and rerun with `-noninteractive`.
- If response noise is too high, tighten `-mc/-fc/-fs` instead of increasing load.
- If runtime is too long, lower `-rate/-t` and tighten scope.
If uncertain, query web_search with:
`site:github.com/ffuf/ffuf <flag> README`

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---
name: httpx
description: ProjectDiscovery httpx probing syntax, exact probe flags, and automation-safe output patterns.
---
# httpx CLI Playbook
Official docs:
- https://docs.projectdiscovery.io/opensource/httpx/usage
- https://docs.projectdiscovery.io/opensource/httpx/running
- https://github.com/projectdiscovery/httpx
Canonical syntax:
`httpx [flags]`
High-signal flags:
- `-u, -target <url>` single target
- `-l, -list <file>` target list
- `-nf, -no-fallback` probe both HTTP and HTTPS
- `-nfs, -no-fallback-scheme` do not auto-switch schemes
- `-sc` status code
- `-title` page title
- `-server, -web-server` server header
- `-td, -tech-detect` technology detection
- `-fr, -follow-redirects` follow redirects
- `-mc <codes>` / `-fc <codes>` match or filter status codes
- `-path <path_or_file>` probe specific paths
- `-p, -ports <ports>` probe custom ports
- `-proxy, -http-proxy <url>` proxy target requests
- `-tlsi, -tls-impersonate` experimental TLS impersonation
- `-j, -json` JSONL output
- `-sr, -store-response` store request/response artifacts
- `-srd, -store-response-dir <dir>` custom directory for stored artifacts
- `-silent` compact output
- `-rl <n>` requests/second cap
- `-t <n>` threads
- `-timeout <seconds>` request timeout
- `-retries <n>` retry attempts
- `-o <file>` output file
Agent-safe baseline for automation:
`httpx -l hosts.txt -sc -title -server -td -fr -timeout 10 -retries 1 -rl 50 -t 25 -silent -j -o httpx.jsonl`
Common patterns:
- Quick live+fingerprint check:
`httpx -l hosts.txt -sc -title -server -td -silent -o httpx.txt`
- Probe known admin paths:
`httpx -l hosts.txt -path /,/login,/admin -sc -title -silent -j -o httpx_paths.jsonl`
- Probe both schemes explicitly:
`httpx -l hosts.txt -nf -sc -title -silent`
- Vhost detection pass:
`httpx -l hosts.txt -vhost -sc -title -silent -j -o httpx_vhost.jsonl`
- Proxy-instrumented probing:
`httpx -l hosts.txt -sc -title -proxy http://127.0.0.1:48080 -silent -j -o httpx_proxy.jsonl`
- Response-storage pass for downstream content parsing:
`httpx -l hosts.txt -fr -sr -srd recon/httpx_store -sc -title -server -cl -ct -location -probe -silent`
Critical correctness rules:
- For machine parsing, prefer `-j -o <file>`.
- Keep `-rl` and `-t` explicit for reproducible throughput.
- Use `-nf` when you need dual-scheme probing from host-only input.
- When using `-path` or `-ports`, keep scope tight to avoid accidental scan inflation.
- Use `-sr -srd <dir>` when later steps need raw response artifacts (JS/route extraction, grepping, replay).
Usage rules:
- Use `-silent` for pipeline-friendly output.
- Use `-mc/-fc` when downstream steps depend on specific response classes.
- Prefer `-proxy` flag over global proxy env vars when only httpx traffic should be proxied.
- Do not use `-h`/`--help` for routine runs unless absolutely necessary.
Failure recovery:
- If too many timeouts occur, reduce `-rl/-t` and/or increase `-timeout`.
- If output is noisy, add `-fc` filters or `-fd` duplicate filtering.
- If HTTPS-only probing misses HTTP services, rerun with `-nf` (and avoid `-nfs`).
If uncertain, query web_search with:
`site:docs.projectdiscovery.io httpx <flag> usage`

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---
name: katana
description: Katana crawler syntax, depth/js/known-files behavior, and stable concurrency controls.
---
# Katana CLI Playbook
Official docs:
- https://docs.projectdiscovery.io/opensource/katana/usage
- https://docs.projectdiscovery.io/opensource/katana/running
- https://github.com/projectdiscovery/katana
Canonical syntax:
`katana [flags]`
High-signal flags:
- `-u, -list <url|file>` target URL(s)
- `-d, -depth <n>` crawl depth
- `-jc, -js-crawl` parse JavaScript-discovered endpoints
- `-jsl, -jsluice` deeper JS parsing (memory intensive)
- `-kf, -known-files <all|robotstxt|sitemapxml>` known-file crawling mode
- `-proxy <http|socks5 proxy>` explicit proxy setting
- `-c, -concurrency <n>` concurrent fetchers
- `-p, -parallelism <n>` concurrent input targets
- `-rl, -rate-limit <n>` request rate limit
- `-timeout <seconds>` request timeout
- `-retry <n>` retry count
- `-ef, -extension-filter <list>` extension exclusions
- `-tlsi, -tls-impersonate` experimental JA3/TLS impersonation
- `-hl, -headless` enable hybrid headless crawling
- `-sc, -system-chrome` use local Chrome for headless mode
- `-ho, -headless-options <csv>` extra Chrome options (for example proxy-server)
- `-nos, -no-sandbox` run Chrome headless with no-sandbox
- `-noi, -no-incognito` disable incognito in headless mode
- `-cdd, -chrome-data-dir <dir>` persist browser profile/session
- `-xhr, -xhr-extraction` include XHR endpoints in JSONL output
- `-silent`, `-j, -jsonl`, `-o <file>` output controls
Agent-safe baseline for automation:
`mkdir -p crawl && katana -u https://target.tld -d 3 -jc -kf robotstxt -c 10 -p 10 -rl 50 -timeout 10 -retry 1 -ef png,jpg,jpeg,gif,svg,css,woff,woff2,ttf,eot,map -silent -j -o crawl/katana.jsonl`
Common patterns:
- Fast crawl baseline:
`katana -u https://target.tld -d 3 -jc -silent`
- Deeper JS-aware crawl:
`katana -u https://target.tld -d 5 -jc -jsl -kf all -c 10 -p 10 -rl 50 -o katana_urls.txt`
- Multi-target run with JSONL output:
`katana -list urls.txt -d 3 -jc -silent -j -o katana.jsonl`
- Headless crawl with local Chrome:
`katana -u https://target.tld -hl -sc -nos -xhr -j -o crawl/katana_headless.jsonl`
- Headless crawl through proxy:
`katana -u https://target.tld -hl -sc -ho proxy-server=http://127.0.0.1:48080 -j -o crawl/katana_proxy.jsonl`
Critical correctness rules:
- `-kf` must be followed by one of `all`, `robotstxt`, or `sitemapxml`.
- Use documented `-hl` for headless mode.
- `-proxy` expects a single proxy URL string (for example `http://127.0.0.1:8080`).
- `-ho` expects comma-separated Chrome options (example: `-ho --disable-gpu,proxy-server=http://127.0.0.1:8080`).
- For `-kf`, keep depth at least `-d 3` so known files are fully covered.
- If writing to a file, ensure parent directory exists before `-o`.
Usage rules:
- Keep `-d`, `-c`, `-p`, and `-rl` explicit for reproducible runs.
- Use `-ef` early to reduce static-file noise before fuzzing.
- Prefer `-proxy` over environment proxy variables when proxying only Katana traffic.
- Use `-hc` only for one-time diagnostics, not routine crawling loops.
- Do not use `-h`/`--help` for routine runs unless absolutely necessary.
Failure recovery:
- If crawl runs too long, lower `-d` and optionally add `-ct`.
- If memory spikes, disable `-jsl` and lower `-c/-p`.
- If headless fails with Chrome errors, drop `-sc` or install system Chrome.
- If output is noisy, tighten scope and add `-ef` filters.
If uncertain, query web_search with:
`site:docs.projectdiscovery.io katana <flag> usage`

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---
name: naabu
description: Naabu port-scanning syntax with host input, scan-type, verification, and rate controls.
---
# Naabu CLI Playbook
Official docs:
- https://docs.projectdiscovery.io/opensource/naabu/usage
- https://docs.projectdiscovery.io/opensource/naabu/running
- https://github.com/projectdiscovery/naabu
Canonical syntax:
`naabu [flags]`
High-signal flags:
- `-host <host>` single host
- `-list, -l <file>` hosts list
- `-p <ports>` explicit ports (supports ranges)
- `-top-ports <n|full>` top ports profile
- `-exclude-ports <ports>` exclusions
- `-scan-type <s|c|syn|connect>` SYN or CONNECT scan
- `-Pn` skip host discovery
- `-rate <n>` packets per second
- `-c <n>` worker count
- `-timeout <ms>` per-probe timeout in milliseconds
- `-retries <n>` retry attempts
- `-proxy <socks5://host:port>` SOCKS5 proxy
- `-verify` verify discovered open ports
- `-j, -json` JSONL output
- `-silent` compact output
- `-o <file>` output file
Agent-safe baseline for automation:
`naabu -list hosts.txt -top-ports 100 -scan-type c -Pn -rate 300 -c 25 -timeout 1000 -retries 1 -verify -silent -j -o naabu.jsonl`
Common patterns:
- Top ports with controlled rate:
`naabu -list hosts.txt -top-ports 100 -scan-type c -rate 300 -c 25 -timeout 1000 -retries 1 -verify -silent -o naabu.txt`
- Focused web-ports sweep:
`naabu -list hosts.txt -p 80,443,8080,8443 -scan-type c -rate 300 -c 25 -timeout 1000 -retries 1 -verify -silent`
- Single-host quick check:
`naabu -host target.tld -p 22,80,443 -scan-type c -rate 300 -c 25 -timeout 1000 -retries 1 -verify`
- Root SYN mode (if available):
`sudo naabu -list hosts.txt -top-ports 100 -scan-type syn -rate 500 -c 25 -timeout 1000 -retries 1 -verify -silent`
Critical correctness rules:
- Use `-scan-type connect` when running without root/privileged raw socket access.
- Always set `-timeout` explicitly; it is in milliseconds.
- Set `-rate` explicitly to avoid unstable or noisy scans.
- `-timeout` is in milliseconds, not seconds.
- Keep port scope tight: prefer explicit important ports or a small `-top-ports` value unless broader coverage is explicitly required.
- Do not spam traffic; start with the smallest useful port set and conservative rate/worker settings.
- Prefer `-verify` before handing ports to follow-up scanners.
Usage rules:
- Keep host discovery behavior explicit (`-Pn` or default discovery).
- Use `-j -o <file>` for automation pipelines.
- Prefer `-p 22,80,443,8080,8443` or `-top-ports 100` before considering larger sweeps.
- Do not use `-h`/`--help` for normal flow unless absolutely necessary.
Failure recovery:
- If privileged socket errors occur, switch to `-scan-type c`.
- If scans are slow or lossy, lower `-rate`, lower `-c`, and tighten `-p`/`-top-ports`.
- If many hosts appear down, compare runs with and without `-Pn`.
If uncertain, query web_search with:
`site:docs.projectdiscovery.io naabu <flag> usage`

