* fix: resolve pre-commit check failures - Change RuntimeError to TypeError for type validation in report/writer.py - Update pyupgrade to v3.21.2 for Python 3.14 compatibility * chore: add pytest test infrastructure Mirror the layout introduced on feature/438-token_budget: pytest + pytest-asyncio dev deps, asyncio_mode auto, a tests.* mypy override, and pytest in the mypy pre-commit hook deps so the tests/ package type-checks. * feat: add --mount and large-target pre-flight for local repos (#492) Large local targets were copied into the sandbox file-by-file via the SDK LocalDir entry, which stalls on big repos and could leave /workspace empty. - --mount <path> bind-mounts a host directory read-only at /workspace/<subdir> instead of copying it, bypassing the per-file stream. - A size pre-flight (STRIX_MAX_LOCAL_COPY_MB, default 1024) fails fast with a clear message suggesting --mount when a non-mounted local target is too big. * fix: reject empty --mount paths An empty or whitespace-only --mount value resolves to the current working directory and would silently bind-mount it into the sandbox. Reject it. * fix: dedupe local targets so a dir is never both copied and mounted If the same directory is passed via --target and --mount (or as duplicate values), it previously produced two targets — copied AND bind-mounted, and the copied one could trip the size pre-flight. Dedupe by resolved path, preferring the bind mount. * fix: treat non-positive STRIX_MAX_LOCAL_COPY_MB as disabled Previously a value of 0 (or negative) made every local target count as oversized, aborting all local scans. Now <= 0 disables the pre-flight. * fix: log unreadable subtrees during size pre-flight os.walk silently swallowed directory-listing errors, so a permission-denied subtree could make a large repo under-count and slip past the pre-flight. Surface such omissions via an onerror warning. * docs: document --mount and STRIX_MAX_LOCAL_COPY_MB Add CLI reference + example for --mount, document the size pre-flight env var, note the read-only-is-not-a-hard-boundary caveat and that remote repos are not size-checked, and clarify the backends docstring on when bind mounts apply. * Update strix/interface/main.py * Update strix/runtime/docker_client.py ---------
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 - Get started with no setup required.
Strix Overview
Strix are autonomous AI agents that act just like real hackers - they run your code dynamically, find vulnerabilities, and validate them through actual proof-of-concepts. Built for developers and security teams who need fast, accurate security testing without the overhead of manual pentesting or the false positives of static analysis tools.
Key Capabilities:
- Full hacker toolkit out of the box
- Teams of agents that collaborate and scale
- Real validation with PoCs, not false positives
- Developer‑first CLI with actionable reports
- Auto‑fix & reporting to accelerate remediation
Use Cases
- Application Security Testing - Detect and validate critical vulnerabilities in your applications
- Rapid Penetration Testing - Get penetration tests done in hours, not weeks, with compliance reports
- Bug Bounty Automation - Automate bug bounty research and generate PoCs for faster reporting
- CI/CD Integration - Run tests in CI/CD to block vulnerabilities before reaching production
🚀 Quick Start
Prerequisites:
- Docker (running)
- An LLM API key from any supported provider (OpenAI, Anthropic, Google, etc.)