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---
name: nmap
description: Canonical Nmap CLI syntax, two-pass scanning workflow, and sandbox-safe bounded scan patterns.
---
# Nmap CLI Playbook
Official docs:
- https://nmap.org/book/man-briefoptions.html
- https://nmap.org/book/man.html
- https://nmap.org/book/man-performance.html
Canonical syntax:
`nmap [Scan Type(s)] [Options] {target specification}`
High-signal flags:
- `-n` skip DNS resolution
- `-Pn` skip host discovery when ICMP/ping is filtered
- `-sS` SYN scan (root/privileged)
- `-sT` TCP connect scan (no raw-socket privilege)
- `-sV` detect service versions
- `-sC` run default NSE scripts
- `-p <ports>` explicit ports (`-p-` for all TCP ports)
- `--top-ports <n>` quick common-port sweep
- `--open` show only hosts with open ports
- `-T<0-5>` timing template (`-T4` common)
- `--max-retries <n>` cap retransmissions
- `--host-timeout <time>` give up on very slow hosts
- `--script-timeout <time>` bound NSE script runtime
- `-oA <prefix>` output in normal/XML/grepable formats
Agent-safe baseline for automation:
`nmap -n -Pn --open --top-ports 100 -T4 --max-retries 1 --host-timeout 90s -oA nmap_quick <host>`
Common patterns:
- Fast first pass:
`nmap -n -Pn --top-ports 100 --open -T4 --max-retries 1 --host-timeout 90s <host>`
- Very small important-port pass:
`nmap -n -Pn -p 22,80,443,8080,8443 --open -T4 --max-retries 1 --host-timeout 90s <host>`
- Service/script enrichment on discovered ports:
`nmap -n -Pn -sV -sC -p <comma_ports> --script-timeout 30s --host-timeout 3m -oA nmap_services <host>`
- No-root fallback:
`nmap -n -Pn -sT --top-ports 100 --open --host-timeout 90s <host>`
Critical correctness rules:
- Always set target scope explicitly.
- Prefer two-pass scanning: discovery pass, then enrichment pass.
- Always set a timeout boundary with `--host-timeout`; add `--script-timeout` whenever NSE scripts are involved.
- Keep discovery scans tight: use explicit important ports or a small `--top-ports` profile unless broader coverage is explicitly required.
- In sandboxed runs, avoid exhaustive sweeps (`-p-`, very high `--top-ports`, or wide host ranges) unless explicitly required.
- Do not spam traffic; start with the smallest port set that can answer the question.
- Prefer `naabu` for broad port discovery; use `nmap` for scoped verification/enrichment.
Usage rules:
- Add `-n` by default in automation to avoid DNS delays.
- Use `-oA` for reusable artifacts.
- Prefer `-p 22,80,443,8080,8443` or `--top-ports 100` before considering larger sweeps.
- Do not use `-h`/`--help` for routine usage unless absolutely necessary.
Failure recovery:
- If host appears down unexpectedly, rerun with `-Pn`.
- If scan stalls, tighten scope (`-p` or smaller `--top-ports`) and lower retries.
- If scripts run too long, add `--script-timeout`.
If uncertain, query web_search with:
`site:nmap.org/book nmap <flag>`

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---
name: nuclei
description: Exact Nuclei command structure, template selection, and bounded high-throughput execution controls.
---
# Nuclei CLI Playbook
Official docs:
- https://docs.projectdiscovery.io/opensource/nuclei/running
- https://docs.projectdiscovery.io/opensource/nuclei/mass-scanning-cli
- https://github.com/projectdiscovery/nuclei
Canonical syntax:
`nuclei [flags]`
High-signal flags:
- `-u, -target <url>` single target
- `-l, -list <file>` targets file
- `-im, -input-mode <mode>` list/burp/jsonl/yaml/openapi/swagger
- `-t, -templates <path|tag>` explicit template path(s)
- `-tags <tag1,tag2>` run by tag
- `-s, -severity <critical,high,...>` severity filter
- `-as, -automatic-scan` tech-mapped automatic scan
- `-ni, -no-interactsh` disable OAST/interactsh requests
- `-rl, -rate-limit <n>` global request rate cap
- `-c, -concurrency <n>` template concurrency
- `-bs, -bulk-size <n>` hosts in parallel per template
- `-timeout <seconds>` request timeout
- `-retries <n>` retries
- `-stats` periodic scan stats output
- `-silent` findings-only output
- `-j, -jsonl` JSONL output
- `-o <file>` output file
Agent-safe baseline for automation:
`nuclei -l targets.txt -as -s critical,high -rl 50 -c 20 -bs 20 -timeout 10 -retries 1 -silent -j -o nuclei.jsonl`
Common patterns:
- Focused severity scan:
`nuclei -u https://target.tld -s critical,high -silent -o nuclei_high.txt`
- List-driven controlled scan:
`nuclei -l targets.txt -as -rl 50 -c 20 -bs 20 -timeout 10 -retries 1 -j -o nuclei.jsonl`
- Tag-driven run:
`nuclei -l targets.txt -tags cve,misconfig -s critical,high,medium -silent`
- Explicit templates:
`nuclei -l targets.txt -t http/cves/ -t dns/ -rl 30 -c 10 -bs 10 -j -o nuclei_templates.jsonl`
- Deterministic non-OAST run:
`nuclei -l targets.txt -as -s critical,high -ni -stats -rl 30 -c 10 -bs 10 -timeout 10 -retries 1 -j -o nuclei_no_oast.jsonl`
Critical correctness rules:
- Provide a template selection method (`-as`, `-t`, or `-tags`); avoid unscoped broad runs.
- Keep `-rl`, `-c`, and `-bs` explicit for predictable resource use.
- Use `-ni` when outbound interactsh/OAST traffic is not expected or not allowed.
- Use structured output (`-j -o <file>`) for automation.
Usage rules:
- Start with severity/tags/templates filters to keep runs explainable.
- Keep retries conservative (`-retries 1`) unless transport instability is proven.
- Do not use `-h`/`--help` for routine operation unless absolutely necessary.
Failure recovery:
- If performance degrades, lower `-c/-bs` before lowering `-rl`.
- If findings are unexpectedly empty, verify template selection (`-as` vs explicit `-t/-tags`).
- If scan duration grows, reduce target set and enforce stricter template/severity filters.
If uncertain, query web_search with:
`site:docs.projectdiscovery.io nuclei <flag> running`

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---
name: semgrep
description: Exact Semgrep CLI structure, metrics-off scanning, scoped ruleset selection, and automation-safe output patterns.
---
# Semgrep CLI Playbook
Official docs:
- https://semgrep.dev/docs/cli-reference
- https://semgrep.dev/docs/getting-started/cli
- https://semgrep.dev/docs/semgrep-code/semgrep-pro-engine-intro
Canonical syntax:
`semgrep scan [flags]`
High-signal flags:
- `--config <rule_or_ruleset>` ruleset, registry pack, local rule file, or directory
- `--metrics=off` disable telemetry and metrics reporting
- `--json` JSON output
- `--sarif` SARIF output
- `--output <file>` write findings to file
- `--severity <level>` filter by severity
- `--error` return non-zero exit when findings exist
- `--quiet` suppress progress noise
- `--jobs <n>` parallel workers
- `--timeout <seconds>` per-file timeout
- `--exclude <pattern>` exclude path pattern
- `--include <pattern>` include path pattern
- `--exclude-rule <rule_id>` suppress specific rule
- `--baseline-commit <sha>` only report findings introduced after baseline
- `--pro` enable Pro engine if available
- `--oss-only` force OSS engine only
Agent-safe baseline for automation:
`semgrep scan --config p/default --metrics=off --json --output semgrep.json --quiet --jobs 4 --timeout 20 /workspace`
Common patterns:
- Default security scan:
`semgrep scan --config p/default --metrics=off --json --output semgrep.json --quiet /workspace`
- High-severity focused pass:
`semgrep scan --config p/default --severity ERROR --metrics=off --json --output semgrep_high.json --quiet /workspace`
- OWASP-oriented scan:
`semgrep scan --config p/owasp-top-ten --metrics=off --sarif --output semgrep.sarif --quiet /workspace`
- Language- or framework-specific rules:
`semgrep scan --config p/python --config p/secrets --metrics=off --json --output semgrep_python.json --quiet /workspace`
- Scoped directory scan:
`semgrep scan --config p/default --metrics=off --json --output semgrep_api.json --quiet /workspace/services/api`
- Pro engine check or run:
`semgrep scan --config p/default --pro --metrics=off --json --output semgrep_pro.json --quiet /workspace`
Critical correctness rules:
- Always include `--metrics=off`; Semgrep sends telemetry by default.
- Always provide an explicit `--config`; do not rely on vague or implied defaults.
- Prefer `--json --output <file>` or `--sarif --output <file>` for machine-readable downstream processing.
- Keep the target path explicit; use an absolute or clearly scoped workspace path instead of `.` when possible.
- If Pro availability matters, check it explicitly with a bounded command before assuming cross-file analysis exists.
Usage rules:
- Start with `p/default` unless the task clearly calls for a narrower pack.
- Add focused packs such as `p/secrets`, `p/python`, or `p/javascript` only when they match the target stack.
- Use `--quiet` in automation to reduce noisy logs.
- Use `--jobs` and `--timeout` explicitly for reproducible runtime behavior.
- Do not use `-h`/`--help` for routine operation unless absolutely necessary.
Failure recovery:
- If scans are too slow, narrow the target path and reduce the active rulesets before changing engine settings.
- If scans time out, increase `--timeout` modestly or lower `--jobs`.
- If output is too broad, scope `--config`, add `--severity`, or exclude known irrelevant paths.
- If Pro mode fails, rerun with `--oss-only` or without `--pro` and note the loss of cross-file coverage.
If uncertain, query web_search with:
`site:semgrep.dev semgrep <flag> cli`

View File

@@ -0,0 +1,67 @@
---
name: sqlmap
description: sqlmap target syntax, non-interactive execution, and common validation/enumeration workflows.
---
# sqlmap CLI Playbook
Official docs:
- https://github.com/sqlmapproject/sqlmap/wiki/usage
- https://sqlmap.org
Canonical syntax:
`sqlmap -u "<target_url_with_params>" [options]`
High-signal flags:
- `-u, --url <url>` target URL
- `-r <request_file>` raw HTTP request input
- `-p <param>` test specific parameter(s)
- `--batch` non-interactive mode
- `--level <1-5>` test depth
- `--risk <1-3>` payload risk profile
- `--threads <n>` concurrency
- `--technique <letters>` technique selection
- `--forms` parse and test forms from target page
- `--cookie <cookie>` and `--headers <headers>` authenticated context
- `--timeout <seconds>` and `--retries <n>` transport stability
- `--tamper <scripts>` WAF/input-filter evasion
- `--random-agent` randomize user-agent
- `--ignore-proxy` bypass configured proxy
- `--dbs`, `-D <db> --tables`, `-D <db> -T <table> --columns`, `-D <db> -T <table> -C <cols> --dump`
- `--flush-session` clear cached scan state
Agent-safe baseline for automation:
`sqlmap -u "https://target.tld/item?id=1" -p id --batch --level 2 --risk 1 --threads 5 --timeout 10 --retries 1 --random-agent`
Common patterns:
- Baseline injection check:
`sqlmap -u "https://target.tld/item?id=1" -p id --batch --level 2 --risk 1 --threads 5`
- POST parameter testing:
`sqlmap -u "https://target.tld/login" --data "user=admin&pass=test" -p pass --batch --level 2 --risk 1`
- Form-driven testing:
`sqlmap -u "https://target.tld/login" --forms --batch --level 2 --risk 1 --random-agent`
- Enumerate DBs:
`sqlmap -u "https://target.tld/item?id=1" -p id --batch --dbs`
- Enumerate tables in DB:
`sqlmap -u "https://target.tld/item?id=1" -p id --batch -D appdb --tables`
- Dump selected columns:
`sqlmap -u "https://target.tld/item?id=1" -p id --batch -D appdb -T users -C id,email,role --dump`
Critical correctness rules:
- Always include `--batch` in automation to avoid interactive prompts.
- Keep target parameter explicit with `-p` when possible.
- Use `--flush-session` when retesting after request/profile changes.
- Start conservative (`--level 1-2`, `--risk 1`) and escalate only when needed.
Usage rules:
- Keep authenticated context (`--cookie`/`--headers`) aligned with manual validation state.
- Prefer narrow extraction (`-D/-T/-C`) over broad dump-first behavior.
- Do not use `-h`/`--help` during normal execution unless absolutely necessary.
Failure recovery:
- If results conflict with manual testing, rerun with `--flush-session`.
- If blocked by filtering/WAF, reduce `--threads` and test targeted `--tamper` chains.
- If initial detection misses likely injection, increment `--level`/`--risk` gradually.
If uncertain, query web_search with:
`site:github.com/sqlmapproject/sqlmap/wiki/usage sqlmap <flag>`

View File

@@ -0,0 +1,66 @@
---
name: subfinder
description: Subfinder passive subdomain enumeration syntax, source controls, and pipeline-ready output patterns.
---
# Subfinder CLI Playbook
Official docs:
- https://docs.projectdiscovery.io/opensource/subfinder/usage
- https://docs.projectdiscovery.io/opensource/subfinder/running
- https://github.com/projectdiscovery/subfinder
Canonical syntax:
`subfinder [flags]`
High-signal flags:
- `-d <domain>` single domain
- `-dL <file>` domain list
- `-all` include all sources
- `-recursive` use recursive-capable sources
- `-s <sources>` include specific sources
- `-es <sources>` exclude specific sources
- `-rl <n>` global rate limit
- `-rls <source=n/s,...>` per-source rate limits
- `-proxy <http://host:port>` proxy outbound source requests
- `-silent` compact output
- `-o <file>` output file
- `-oJ, -json` JSONL output
- `-cs, -collect-sources` include source metadata (`-oJ` output)
- `-nW, -active` show only active subdomains
- `-timeout <seconds>` request timeout
- `-max-time <minutes>` overall enumeration cap
Agent-safe baseline for automation:
`subfinder -d example.com -all -recursive -rl 20 -timeout 30 -silent -oJ -o subfinder.jsonl`
Common patterns:
- Standard passive enum:
`subfinder -d example.com -silent -o subs.txt`
- Broad-source passive enum:
`subfinder -d example.com -all -recursive -silent -o subs_all.txt`
- Multi-domain run:
`subfinder -dL domains.txt -all -recursive -rl 20 -silent -o subfinder_out.txt`
- Source-attributed JSONL output:
`subfinder -d example.com -all -oJ -cs -o subfinder_sources.jsonl`
- Passive enum via explicit proxy:
`subfinder -d example.com -all -recursive -proxy http://127.0.0.1:48080 -silent -oJ -o subfinder_proxy.jsonl`
Critical correctness rules:
- `-cs` is useful only with JSON output (`-oJ`).
- Many sources require API keys in provider config; low results can be config-related, not target-related.
- `-nW` performs active resolution/filtering and can drop passive-only hits.
- Keep passive enum first, then validate with `httpx`.
Usage rules:
- Keep output files explicit when chaining to `httpx`/`nuclei`.
- Use `-rl/-rls` when providers throttle aggressively.
- Do not use `-h`/`--help` for routine tasks unless absolutely necessary.
Failure recovery:
- If results are unexpectedly low, rerun with `-all` and verify provider config/API keys.
- If provider errors appear, lower `-rl` and apply `-rls` per source.
- If runs take too long, lower scope or split domain batches.
If uncertain, query web_search with:
`site:docs.projectdiscovery.io subfinder <flag> usage`

23
strix/telemetry/flags.py Normal file
View File

@@ -0,0 +1,23 @@
from strix.config import Config
_DISABLED_VALUES = {"0", "false", "no", "off"}
def _is_enabled(raw_value: str | None, default: str = "1") -> bool:
value = (raw_value if raw_value is not None else default).strip().lower()
return value not in _DISABLED_VALUES
def is_otel_enabled() -> bool:
explicit = Config.get("strix_otel_telemetry")
if explicit is not None:
return _is_enabled(explicit)
return _is_enabled(Config.get("strix_telemetry"), default="1")
def is_posthog_enabled() -> bool:
explicit = Config.get("strix_posthog_telemetry")
if explicit is not None:
return _is_enabled(explicit)
return _is_enabled(Config.get("strix_telemetry"), default="1")

View File

@@ -6,7 +6,7 @@ from pathlib import Path
from typing import TYPE_CHECKING, Any
from uuid import uuid4
from strix.config import Config
from strix.telemetry.flags import is_posthog_enabled
if TYPE_CHECKING:
@@ -19,7 +19,7 @@ _SESSION_ID = uuid4().hex[:16]
def _is_enabled() -> bool:
return (Config.get("strix_telemetry") or "1").lower() not in ("0", "false", "no", "off")
return is_posthog_enabled()
def _is_first_run() -> bool:

View File

@@ -1,20 +1,40 @@
import json
import logging
import threading
from datetime import UTC, datetime
from pathlib import Path
from typing import TYPE_CHECKING, Any, Optional
from typing import Any, Callable, Optional
from uuid import uuid4
from opentelemetry import trace
from opentelemetry.trace import SpanContext, SpanKind
from strix.config import Config
from strix.telemetry import posthog
from strix.telemetry.flags import is_otel_enabled
from strix.telemetry.utils import (
TelemetrySanitizer,
append_jsonl_record,
bootstrap_otel,
format_span_id,
format_trace_id,
get_events_write_lock,
)
if TYPE_CHECKING:
from collections.abc import Callable
try:
from traceloop.sdk import Traceloop
except ImportError: # pragma: no cover - exercised when dependency is absent
Traceloop = None # type: ignore[assignment,unused-ignore]
logger = logging.getLogger(__name__)
_global_tracer: Optional["Tracer"] = None
_OTEL_BOOTSTRAP_LOCK = threading.Lock()
_OTEL_BOOTSTRAPPED = False
_OTEL_REMOTE_ENABLED = False
def get_global_tracer() -> Optional["Tracer"]:
return _global_tracer
@@ -52,16 +72,225 @@ class Tracer:
"status": "running",
}
self._run_dir: Path | None = None
self._events_file_path: Path | None = None
self._next_execution_id = 1
self._next_message_id = 1
self._saved_vuln_ids: set[str] = set()
self._run_completed_emitted = False
self._telemetry_enabled = is_otel_enabled()
self._sanitizer = TelemetrySanitizer()
self._otel_tracer: Any = None
self._remote_export_enabled = False
self.caido_url: str | None = None
self.vulnerability_found_callback: Callable[[dict[str, Any]], None] | None = None
self._setup_telemetry()
self._emit_run_started_event()
@property
def events_file_path(self) -> Path:
if self._events_file_path is None:
self._events_file_path = self.get_run_dir() / "events.jsonl"
return self._events_file_path
def _active_events_file_path(self) -> Path:
active = get_global_tracer()
if active and active._events_file_path is not None:
return active._events_file_path
return self.events_file_path
def _get_events_write_lock(self, output_path: Path | None = None) -> threading.Lock:
path = output_path or self.events_file_path
return get_events_write_lock(path)
def _active_run_metadata(self) -> dict[str, Any]:
active = get_global_tracer()
if active:
return active.run_metadata
return self.run_metadata
def _setup_telemetry(self) -> None:
global _OTEL_BOOTSTRAPPED, _OTEL_REMOTE_ENABLED
if not self._telemetry_enabled:
self._otel_tracer = None
self._remote_export_enabled = False
return
run_dir = self.get_run_dir()
self._events_file_path = run_dir / "events.jsonl"
base_url = (Config.get("traceloop_base_url") or "").strip()
api_key = (Config.get("traceloop_api_key") or "").strip()
headers_raw = Config.get("traceloop_headers") or ""
(
self._otel_tracer,
self._remote_export_enabled,
_OTEL_BOOTSTRAPPED,
_OTEL_REMOTE_ENABLED,
) = bootstrap_otel(
bootstrapped=_OTEL_BOOTSTRAPPED,
remote_enabled_state=_OTEL_REMOTE_ENABLED,
bootstrap_lock=_OTEL_BOOTSTRAP_LOCK,
traceloop=Traceloop,
base_url=base_url,
api_key=api_key,
headers_raw=headers_raw,
output_path_getter=self._active_events_file_path,
run_metadata_getter=self._active_run_metadata,
sanitizer=self._sanitize_data,
write_lock_getter=self._get_events_write_lock,
tracer_name="strix.telemetry.tracer",
)
def _set_association_properties(self, properties: dict[str, Any]) -> None:
if Traceloop is None:
return
sanitized = self._sanitize_data(properties)
try:
Traceloop.set_association_properties(sanitized)
except Exception: # noqa: BLE001
logger.debug("Failed to set Traceloop association properties")
def _sanitize_data(self, data: Any, key_hint: str | None = None) -> Any:
return self._sanitizer.sanitize(data, key_hint=key_hint)
def _append_event_record(self, record: dict[str, Any]) -> None:
try:
append_jsonl_record(self.events_file_path, record)
except OSError:
logger.exception("Failed to append JSONL event record")
def _enrich_actor(self, actor: dict[str, Any] | None) -> dict[str, Any] | None:
if not actor:
return None
enriched = dict(actor)
if "agent_name" in enriched:
return enriched
agent_id = enriched.get("agent_id")
if not isinstance(agent_id, str):
return enriched
agent_data = self.agents.get(agent_id, {})
agent_name = agent_data.get("name")
if isinstance(agent_name, str) and agent_name:
enriched["agent_name"] = agent_name
return enriched
def _emit_event(
self,
event_type: str,
actor: dict[str, Any] | None = None,
payload: Any | None = None,
status: str | None = None,
error: Any | None = None,
source: str = "strix.tracer",
include_run_metadata: bool = False,
) -> None:
if not self._telemetry_enabled:
return
enriched_actor = self._enrich_actor(actor)
sanitized_actor = self._sanitize_data(enriched_actor) if enriched_actor else None
sanitized_payload = self._sanitize_data(payload) if payload is not None else None
sanitized_error = self._sanitize_data(error) if error is not None else None
trace_id: str | None = None
span_id: str | None = None
parent_span_id: str | None = None
current_context = trace.get_current_span().get_span_context()
if isinstance(current_context, SpanContext) and current_context.is_valid:
parent_span_id = format_span_id(current_context.span_id)
if self._otel_tracer is not None:
try:
with self._otel_tracer.start_as_current_span(
f"strix.{event_type}",
kind=SpanKind.INTERNAL,
) as span:
span_context = span.get_span_context()
trace_id = format_trace_id(span_context.trace_id)
span_id = format_span_id(span_context.span_id)
span.set_attribute("strix.event_type", event_type)
span.set_attribute("strix.source", source)
span.set_attribute("strix.run_id", self.run_id)
span.set_attribute("strix.run_name", self.run_name or "")
if status:
span.set_attribute("strix.status", status)
if sanitized_actor is not None:
span.set_attribute(
"strix.actor",
json.dumps(sanitized_actor, ensure_ascii=False),
)
if sanitized_payload is not None:
span.set_attribute(
"strix.payload",
json.dumps(sanitized_payload, ensure_ascii=False),
)
if sanitized_error is not None:
span.set_attribute(
"strix.error",
json.dumps(sanitized_error, ensure_ascii=False),
)
except Exception: # noqa: BLE001
logger.debug("Failed to create OTEL span for event type '%s'", event_type)
if trace_id is None:
trace_id = format_trace_id(uuid4().int & ((1 << 128) - 1)) or uuid4().hex
if span_id is None:
span_id = format_span_id(uuid4().int & ((1 << 64) - 1)) or uuid4().hex[:16]
record = {
"timestamp": datetime.now(UTC).isoformat(),
"event_type": event_type,
"run_id": self.run_id,
"trace_id": trace_id,
"span_id": span_id,
"parent_span_id": parent_span_id,
"actor": sanitized_actor,
"payload": sanitized_payload,
"status": status,
"error": sanitized_error,
"source": source,
}
if include_run_metadata:
record["run_metadata"] = self._sanitize_data(self.run_metadata)
self._append_event_record(record)
def set_run_name(self, run_name: str) -> None:
self.run_name = run_name
self.run_id = run_name
self.run_metadata["run_name"] = run_name
self.run_metadata["run_id"] = run_name
self._run_dir = None
self._events_file_path = None
self._run_completed_emitted = False
self._set_association_properties({"run_id": self.run_id, "run_name": self.run_name or ""})
self._emit_run_started_event()
def _emit_run_started_event(self) -> None:
if not self._telemetry_enabled:
return
self._emit_event(
"run.started",
payload={
"run_name": self.run_name,
"start_time": self.start_time,
"local_jsonl_path": str(self.events_file_path),
"remote_export_enabled": self._remote_export_enabled,
},
status="running",
include_run_metadata=True,
)
def get_run_dir(self) -> Path:
if self._run_dir is None:
@@ -134,6 +363,12 @@ class Tracer:
self.vulnerability_reports.append(report)
logger.info(f"Added vulnerability report: {report_id} - {title}")
posthog.finding(severity)
self._emit_event(
"finding.created",
payload={"report": report},
status=report["severity"],
source="strix.findings",
)
if self.vulnerability_found_callback:
self.vulnerability_found_callback(report)
@@ -178,11 +413,24 @@ class Tracer:
"""
logger.info("Updated scan final fields")
self._emit_event(
"finding.reviewed",
payload={
"scan_completed": True,
"vulnerability_count": len(self.vulnerability_reports),
},
status="completed",
source="strix.findings",
)
self.save_run_data(mark_complete=True)
posthog.end(self, exit_reason="finished_by_tool")
def log_agent_creation(
self, agent_id: str, name: str, task: str, parent_id: str | None = None
self,
agent_id: str,
name: str,
task: str,
parent_id: str | None = None,
) -> None:
agent_data: dict[str, Any] = {
"id": agent_id,
@@ -196,6 +444,13 @@ class Tracer:
}
self.agents[agent_id] = agent_data
self._emit_event(
"agent.created",
actor={"agent_id": agent_id, "agent_name": name},
payload={"task": task, "parent_id": parent_id},
status="running",
source="strix.agents",
)
def log_chat_message(
self,
@@ -217,9 +472,21 @@ class Tracer:
}
self.chat_messages.append(message_data)
self._emit_event(
"chat.message",
actor={"agent_id": agent_id, "role": role},
payload={"message_id": message_id, "content": content, "metadata": metadata or {}},
status="logged",
source="strix.chat",
)
return message_id
def log_tool_execution_start(self, agent_id: str, tool_name: str, args: dict[str, Any]) -> int:
def log_tool_execution_start(
self,
agent_id: str,
tool_name: str,
args: dict[str, Any],
) -> int:
execution_id = self._next_execution_id
self._next_execution_id += 1
@@ -241,18 +508,67 @@ class Tracer:
if agent_id in self.agents:
self.agents[agent_id]["tool_executions"].append(execution_id)
self._emit_event(
"tool.execution.started",
actor={
"agent_id": agent_id,
"tool_name": tool_name,
"execution_id": execution_id,
},
payload={"args": args},
status="running",
source="strix.tools",
)
return execution_id
def update_tool_execution(
self, execution_id: int, status: str, result: Any | None = None
self,
execution_id: int,
status: str,
result: Any | None = None,
) -> None:
if execution_id in self.tool_executions:
self.tool_executions[execution_id]["status"] = status
self.tool_executions[execution_id]["result"] = result
self.tool_executions[execution_id]["completed_at"] = datetime.now(UTC).isoformat()
if execution_id not in self.tool_executions:
return
tool_data = self.tool_executions[execution_id]
tool_data["status"] = status
tool_data["result"] = result
tool_data["completed_at"] = datetime.now(UTC).isoformat()
tool_name = str(tool_data.get("tool_name", "unknown"))
agent_id = str(tool_data.get("agent_id", "unknown"))
error_payload = result if status in {"error", "failed"} else None
self._emit_event(
"tool.execution.updated",
actor={
"agent_id": agent_id,
"tool_name": tool_name,
"execution_id": execution_id,
},
payload={"result": result},
status=status,
error=error_payload,
source="strix.tools",
)
if tool_name == "create_vulnerability_report":
finding_status = "reviewed" if status == "completed" else "rejected"
self._emit_event(
"finding.reviewed",
actor={"agent_id": agent_id, "tool_name": tool_name},
payload={"execution_id": execution_id, "result": result},
status=finding_status,
error=error_payload,
source="strix.findings",
)
def update_agent_status(
self, agent_id: str, status: str, error_message: str | None = None
self,
agent_id: str,
status: str,
error_message: str | None = None,
) -> None:
if agent_id in self.agents:
self.agents[agent_id]["status"] = status
@@ -260,6 +576,15 @@ class Tracer:
if error_message:
self.agents[agent_id]["error_message"] = error_message
self._emit_event(
"agent.status.updated",
actor={"agent_id": agent_id},
payload={"error_message": error_message},
status=status,
error=error_message,
source="strix.agents",
)
def set_scan_config(self, config: dict[str, Any]) -> None:
self.scan_config = config
self.run_metadata.update(
@@ -269,13 +594,29 @@ class Tracer:
"max_iterations": config.get("max_iterations", 200),
}
)
self.get_run_dir()
self._set_association_properties(
{
"run_id": self.run_id,
"run_name": self.run_name or "",
"targets": config.get("targets", []),
"max_iterations": config.get("max_iterations", 200),
}
)
self._emit_event(
"run.configured",
payload={"scan_config": config},
status="configured",
source="strix.run",
)
def save_run_data(self, mark_complete: bool = False) -> None: # noqa: PLR0912, PLR0915
def save_run_data(self, mark_complete: bool = False) -> None:
try:
run_dir = self.get_run_dir()
if mark_complete:
self.end_time = datetime.now(UTC).isoformat()
if self.end_time is None:
self.end_time = datetime.now(UTC).isoformat()
self.run_metadata["end_time"] = self.end_time
self.run_metadata["status"] = "completed"
if self.final_scan_result:
penetration_test_report_file = run_dir / "penetration_test_report.md"
@@ -286,7 +627,8 @@ class Tracer:
)
f.write(f"{self.final_scan_result}\n")
logger.info(
f"Saved final penetration test report to: {penetration_test_report_file}"
"Saved final penetration test report to: %s",
penetration_test_report_file,
)
if self.vulnerability_reports:
@@ -302,7 +644,10 @@ class Tracer:
severity_order = {"critical": 0, "high": 1, "medium": 2, "low": 3, "info": 4}
sorted_reports = sorted(
self.vulnerability_reports,
key=lambda x: (severity_order.get(x["severity"], 5), x["timestamp"]),
key=lambda report: (
severity_order.get(report["severity"], 5),
report["timestamp"],
),
)
for report in new_reports:
@@ -329,8 +674,8 @@ class Tracer:
f.write(f"**{label}:** {value}\n")
f.write("\n## Description\n\n")
desc = report.get("description") or "No description provided."
f.write(f"{desc}\n\n")
description = report.get("description") or "No description provided."
f.write(f"{description}\n\n")
if report.get("impact"):
f.write("## Impact\n\n")
@@ -404,11 +749,25 @@ class Tracer:
if new_reports:
logger.info(
f"Saved {len(new_reports)} new vulnerability report(s) to: {vuln_dir}"
"Saved %d new vulnerability report(s) to: %s",
len(new_reports),
vuln_dir,
)
logger.info(f"Updated vulnerability index: {vuln_csv_file}")
logger.info("Updated vulnerability index: %s", vuln_csv_file)
logger.info(f"📊 Essential scan data saved to: {run_dir}")
logger.info("📊 Essential scan data saved to: %s", run_dir)
if mark_complete and not self._run_completed_emitted:
self._emit_event(
"run.completed",
payload={
"duration_seconds": self._calculate_duration(),
"vulnerability_count": len(self.vulnerability_reports),
},
status="completed",
source="strix.run",
include_run_metadata=True,
)
self._run_completed_emitted = True
except (OSError, RuntimeError):
logger.exception("Failed to save scan data")