Installation & First Scan
# Install Strix
curl -sSL https://strix.ai/install | bash
# Configure your AI provider
export STRIX_LLM="openai/gpt-5.4"
export LLM_API_KEY="your-api-key"
# Run your first security assessment
strix --target ./app-directory
Note
First run automatically pulls the sandbox Docker image. Results are saved to
strix_runs/<run-name>
☁️ Strix Platform
Try the Strix full-stack security platform at 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
✨ Features
Agentic Security Tools
Strix agents come equipped with a comprehensive security testing toolkit:
- Full HTTP Proxy - Full request/response manipulation and analysis
- Browser Automation - Multi-tab browser for testing of XSS, CSRF, auth flows
- Terminal Environments - Interactive shells for command execution and testing
- Python Runtime - Custom exploit development and validation
- Reconnaissance - Automated OSINT and attack surface mapping
- Code Analysis - Static and dynamic analysis capabilities
- Knowledge Management - Structured findings and attack documentation
Comprehensive Vulnerability Detection
Strix can identify and validate a wide range of security vulnerabilities:
- Access Control - IDOR, privilege escalation, auth bypass
- Injection Attacks - SQL, NoSQL, command injection
- Server-Side - SSRF, XXE, deserialization flaws
- Client-Side - XSS, prototype pollution, DOM vulnerabilities
- Business Logic - Race conditions, workflow manipulation
- Authentication - JWT vulnerabilities, session management
- Infrastructure - Misconfigurations, exposed services
Graph of Agents
Advanced multi-agent orchestration for comprehensive security testing:
- Distributed Workflows - Specialized agents for different attacks and assets
- Scalable Testing - Parallel execution for fast comprehensive coverage
- Dynamic Coordination - Agents collaborate and share discoveries
Usage Examples
Basic Usage
# Scan a local codebase
strix --target ./app-directory
# Security review of a GitHub repository
strix --target https://github.com/org/repo
# Black-box web application assessment
strix --target https://your-app.com
Advanced Testing Scenarios
# Grey-box authenticated testing
strix --target https://your-app.com --instruction "Perform authenticated testing using credentials: user:pass"
# Multi-target testing (source code + deployed app)
strix -t https://github.com/org/app -t https://your-app.com
# White-box source-aware scan (local repository)
strix --target ./app-directory --scan-mode standard
# Focused testing with custom instructions
strix --target api.your-app.com --instruction "Focus on business logic flaws and IDOR vulnerabilities"
# Provide detailed instructions through file (e.g., rules of engagement, scope, exclusions)
strix --target api.your-app.com --instruction-file ./instruction.md
# Force PR diff-scope against a specific base branch
strix -n --target ./ --scan-mode quick --scope-mode diff --diff-base origin/main
Headless Mode
Run Strix programmatically without interactive UI using the -n/--non-interactive flag—perfect for servers and automated jobs. The CLI prints real-time vulnerability findings, and the final report before exiting. Exits with non-zero code when vulnerabilities are found.
strix -n --target https://your-app.com
CI/CD (GitHub Actions)
Strix can be added to your pipeline to run a security test on pull requests with a lightweight GitHub Actions workflow:
name: strix-penetration-test
on:
pull_request:
jobs:
security-scan:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Install Strix
run: curl -sSL https://strix.ai/install | bash
- name: Run Strix
env:
STRIX_LLM: ${{ secrets.STRIX_LLM }}
LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
run: strix -n -t ./ --scan-mode quick
Tip
In CI pull request runs, Strix automatically scopes quick reviews to changed files. If diff-scope cannot resolve, ensure checkout uses full history (
fetch-depth: 0) or pass--diff-baseexplicitly.
Configuration
export STRIX_LLM="openai/gpt-5.4"
export LLM_API_KEY="your-api-key"
# Optional
export LLM_API_BASE="your-api-base-url" # if using a local model, e.g. Ollama, LMStudio
export PERPLEXITY_API_KEY="your-api-key" # for search capabilities
export STRIX_REASONING_EFFORT="high" # control thinking effort (default: high, quick scan: medium)
Note
Strix automatically saves your configuration to
~/.strix/cli-config.json, so you don't have to re-enter it on every run.
Recommended models for best results:
- OpenAI GPT-5.4 —
openai/gpt-5.4 - Anthropic Claude Sonnet 4.6 —
anthropic/claude-sonnet-4-6 - Google Gemini 3 Pro Preview —
vertex_ai/gemini-3-pro-preview
See the LLM Providers documentation for all supported providers including Vertex AI, Bedrock, Azure, and local models.
Enterprise
Get the same Strix experience with enterprise-grade 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.
Documentation
Full documentation is available at docs.strix.ai — including detailed guides for usage, CI/CD integrations, skills, and advanced configuration.
Contributing
We welcome contributions of code, docs, and new skills - check out our Contributing Guide to get started or open a pull request/issue.
Join Our Community
Have questions? Found a bug? Want to contribute? Join our Discord!
Support the Project
Love Strix? Give us a ⭐ on GitHub!
Acknowledgements
Strix builds on the incredible work of open-source projects like LiteLLM, Caido, Nuclei, Playwright, and Textual. Huge thanks to their maintainers!
Warning
Only test apps you own or have permission to test. You are responsible for using Strix ethically and legally.