413
strix/telemetry/utils.py Normal file
View File

@@ -0,0 +1,413 @@
import json
import logging
import re
import threading
from collections.abc import Callable, Sequence
from datetime import UTC, datetime
from pathlib import Path
from typing import Any
from opentelemetry import trace
from opentelemetry.sdk.trace import ReadableSpan, TracerProvider
from opentelemetry.sdk.trace.export import (
BatchSpanProcessor,
SimpleSpanProcessor,
SpanExporter,
SpanExportResult,
)
from scrubadub import Scrubber
from scrubadub.detectors import RegexDetector
from scrubadub.filth import Filth
logger = logging.getLogger(__name__)
_REDACTED = "[REDACTED]"
_SCREENSHOT_OMITTED = "[SCREENSHOT_OMITTED]"
_SCREENSHOT_KEY_PATTERN = re.compile(r"screenshot", re.IGNORECASE)
_SENSITIVE_KEY_PATTERN = re.compile(
r"(api[_-]?key|token|secret|password|authorization|cookie|session|credential|private[_-]?key)",
re.IGNORECASE,
)
_SENSITIVE_TOKEN_PATTERN = re.compile(
r"(?i)\b("
r"bearer\s+[a-z0-9._-]+|"
r"sk-[a-z0-9_-]{8,}|"
r"gh[pousr]_[a-z0-9_-]{12,}|"
r"xox[baprs]-[a-z0-9-]{12,}"
r")\b"
)
_SCRUBADUB_PLACEHOLDER_PATTERN = re.compile(r"\{\{[^}]+\}\}")
_EVENTS_FILE_LOCKS_LOCK = threading.Lock()
_EVENTS_FILE_LOCKS: dict[str, threading.Lock] = {}
_NOISY_OTEL_CONTENT_PREFIXES = (
"gen_ai.prompt.",
"gen_ai.completion.",
"llm.input_messages.",
"llm.output_messages.",
)
_NOISY_OTEL_EXACT_KEYS = {
"llm.input",
"llm.output",
"llm.prompt",
"llm.completion",
}
class _SecretFilth(Filth): # type: ignore[misc]
type = "secret"
class _SecretTokenDetector(RegexDetector): # type: ignore[misc]
name = "strix_secret_token_detector"
filth_cls = _SecretFilth
regex = _SENSITIVE_TOKEN_PATTERN
class TelemetrySanitizer:
def __init__(self) -> None:
self._scrubber = Scrubber(detector_list=[_SecretTokenDetector])
def sanitize(self, data: Any, key_hint: str | None = None) -> Any: # noqa: PLR0911
if data is None:
return None
if isinstance(data, dict):
sanitized: dict[str, Any] = {}
for key, value in data.items():
key_str = str(key)
if _SCREENSHOT_KEY_PATTERN.search(key_str):
sanitized[key_str] = _SCREENSHOT_OMITTED
elif _SENSITIVE_KEY_PATTERN.search(key_str):
sanitized[key_str] = _REDACTED
else:
sanitized[key_str] = self.sanitize(value, key_hint=key_str)
return sanitized
if isinstance(data, list):
return [self.sanitize(item, key_hint=key_hint) for item in data]
if isinstance(data, tuple):
return [self.sanitize(item, key_hint=key_hint) for item in data]
if isinstance(data, str):
if key_hint and _SENSITIVE_KEY_PATTERN.search(key_hint):
return _REDACTED
cleaned = self._scrubber.clean(data)
return _SCRUBADUB_PLACEHOLDER_PATTERN.sub(_REDACTED, cleaned)
if isinstance(data, int | float | bool):
return data
return str(data)
def format_trace_id(trace_id: int | None) -> str | None:
if trace_id is None or trace_id == 0:
return None
return f"{trace_id:032x}"
def format_span_id(span_id: int | None) -> str | None:
if span_id is None or span_id == 0:
return None
return f"{span_id:016x}"
def iso_from_unix_ns(unix_ns: int | None) -> str | None:
if unix_ns is None:
return None
try:
return datetime.fromtimestamp(unix_ns / 1_000_000_000, tz=UTC).isoformat()
except (OSError, OverflowError, ValueError):
return None
def get_events_write_lock(output_path: Path) -> threading.Lock:
path_key = str(output_path.resolve(strict=False))
with _EVENTS_FILE_LOCKS_LOCK:
lock = _EVENTS_FILE_LOCKS.get(path_key)
if lock is None:
lock = threading.Lock()
_EVENTS_FILE_LOCKS[path_key] = lock
return lock
def reset_events_write_locks() -> None:
with _EVENTS_FILE_LOCKS_LOCK:
_EVENTS_FILE_LOCKS.clear()
def append_jsonl_record(output_path: Path, record: dict[str, Any]) -> None:
output_path.parent.mkdir(parents=True, exist_ok=True)
with get_events_write_lock(output_path), output_path.open("a", encoding="utf-8") as f:
f.write(json.dumps(record, ensure_ascii=False) + "\n")
def default_resource_attributes() -> dict[str, str]:
return {
"service.name": "strix-agent",
"service.namespace": "strix",
}
def parse_traceloop_headers(raw_headers: str) -> dict[str, str]:
headers = raw_headers.strip()
if not headers:
return {}
if headers.startswith("{"):
try:
parsed = json.loads(headers)
except json.JSONDecodeError:
logger.warning("Invalid TRACELOOP_HEADERS JSON, ignoring custom headers")
return {}
if isinstance(parsed, dict):
return {str(key): str(value) for key, value in parsed.items() if value is not None}
logger.warning("TRACELOOP_HEADERS JSON must be an object, ignoring custom headers")
return {}
result: dict[str, str] = {}
for part in headers.split(","):
key, sep, value = part.partition("=")
if not sep:
continue
key = key.strip()
value = value.strip()
if key and value:
result[key] = value
return result
def prune_otel_span_attributes(attributes: dict[str, Any]) -> dict[str, Any]:
"""Drop high-volume LLM payload attributes to keep JSONL event files compact."""
filtered: dict[str, Any] = {}
filtered_count = 0
for key, value in attributes.items():
key_str = str(key)
if key_str in _NOISY_OTEL_EXACT_KEYS:
filtered_count += 1
continue
if key_str.endswith(".content") and key_str.startswith(_NOISY_OTEL_CONTENT_PREFIXES):
filtered_count += 1
continue
filtered[key_str] = value
if filtered_count:
filtered["strix.filtered_attributes_count"] = filtered_count
return filtered
class JsonlSpanExporter(SpanExporter): # type: ignore[misc]
"""Append OTEL spans to JSONL for local run artifacts."""
def __init__(
self,
output_path_getter: Callable[[], Path],
run_metadata_getter: Callable[[], dict[str, Any]],
sanitizer: Callable[[Any], Any],
write_lock_getter: Callable[[Path], threading.Lock],
):
self._output_path_getter = output_path_getter
self._run_metadata_getter = run_metadata_getter
self._sanitize = sanitizer
self._write_lock_getter = write_lock_getter
def export(self, spans: Sequence[ReadableSpan]) -> SpanExportResult:
records: list[dict[str, Any]] = []
for span in spans:
attributes = prune_otel_span_attributes(dict(span.attributes or {}))
if "strix.event_type" in attributes:
# Tracer events are written directly in Tracer._emit_event.
continue
records.append(self._span_to_record(span, attributes))
if not records:
return SpanExportResult.SUCCESS
try:
output_path = self._output_path_getter()
output_path.parent.mkdir(parents=True, exist_ok=True)
with self._write_lock_getter(output_path), output_path.open("a", encoding="utf-8") as f:
for record in records:
f.write(json.dumps(record, ensure_ascii=False) + "\n")
except OSError:
logger.exception("Failed to write OTEL span records to JSONL")
return SpanExportResult.FAILURE
return SpanExportResult.SUCCESS
def shutdown(self) -> None:
return None
def force_flush(self, timeout_millis: int = 30_000) -> bool: # noqa: ARG002
return True
def _span_to_record(
self,
span: ReadableSpan,
attributes: dict[str, Any],
) -> dict[str, Any]:
span_context = span.get_span_context()
parent_context = span.parent
status = None
if span.status and span.status.status_code:
status = span.status.status_code.name.lower()
event_type = str(attributes.get("gen_ai.operation.name", span.name))
run_metadata = self._run_metadata_getter()
run_id_attr = (
attributes.get("strix.run_id")
or attributes.get("strix_run_id")
or run_metadata.get("run_id")
or span.resource.attributes.get("strix.run_id")
)
record: dict[str, Any] = {
"timestamp": iso_from_unix_ns(span.end_time) or datetime.now(UTC).isoformat(),
"event_type": event_type,
"run_id": str(run_id_attr or run_metadata.get("run_id") or ""),
"trace_id": format_trace_id(span_context.trace_id),
"span_id": format_span_id(span_context.span_id),
"parent_span_id": format_span_id(parent_context.span_id if parent_context else None),
"actor": None,
"payload": None,
"status": status,
"error": None,
"source": "otel.span",
"span_name": span.name,
"span_kind": span.kind.name.lower(),
"attributes": self._sanitize(attributes),
}
if span.events:
record["otel_events"] = self._sanitize(
[
{
"name": event.name,
"timestamp": iso_from_unix_ns(event.timestamp),
"attributes": dict(event.attributes or {}),
}
for event in span.events
]
)
return record
def bootstrap_otel(
*,
bootstrapped: bool,
remote_enabled_state: bool,
bootstrap_lock: threading.Lock,
traceloop: Any,
base_url: str,
api_key: str,
headers_raw: str,
output_path_getter: Callable[[], Path],
run_metadata_getter: Callable[[], dict[str, Any]],
sanitizer: Callable[[Any], Any],
write_lock_getter: Callable[[Path], threading.Lock],
tracer_name: str = "strix.telemetry.tracer",
) -> tuple[Any, bool, bool, bool]:
with bootstrap_lock:
if bootstrapped:
return (
trace.get_tracer(tracer_name),
remote_enabled_state,
bootstrapped,
remote_enabled_state,
)
local_exporter = JsonlSpanExporter(
output_path_getter=output_path_getter,
run_metadata_getter=run_metadata_getter,
sanitizer=sanitizer,
write_lock_getter=write_lock_getter,
)
local_processor = SimpleSpanProcessor(local_exporter)
headers = parse_traceloop_headers(headers_raw)
remote_enabled = bool(base_url and api_key)
otlp_headers = headers
if remote_enabled:
otlp_headers = {"Authorization": f"Bearer {api_key}"}
otlp_headers.update(headers)
otel_init_ok = False
if traceloop:
try:
from traceloop.sdk.instruments import Instruments
init_kwargs: dict[str, Any] = {
"app_name": "strix-agent",
"processor": local_processor,
"telemetry_enabled": False,
"resource_attributes": default_resource_attributes(),
"block_instruments": {
Instruments.URLLIB3,
Instruments.REQUESTS,
},
}
if remote_enabled:
init_kwargs.update(
{
"api_endpoint": base_url,
"api_key": api_key,
"headers": headers,
}
)
import io
import sys
_stdout = sys.stdout
sys.stdout = io.StringIO()
try:
traceloop.init(**init_kwargs)
finally:
sys.stdout = _stdout
otel_init_ok = True
except Exception:
logger.exception("Failed to initialize Traceloop/OpenLLMetry")
remote_enabled = False
if not otel_init_ok:
from opentelemetry.sdk.resources import Resource
provider = TracerProvider(resource=Resource.create(default_resource_attributes()))
provider.add_span_processor(local_processor)
if remote_enabled:
try:
from opentelemetry.exporter.otlp.proto.http.trace_exporter import (
OTLPSpanExporter,
)
endpoint = base_url.rstrip("/") + "/v1/traces"
provider.add_span_processor(
BatchSpanProcessor(
OTLPSpanExporter(endpoint=endpoint, headers=otlp_headers)
)
)
except Exception:
logger.exception("Failed to configure OTLP HTTP exporter")
remote_enabled = False
try:
trace.set_tracer_provider(provider)
otel_init_ok = True
except Exception:
logger.exception("Failed to set OpenTelemetry tracer provider")
remote_enabled = False
otel_tracer = trace.get_tracer(tracer_name)
if otel_init_ok:
return otel_tracer, remote_enabled, True, remote_enabled
return otel_tracer, remote_enabled, bootstrapped, remote_enabled_state

View File

@@ -1,7 +1,5 @@
import os
from strix.config import Config
from .agents_graph import * # noqa: F403
from .browser import * # noqa: F403
from .executor import (
execute_tool,
execute_tool_invocation,
@@ -11,6 +9,12 @@ from .executor import (
remove_screenshot_from_result,
validate_tool_availability,
)
from .file_edit import * # noqa: F403
from .finish import * # noqa: F403
from .load_skill import * # noqa: F403
from .notes import * # noqa: F403
from .proxy import * # noqa: F403
from .python import * # noqa: F403
from .registry import (
ImplementedInClientSideOnlyError,
get_tool_by_name,
@@ -20,39 +24,13 @@ from .registry import (
register_tool,
tools,
)
from .reporting import * # noqa: F403
from .terminal import * # noqa: F403
from .thinking import * # noqa: F403
from .todo import * # noqa: F403
from .web_search import * # noqa: F403
SANDBOX_MODE = os.getenv("STRIX_SANDBOX_MODE", "false").lower() == "true"
HAS_PERPLEXITY_API = bool(Config.get("perplexity_api_key"))
DISABLE_BROWSER = (Config.get("strix_disable_browser") or "false").lower() == "true"
if not SANDBOX_MODE:
from .agents_graph import * # noqa: F403
if not DISABLE_BROWSER:
from .browser import * # noqa: F403
from .file_edit import * # noqa: F403
from .finish import * # noqa: F403
from .notes import * # noqa: F403
from .proxy import * # noqa: F403
from .python import * # noqa: F403
from .reporting import * # noqa: F403
from .terminal import * # noqa: F403
from .thinking import * # noqa: F403
from .todo import * # noqa: F403
if HAS_PERPLEXITY_API:
from .web_search import * # noqa: F403
else:
if not DISABLE_BROWSER:
from .browser import * # noqa: F403
from .file_edit import * # noqa: F403
from .proxy import * # noqa: F403
from .python import * # noqa: F403
from .terminal import * # noqa: F403
__all__ = [
"ImplementedInClientSideOnlyError",
"execute_tool",

View File

@@ -195,58 +195,52 @@ def create_agent(
try:
parent_id = agent_state.agent_id
skill_list = []
if skills:
skill_list = [s.strip() for s in skills.split(",") if s.strip()]
from strix.skills import parse_skill_list, validate_requested_skills
if len(skill_list) > 5:
skill_list = parse_skill_list(skills)
validation_error = validate_requested_skills(skill_list)
if validation_error:
return {
"success": False,
"error": (
"Cannot specify more than 5 skills for an agent (use comma-separated format)"
),
"error": validation_error,
"agent_id": None,
}
if skill_list:
from strix.skills import get_all_skill_names, validate_skill_names
validation = validate_skill_names(skill_list)
if validation["invalid"]:
available_skills = list(get_all_skill_names())
return {
"success": False,
"error": (
f"Invalid skills: {validation['invalid']}. "
f"Available skills: {', '.join(available_skills)}"
),
"agent_id": None,
}
from strix.agents import StrixAgent
from strix.agents.state import AgentState
from strix.llm.config import LLMConfig
state = AgentState(task=task, agent_name=name, parent_id=parent_id, max_iterations=300)
parent_agent = _agent_instances.get(parent_id)
timeout = None
scan_mode = "deep"
interactive = False
if parent_agent and hasattr(parent_agent, "llm_config"):
if hasattr(parent_agent.llm_config, "timeout"):
timeout = parent_agent.llm_config.timeout
if hasattr(parent_agent.llm_config, "scan_mode"):
scan_mode = parent_agent.llm_config.scan_mode
interactive = getattr(parent_agent.llm_config, "interactive", False)
llm_config = LLMConfig(skills=skill_list, timeout=timeout, scan_mode=scan_mode)
state = AgentState(
task=task,
agent_name=name,
parent_id=parent_id,
max_iterations=300,
waiting_timeout=300 if interactive else 600,
)
llm_config = LLMConfig(
skills=skill_list,
timeout=timeout,
scan_mode=scan_mode,
interactive=interactive,
)
agent_config = {
"llm_config": llm_config,
"state": state,
}
if parent_agent and hasattr(parent_agent, "non_interactive"):
agent_config["non_interactive"] = parent_agent.non_interactive
agent = StrixAgent(agent_config)

View File

@@ -180,7 +180,7 @@ def _handle_utility_actions(
raise ValueError(f"Unknown utility action: {action}")
@register_tool
@register_tool(requires_browser_mode=True)
def browser_action(
action: BrowserAction,
url: str | None = None,

View File

@@ -0,0 +1,4 @@
from .load_skill_actions import load_skill
__all__ = ["load_skill"]

View File

@@ -0,0 +1,71 @@
from typing import Any
from strix.tools.registry import register_tool
@register_tool(sandbox_execution=False)
def load_skill(agent_state: Any, skills: str) -> dict[str, Any]:
try:
from strix.skills import parse_skill_list, validate_requested_skills
requested_skills = parse_skill_list(skills)
if not requested_skills:
return {
"success": False,
"error": "No skills provided. Pass one or more comma-separated skill names.",
"requested_skills": [],
}
validation_error = validate_requested_skills(requested_skills)
if validation_error:
return {
"success": False,
"error": validation_error,
"requested_skills": requested_skills,
"loaded_skills": [],
}
from strix.tools.agents_graph.agents_graph_actions import _agent_instances
current_agent = _agent_instances.get(agent_state.agent_id)
if current_agent is None or not hasattr(current_agent, "llm"):
return {
"success": False,
"error": (
"Could not find running agent instance for runtime skill loading. "
"Try again in the current active agent."
),
"requested_skills": requested_skills,
"loaded_skills": [],
}
newly_loaded = current_agent.llm.add_skills(requested_skills)
already_loaded = [skill for skill in requested_skills if skill not in newly_loaded]
prior = agent_state.context.get("loaded_skills", [])
if not isinstance(prior, list):
prior = []
merged_skills = sorted(set(prior).union(requested_skills))
agent_state.update_context("loaded_skills", merged_skills)
except Exception as e: # noqa: BLE001
fallback_requested_skills = (
requested_skills
if "requested_skills" in locals()
else [s.strip() for s in skills.split(",") if s.strip()]
)
return {
"success": False,
"error": f"Failed to load skill(s): {e!s}",
"requested_skills": fallback_requested_skills,
"loaded_skills": [],
}
else:
return {
"success": True,
"requested_skills": requested_skills,
"loaded_skills": requested_skills,
"newly_loaded_skills": newly_loaded,
"already_loaded_skills": already_loaded,
"message": "Skills loaded into this agent prompt context.",
}

View File

@@ -0,0 +1,33 @@
<tools>
<tool name="load_skill">
<description>Dynamically load one or more skills into the current agent at runtime.
Use this when you need exact guidance right before acting (tool syntax, exploit workflow, or protocol details).
This updates the current agent's prompt context immediately.</description>
<details>Accepts one skill or a comma-separated skill bundle. Works for root agents and subagents.
Examples:
- Single skill: `xss`
- Bundle: `sql_injection,business_logic`</details>
<parameters>
<parameter name="skills" type="string" required="true">
<description>Comma-separated list of skills to use for the agent (MAXIMUM 5 skills allowed). Most agents should have at least one skill in order to be useful. Agents should be highly specialized - use 1-3 related skills; up to 5 for complex contexts. {{DYNAMIC_SKILLS_DESCRIPTION}}</description>
</parameter>
</parameters>
<returns type="Dict[str, Any]">
<description>Response containing: - success: Whether runtime loading succeeded - requested_skills: Skills requested - loaded_skills: Skills validated and applied - newly_loaded_skills: Skills newly injected into prompt - already_loaded_skills: Skills already present in prompt context</description>
</returns>
<examples>
<function=load_skill>
<parameter=skills>xss</parameter>
</function>
<function=load_skill>
<parameter=skills>sql_injection,business_logic</parameter>
</function>
<function=load_skill>
<parameter=skills>nmap,httpx</parameter>
</function>
</examples>
</tool>
</tools>

View File

@@ -1,6 +1,6 @@
<tools>
<tool name="python_action">
<description>Perform Python actions using persistent interpreter sessions for cybersecurity tasks.</description>
<description>Perform Python actions using persistent interpreter sessions for cybersecurity tasks. This is the PREFERRED tool for Python code because it provides structured execution, persistence, cleaner output, and easier debugging than embedding Python inside terminal commands.</description>
<details>Common Use Cases:
- Security script development and testing (payload generation, exploit scripts)
- Data analysis of security logs, network traffic, or vulnerability scans
@@ -58,9 +58,14 @@
- IPython magic commands are fully supported (%pip, %time, %whos, %%writefile, etc.)
- Line magics (%) and cell magics (%%) work as expected
6. CLOSE: Terminates the session completely and frees memory
7. The Python sessions can operate concurrently with other tools. You may invoke
7. PREFER THIS TOOL OVER TERMINAL FOR PYTHON:
- If you are writing or running Python code, use python_action instead of terminal_execute
- Do NOT wrap Python in bash heredocs, here-strings, python -c one-liners, or interactive REPL sessions when the Python tool can do the job
- The Python tool exists so code execution is structured, stateful, easier to continue across calls, and easier to inspect/debug
- Use terminal_execute for shell commands, package managers, non-Python CLIs, process control, and launching services
8. The Python sessions can operate concurrently with other tools. You may invoke
terminal, browser, or other tools while maintaining active Python sessions.
8. Each session has its own isolated namespace - variables in one session don't
9. Each session has its own isolated namespace - variables in one session don't
affect others.
</notes>
<examples>

View File

@@ -149,10 +149,60 @@ def _get_schema_path(func: Callable[..., Any]) -> Path | None:
return get_strix_resource_path("tools", folder, schema_file)
def _is_sandbox_mode() -> bool:
return os.getenv("STRIX_SANDBOX_MODE", "false").lower() == "true"
def _is_browser_disabled() -> bool:
if os.getenv("STRIX_DISABLE_BROWSER", "").lower() == "true":
return True
from strix.config import Config
val: str = Config.load().get("env", {}).get("STRIX_DISABLE_BROWSER", "")
return str(val).lower() == "true"
def _has_perplexity_api() -> bool:
if os.getenv("PERPLEXITY_API_KEY"):
return True
from strix.config import Config
return bool(Config.load().get("env", {}).get("PERPLEXITY_API_KEY"))
def _should_register_tool(
*,
sandbox_execution: bool,
requires_browser_mode: bool,
requires_web_search_mode: bool,
) -> bool:
sandbox_mode = _is_sandbox_mode()
if sandbox_mode and not sandbox_execution:
return False
if requires_browser_mode and _is_browser_disabled():
return False
return not (requires_web_search_mode and not _has_perplexity_api())
def register_tool(
func: Callable[..., Any] | None = None, *, sandbox_execution: bool = True
func: Callable[..., Any] | None = None,
*,
sandbox_execution: bool = True,
requires_browser_mode: bool = False,
requires_web_search_mode: bool = False,
) -> Callable[..., Any]:
def decorator(f: Callable[..., Any]) -> Callable[..., Any]:
if not _should_register_tool(
sandbox_execution=sandbox_execution,
requires_browser_mode=requires_browser_mode,
requires_web_search_mode=requires_web_search_mode,
):
return f
sandbox_mode = _is_sandbox_mode()
func_dict = {
"name": f.__name__,
"function": f,
@@ -160,7 +210,6 @@ def register_tool(
"sandbox_execution": sandbox_execution,
}
sandbox_mode = os.getenv("STRIX_SANDBOX_MODE", "false").lower() == "true"
if not sandbox_mode:
try:
schema_path = _get_schema_path(f)

View File

@@ -59,6 +59,11 @@
- AVOID: Long pipelines, complex bash scripts, or convoluted one-liners
- Break complex operations into multiple simple tool calls for clarity and debugging
- For multiple commands, prefer separate tool calls over chaining with && or ;
- Do NOT use this tool to run embedded Python via heredocs, here-strings, python -c, or ad hoc Python REPL input when python_action can be used instead
- If the task is primarily Python code execution, data processing, HTTP automation in Python, or iterative Python scripting, use python_action because it is persistent, structured, and easier to debug
- Use terminal_execute for actual shell work: CLI tools, package managers, file/system commands, process control, and starting or supervising services
- Before improvising a complex workflow, payload set, protocol sequence, or tool syntax from memory, consider calling load_skill to inject the exact specialized guidance you need
- Prefer load_skill plus the right tool over ad hoc shell experimentation when a relevant skill exists
3. LONG-RUNNING COMMANDS:
- Commands never get killed automatically - they keep running in background

View File

@@ -31,7 +31,7 @@ Structure your response to be comprehensive yet concise, emphasizing the most cr
security implications and details."""
@register_tool(sandbox_execution=False)
@register_tool(sandbox_execution=False, requires_web_search_mode=True)
def web_search(query: str) -> dict[str, Any]:
try:
api_key = os.getenv("PERPLEXITY_API_KEY")
@@ -46,7 +46,7 @@ def web_search(query: str) -> dict[str, Any]:
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
"model": "sonar-reasoning",
"model": "sonar-reasoning-pro",
"messages": [
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": query},

1
tests/config/__init__.py Normal file
View File

@@ -0,0 +1 @@
"""Tests for strix.config module."""

View File

@@ -0,0 +1,55 @@
import json
from strix.config.config import Config
def test_traceloop_vars_are_tracked() -> None:
tracked = Config.tracked_vars()
assert "STRIX_OTEL_TELEMETRY" in tracked
assert "STRIX_POSTHOG_TELEMETRY" in tracked
assert "TRACELOOP_BASE_URL" in tracked
assert "TRACELOOP_API_KEY" in tracked
assert "TRACELOOP_HEADERS" in tracked
def test_apply_saved_uses_saved_traceloop_vars(monkeypatch, tmp_path) -> None:
config_path = tmp_path / "cli-config.json"
config_path.write_text(
json.dumps(
{
"env": {
"TRACELOOP_BASE_URL": "https://otel.example.com",
"TRACELOOP_API_KEY": "api-key",
"TRACELOOP_HEADERS": "x-test=value",
}
}
),
encoding="utf-8",
)
monkeypatch.setattr(Config, "_config_file_override", config_path)
monkeypatch.delenv("TRACELOOP_BASE_URL", raising=False)
monkeypatch.delenv("TRACELOOP_API_KEY", raising=False)
monkeypatch.delenv("TRACELOOP_HEADERS", raising=False)
applied = Config.apply_saved()
assert applied["TRACELOOP_BASE_URL"] == "https://otel.example.com"
assert applied["TRACELOOP_API_KEY"] == "api-key"
assert applied["TRACELOOP_HEADERS"] == "x-test=value"
def test_apply_saved_respects_existing_env_traceloop_vars(monkeypatch, tmp_path) -> None:
config_path = tmp_path / "cli-config.json"
config_path.write_text(
json.dumps({"env": {"TRACELOOP_BASE_URL": "https://otel.example.com"}}),
encoding="utf-8",
)
monkeypatch.setattr(Config, "_config_file_override", config_path)
monkeypatch.setenv("TRACELOOP_BASE_URL", "https://env.example.com")
applied = Config.apply_saved(force=False)
assert "TRACELOOP_BASE_URL" not in applied

View File

@@ -0,0 +1,16 @@
import litellm
import pytest
from strix.llm.config import LLMConfig
from strix.llm.llm import LLM
def test_llm_does_not_modify_litellm_callbacks(monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setenv("STRIX_TELEMETRY", "1")
monkeypatch.setenv("STRIX_OTEL_TELEMETRY", "1")
monkeypatch.setattr(litellm, "callbacks", ["custom-callback"])
llm = LLM(LLMConfig(model_name="openai/gpt-5.4"), agent_name=None)
assert llm is not None
assert litellm.callbacks == ["custom-callback"]

1
tests/skills/__init__.py Normal file
View File

@@ -0,0 +1 @@
# Tests for skill-related runtime behavior.

View File

@@ -0,0 +1,28 @@
from strix.telemetry.flags import is_otel_enabled, is_posthog_enabled
def test_flags_fallback_to_strix_telemetry(monkeypatch) -> None:
monkeypatch.delenv("STRIX_OTEL_TELEMETRY", raising=False)
monkeypatch.delenv("STRIX_POSTHOG_TELEMETRY", raising=False)
monkeypatch.setenv("STRIX_TELEMETRY", "0")
assert is_otel_enabled() is False
assert is_posthog_enabled() is False
def test_otel_flag_overrides_global_telemetry(monkeypatch) -> None:
monkeypatch.setenv("STRIX_TELEMETRY", "0")
monkeypatch.setenv("STRIX_OTEL_TELEMETRY", "1")
monkeypatch.delenv("STRIX_POSTHOG_TELEMETRY", raising=False)
assert is_otel_enabled() is True
assert is_posthog_enabled() is False
def test_posthog_flag_overrides_global_telemetry(monkeypatch) -> None:
monkeypatch.setenv("STRIX_TELEMETRY", "0")
monkeypatch.setenv("STRIX_POSTHOG_TELEMETRY", "1")
monkeypatch.delenv("STRIX_OTEL_TELEMETRY", raising=False)
assert is_otel_enabled() is False
assert is_posthog_enabled() is True

View File

@@ -0,0 +1,379 @@
import json
import sys
import types
from pathlib import Path
from typing import Any, ClassVar
import pytest
from opentelemetry.sdk.trace.export import SimpleSpanProcessor, SpanExportResult
from strix.telemetry import tracer as tracer_module
from strix.telemetry import utils as telemetry_utils
from strix.telemetry.tracer import Tracer, set_global_tracer
def _load_events(events_path: Path) -> list[dict[str, Any]]:
lines = events_path.read_text(encoding="utf-8").splitlines()
return [json.loads(line) for line in lines if line]
@pytest.fixture(autouse=True)
def _reset_tracer_globals(monkeypatch) -> None:
monkeypatch.setattr(tracer_module, "_global_tracer", None)
monkeypatch.setattr(tracer_module, "_OTEL_BOOTSTRAPPED", False)
monkeypatch.setattr(tracer_module, "_OTEL_REMOTE_ENABLED", False)
telemetry_utils.reset_events_write_locks()
monkeypatch.delenv("STRIX_TELEMETRY", raising=False)
monkeypatch.delenv("STRIX_OTEL_TELEMETRY", raising=False)
monkeypatch.delenv("STRIX_POSTHOG_TELEMETRY", raising=False)
monkeypatch.delenv("TRACELOOP_BASE_URL", raising=False)
monkeypatch.delenv("TRACELOOP_API_KEY", raising=False)
monkeypatch.delenv("TRACELOOP_HEADERS", raising=False)
def test_tracer_local_mode_writes_jsonl_with_correlation(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
tracer = Tracer("local-observability")
set_global_tracer(tracer)
tracer.set_scan_config({"targets": ["https://example.com"], "user_instructions": "focus auth"})
tracer.log_agent_creation("agent-1", "Root Agent", "scan auth")
tracer.log_chat_message("starting scan", "user", "agent-1")
execution_id = tracer.log_tool_execution_start(
"agent-1",
"send_request",
{"url": "https://example.com/login"},
)
tracer.update_tool_execution(execution_id, "completed", {"status_code": 200, "body": "ok"})
events_path = tmp_path / "strix_runs" / "local-observability" / "events.jsonl"
assert events_path.exists()
events = _load_events(events_path)
assert any(event["event_type"] == "tool.execution.updated" for event in events)
assert not any(event["event_type"] == "traffic.intercepted" for event in events)
for event in events:
assert event["run_id"] == "local-observability"
assert event["trace_id"]
assert event["span_id"]
def test_tracer_redacts_sensitive_payloads(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
tracer = Tracer("redaction-run")
set_global_tracer(tracer)
execution_id = tracer.log_tool_execution_start(
"agent-1",
"send_request",
{
"url": "https://example.com",
"api_key": "sk-secret-token-value",
"authorization": "Bearer super-secret-token",
},
)
tracer.update_tool_execution(
execution_id,
"error",
{"error": "request failed with token sk-secret-token-value"},
)
events_path = tmp_path / "strix_runs" / "redaction-run" / "events.jsonl"
events = _load_events(events_path)
serialized = json.dumps(events)
assert "sk-secret-token-value" not in serialized
assert "super-secret-token" not in serialized
assert "[REDACTED]" in serialized
def test_tracer_remote_mode_configures_traceloop_export(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
class FakeTraceloop:
init_calls: ClassVar[list[dict[str, Any]]] = []
@staticmethod
def init(**kwargs: Any) -> None:
FakeTraceloop.init_calls.append(kwargs)
@staticmethod
def set_association_properties(properties: dict[str, Any]) -> None: # noqa: ARG004
return None
monkeypatch.setattr(tracer_module, "Traceloop", FakeTraceloop)
monkeypatch.setenv("TRACELOOP_BASE_URL", "https://otel.example.com")
monkeypatch.setenv("TRACELOOP_API_KEY", "test-api-key")
monkeypatch.setenv("TRACELOOP_HEADERS", '{"x-custom":"header"}')
tracer = Tracer("remote-observability")
set_global_tracer(tracer)
tracer.log_chat_message("hello", "user", "agent-1")
assert tracer._remote_export_enabled is True
assert FakeTraceloop.init_calls
init_kwargs = FakeTraceloop.init_calls[-1]
assert init_kwargs["api_endpoint"] == "https://otel.example.com"
assert init_kwargs["api_key"] == "test-api-key"
assert init_kwargs["headers"] == {"x-custom": "header"}
assert isinstance(init_kwargs["processor"], SimpleSpanProcessor)
assert "strix.run_id" not in init_kwargs["resource_attributes"]
assert "strix.run_name" not in init_kwargs["resource_attributes"]
events_path = tmp_path / "strix_runs" / "remote-observability" / "events.jsonl"
events = _load_events(events_path)
run_started = next(event for event in events if event["event_type"] == "run.started")
assert run_started["payload"]["remote_export_enabled"] is True
def test_tracer_local_mode_avoids_traceloop_remote_endpoint(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
class FakeTraceloop:
init_calls: ClassVar[list[dict[str, Any]]] = []
@staticmethod
def init(**kwargs: Any) -> None:
FakeTraceloop.init_calls.append(kwargs)
@staticmethod
def set_association_properties(properties: dict[str, Any]) -> None: # noqa: ARG004
return None
monkeypatch.setattr(tracer_module, "Traceloop", FakeTraceloop)
tracer = Tracer("local-traceloop")
set_global_tracer(tracer)
tracer.log_chat_message("hello", "user", "agent-1")
assert FakeTraceloop.init_calls
init_kwargs = FakeTraceloop.init_calls[-1]
assert "api_endpoint" not in init_kwargs
assert "api_key" not in init_kwargs
assert "headers" not in init_kwargs
assert isinstance(init_kwargs["processor"], SimpleSpanProcessor)
assert tracer._remote_export_enabled is False
def test_otlp_fallback_includes_auth_and_custom_headers(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
monkeypatch.setattr(tracer_module, "Traceloop", None)
monkeypatch.setenv("TRACELOOP_BASE_URL", "https://otel.example.com")
monkeypatch.setenv("TRACELOOP_API_KEY", "test-api-key")
monkeypatch.setenv("TRACELOOP_HEADERS", '{"x-custom":"header"}')
captured: dict[str, Any] = {}
class FakeOTLPSpanExporter:
def __init__(self, endpoint: str, headers: dict[str, str] | None = None, **kwargs: Any):
captured["endpoint"] = endpoint
captured["headers"] = headers or {}
captured["kwargs"] = kwargs
def export(self, spans: Any) -> SpanExportResult: # noqa: ARG002
return SpanExportResult.SUCCESS
def shutdown(self) -> None:
return None
def force_flush(self, timeout_millis: int = 30_000) -> bool: # noqa: ARG002
return True
fake_module = types.ModuleType("opentelemetry.exporter.otlp.proto.http.trace_exporter")
fake_module.OTLPSpanExporter = FakeOTLPSpanExporter
monkeypatch.setitem(
sys.modules,
"opentelemetry.exporter.otlp.proto.http.trace_exporter",
fake_module,
)
tracer = Tracer("otlp-fallback")
set_global_tracer(tracer)
assert tracer._remote_export_enabled is True
assert captured["endpoint"] == "https://otel.example.com/v1/traces"
assert captured["headers"]["Authorization"] == "Bearer test-api-key"
assert captured["headers"]["x-custom"] == "header"
def test_traceloop_init_failure_does_not_mark_bootstrapped_on_provider_failure(
monkeypatch, tmp_path
) -> None:
monkeypatch.chdir(tmp_path)
class FakeTraceloop:
@staticmethod
def init(**kwargs: Any) -> None: # noqa: ARG004
raise RuntimeError("traceloop init failed")
@staticmethod
def set_association_properties(properties: dict[str, Any]) -> None: # noqa: ARG004
return None
monkeypatch.setattr(tracer_module, "Traceloop", FakeTraceloop)
def _raise_provider_error(provider: Any) -> None:
raise RuntimeError("provider setup failed")
monkeypatch.setattr(tracer_module.trace, "set_tracer_provider", _raise_provider_error)
tracer = Tracer("bootstrap-failure")
set_global_tracer(tracer)
assert tracer_module._OTEL_BOOTSTRAPPED is False
assert tracer._remote_export_enabled is False
def test_run_completed_event_emitted_once(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
tracer = Tracer("single-complete")
set_global_tracer(tracer)
tracer.save_run_data(mark_complete=True)
tracer.save_run_data(mark_complete=True)
events_path = tmp_path / "strix_runs" / "single-complete" / "events.jsonl"
events = _load_events(events_path)
run_completed = [event for event in events if event["event_type"] == "run.completed"]
assert len(run_completed) == 1
def test_events_with_agent_id_include_agent_name(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
tracer = Tracer("agent-name-enrichment")
set_global_tracer(tracer)
tracer.log_agent_creation("agent-1", "Root Agent", "scan auth")
tracer.log_chat_message("hello", "assistant", "agent-1")
events_path = tmp_path / "strix_runs" / "agent-name-enrichment" / "events.jsonl"
events = _load_events(events_path)
chat_event = next(event for event in events if event["event_type"] == "chat.message")
assert chat_event["actor"]["agent_id"] == "agent-1"
assert chat_event["actor"]["agent_name"] == "Root Agent"
def test_run_metadata_is_only_on_run_lifecycle_events(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
tracer = Tracer("metadata-scope")
set_global_tracer(tracer)
tracer.log_chat_message("hello", "assistant", "agent-1")
tracer.save_run_data(mark_complete=True)
events_path = tmp_path / "strix_runs" / "metadata-scope" / "events.jsonl"
events = _load_events(events_path)
run_started = next(event for event in events if event["event_type"] == "run.started")
run_completed = next(event for event in events if event["event_type"] == "run.completed")
chat_event = next(event for event in events if event["event_type"] == "chat.message")
assert "run_metadata" in run_started
assert "run_metadata" in run_completed
assert "run_metadata" not in chat_event
def test_set_run_name_resets_cached_paths(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
tracer = Tracer()
set_global_tracer(tracer)
old_events_path = tracer.events_file_path
tracer.set_run_name("renamed-run")
tracer.log_chat_message("hello", "assistant", "agent-1")
new_events_path = tracer.events_file_path
assert new_events_path != old_events_path
assert new_events_path == tmp_path / "strix_runs" / "renamed-run" / "events.jsonl"
events = _load_events(new_events_path)
assert any(event["event_type"] == "run.started" for event in events)
assert any(event["event_type"] == "chat.message" for event in events)
def test_set_run_name_resets_run_completed_flag(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
tracer = Tracer()
set_global_tracer(tracer)
tracer.save_run_data(mark_complete=True)
tracer.set_run_name("renamed-complete")
tracer.save_run_data(mark_complete=True)
events_path = tmp_path / "strix_runs" / "renamed-complete" / "events.jsonl"
events = _load_events(events_path)
run_completed = [event for event in events if event["event_type"] == "run.completed"]
assert any(event["event_type"] == "run.started" for event in events)
assert len(run_completed) == 1
def test_set_run_name_updates_traceloop_association_properties(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
class FakeTraceloop:
associations: ClassVar[list[dict[str, Any]]] = []
@staticmethod
def init(**kwargs: Any) -> None: # noqa: ARG004
return None
@staticmethod
def set_association_properties(properties: dict[str, Any]) -> None:
FakeTraceloop.associations.append(properties)
monkeypatch.setattr(tracer_module, "Traceloop", FakeTraceloop)
tracer = Tracer()
set_global_tracer(tracer)
tracer.set_run_name("renamed-run")
assert FakeTraceloop.associations
assert FakeTraceloop.associations[-1]["run_id"] == "renamed-run"
assert FakeTraceloop.associations[-1]["run_name"] == "renamed-run"
def test_events_write_locks_are_scoped_by_events_file(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
monkeypatch.setenv("STRIX_TELEMETRY", "0")
tracer_one = Tracer("lock-run-a")
tracer_two = Tracer("lock-run-b")
lock_a_from_one = tracer_one._get_events_write_lock(tracer_one.events_file_path)
lock_a_from_two = tracer_two._get_events_write_lock(tracer_one.events_file_path)
lock_b = tracer_two._get_events_write_lock(tracer_two.events_file_path)
assert lock_a_from_one is lock_a_from_two
assert lock_a_from_one is not lock_b
def test_tracer_skips_jsonl_when_telemetry_disabled(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
monkeypatch.setenv("STRIX_TELEMETRY", "0")
tracer = Tracer("telemetry-disabled")
set_global_tracer(tracer)
tracer.log_chat_message("hello", "assistant", "agent-1")
tracer.save_run_data(mark_complete=True)
events_path = tmp_path / "strix_runs" / "telemetry-disabled" / "events.jsonl"
assert not events_path.exists()
def test_tracer_otel_flag_overrides_global_telemetry(monkeypatch, tmp_path) -> None:
monkeypatch.chdir(tmp_path)
monkeypatch.setenv("STRIX_TELEMETRY", "0")
monkeypatch.setenv("STRIX_OTEL_TELEMETRY", "1")
tracer = Tracer("otel-enabled")
set_global_tracer(tracer)
tracer.log_chat_message("hello", "assistant", "agent-1")
tracer.save_run_data(mark_complete=True)
events_path = tmp_path / "strix_runs" / "otel-enabled" / "events.jsonl"
assert events_path.exists()

View File

@@ -0,0 +1,39 @@
from strix.telemetry.utils import prune_otel_span_attributes
def test_prune_otel_span_attributes_drops_high_volume_prompt_content() -> None:
attributes = {
"gen_ai.operation.name": "openai.chat",
"gen_ai.request.model": "gpt-5.2",
"gen_ai.prompt.0.role": "system",
"gen_ai.prompt.0.content": "a" * 20_000,
"gen_ai.completion.0.content": "b" * 10_000,
"llm.input_messages.0.content": "c" * 5_000,
"llm.output_messages.0.content": "d" * 5_000,
"llm.input": "x" * 3_000,
"llm.output": "y" * 3_000,
}
pruned = prune_otel_span_attributes(attributes)
assert "gen_ai.prompt.0.content" not in pruned
assert "gen_ai.completion.0.content" not in pruned
assert "llm.input_messages.0.content" not in pruned
assert "llm.output_messages.0.content" not in pruned
assert "llm.input" not in pruned
assert "llm.output" not in pruned
assert pruned["gen_ai.operation.name"] == "openai.chat"
assert pruned["gen_ai.prompt.0.role"] == "system"
assert pruned["strix.filtered_attributes_count"] == 6
def test_prune_otel_span_attributes_keeps_metadata_when_nothing_is_dropped() -> None:
attributes = {
"gen_ai.operation.name": "openai.chat",
"gen_ai.request.model": "gpt-5.2",
"gen_ai.prompt.0.role": "user",
}
pruned = prune_otel_span_attributes(attributes)
assert pruned == attributes

View File

@@ -0,0 +1,139 @@
from typing import Any
from strix.tools.agents_graph import agents_graph_actions
from strix.tools.load_skill import load_skill_actions
class _DummyLLM:
def __init__(self, initial_skills: list[str] | None = None) -> None:
self.loaded: set[str] = set(initial_skills or [])
def add_skills(self, skill_names: list[str]) -> list[str]:
newly_loaded = [skill for skill in skill_names if skill not in self.loaded]
self.loaded.update(newly_loaded)
return newly_loaded
class _DummyAgent:
def __init__(self, initial_skills: list[str] | None = None) -> None:
self.llm = _DummyLLM(initial_skills)
class _DummyAgentState:
def __init__(self, agent_id: str) -> None:
self.agent_id = agent_id
self.context: dict[str, Any] = {}
def update_context(self, key: str, value: Any) -> None:
self.context[key] = value
def test_load_skill_success_and_context_update() -> None:
instances = agents_graph_actions.__dict__["_agent_instances"]
original_instances = dict(instances)
try:
state = _DummyAgentState("agent_test_load_skill_success")
instances.clear()
instances[state.agent_id] = _DummyAgent()
result = load_skill_actions.load_skill(state, "ffuf,xss")
assert result["success"] is True
assert result["loaded_skills"] == ["ffuf", "xss"]
assert result["newly_loaded_skills"] == ["ffuf", "xss"]
assert state.context["loaded_skills"] == ["ffuf", "xss"]
finally:
instances.clear()
instances.update(original_instances)
def test_load_skill_uses_same_plain_skill_format_as_create_agent() -> None:
instances = agents_graph_actions.__dict__["_agent_instances"]
original_instances = dict(instances)
try:
state = _DummyAgentState("agent_test_load_skill_short_name")
instances.clear()
instances[state.agent_id] = _DummyAgent()
result = load_skill_actions.load_skill(state, "nmap")
assert result["success"] is True
assert result["loaded_skills"] == ["nmap"]
assert result["newly_loaded_skills"] == ["nmap"]
assert state.context["loaded_skills"] == ["nmap"]
finally:
instances.clear()
instances.update(original_instances)
def test_load_skill_invalid_skill_returns_error() -> None:
instances = agents_graph_actions.__dict__["_agent_instances"]
original_instances = dict(instances)
try:
state = _DummyAgentState("agent_test_load_skill_invalid")
instances.clear()
instances[state.agent_id] = _DummyAgent()
result = load_skill_actions.load_skill(state, "definitely_not_a_real_skill")
assert result["success"] is False
assert "Invalid skills" in result["error"]
assert "Available skills" in result["error"]
finally:
instances.clear()
instances.update(original_instances)
def test_load_skill_rejects_more_than_five_skills() -> None:
instances = agents_graph_actions.__dict__["_agent_instances"]
original_instances = dict(instances)
try:
state = _DummyAgentState("agent_test_load_skill_too_many")
instances.clear()
instances[state.agent_id] = _DummyAgent()
result = load_skill_actions.load_skill(state, "a,b,c,d,e,f")
assert result["success"] is False
assert result["error"] == (
"Cannot specify more than 5 skills for an agent (use comma-separated format)"
)
finally:
instances.clear()
instances.update(original_instances)
def test_load_skill_missing_agent_instance_returns_error() -> None:
instances = agents_graph_actions.__dict__["_agent_instances"]
original_instances = dict(instances)
try:
state = _DummyAgentState("agent_test_load_skill_missing_instance")
instances.clear()
result = load_skill_actions.load_skill(state, "httpx")
assert result["success"] is False
assert "running agent instance" in result["error"]
finally:
instances.clear()
instances.update(original_instances)
def test_load_skill_does_not_reload_skill_already_present_from_agent_creation() -> None:
instances = agents_graph_actions.__dict__["_agent_instances"]
original_instances = dict(instances)
try:
state = _DummyAgentState("agent_test_load_skill_existing_config_skill")
instances.clear()
instances[state.agent_id] = _DummyAgent(["xss"])
result = load_skill_actions.load_skill(state, "xss,sql_injection")
assert result["success"] is True
assert result["loaded_skills"] == ["xss", "sql_injection"]
assert result["newly_loaded_skills"] == ["sql_injection"]
assert result["already_loaded_skills"] == ["xss"]
assert state.context["loaded_skills"] == ["sql_injection", "xss"]
finally:
instances.clear()
instances.update(original_instances)

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import importlib
import sys
from types import ModuleType
from typing import Any
from strix.config import Config
from strix.tools.registry import clear_registry
def _empty_config_load(_cls: type[Config]) -> dict[str, dict[str, str]]:
return {"env": {}}
def _reload_tools_module() -> ModuleType:
clear_registry()
for name in list(sys.modules):
if name == "strix.tools" or name.startswith("strix.tools."):
sys.modules.pop(name, None)
return importlib.import_module("strix.tools")
def test_non_sandbox_registers_agents_graph_but_not_browser_or_web_search_when_disabled(
monkeypatch: Any,
) -> None:
monkeypatch.setenv("STRIX_SANDBOX_MODE", "false")
monkeypatch.setenv("STRIX_DISABLE_BROWSER", "true")
monkeypatch.delenv("PERPLEXITY_API_KEY", raising=False)
monkeypatch.setattr(Config, "load", classmethod(_empty_config_load))
tools = _reload_tools_module()
names = set(tools.get_tool_names())
assert "create_agent" in names
assert "browser_action" not in names
assert "web_search" not in names
def test_sandbox_registers_sandbox_tools_but_not_non_sandbox_tools(
monkeypatch: Any,
) -> None:
monkeypatch.setenv("STRIX_SANDBOX_MODE", "true")
monkeypatch.setenv("STRIX_DISABLE_BROWSER", "true")
monkeypatch.delenv("PERPLEXITY_API_KEY", raising=False)
monkeypatch.setattr(Config, "load", classmethod(_empty_config_load))
tools = _reload_tools_module()
names = set(tools.get_tool_names())
assert "terminal_execute" in names
assert "python_action" in names
assert "list_requests" in names
assert "create_agent" not in names
assert "finish_scan" not in names
assert "load_skill" not in names
assert "browser_action" not in names
assert "web_search" not in names
def test_load_skill_import_does_not_register_create_agent_in_sandbox(
monkeypatch: Any,
) -> None:
monkeypatch.setenv("STRIX_SANDBOX_MODE", "true")
monkeypatch.setenv("STRIX_DISABLE_BROWSER", "true")
monkeypatch.delenv("PERPLEXITY_API_KEY", raising=False)
monkeypatch.setattr(Config, "load", classmethod(_empty_config_load))
clear_registry()
for name in list(sys.modules):
if name == "strix.tools" or name.startswith("strix.tools."):
sys.modules.pop(name, None)
load_skill_module = importlib.import_module("strix.tools.load_skill.load_skill_actions")
registry = importlib.import_module("strix.tools.registry")
names_before = set(registry.get_tool_names())
assert "load_skill" not in names_before
assert "create_agent" not in names_before
state_type = type(
"DummyState",
(),
{
"agent_id": "agent_test",
"context": {},
"update_context": lambda self, key, value: self.context.__setitem__(key, value),
},
)
result = load_skill_module.load_skill(state_type(), "nmap")
names_after = set(registry.get_tool_names())
assert "create_agent" not in names_after
assert result["success"] is False