OpenAuditKit is not just another linter. It's an intelligent security companion that lives in your terminal. Unlike traditional tools that drown you in false positives, OpenAuditKit combines robust pattern matching (Regex & Entropy) with Context-Aware AI Agents to understand why a piece of code might be dangerous.
Whether you are a solo developer or part of a large enterprise, OpenAuditKit helps you ship secure code faster.
| Feature | Description |
|---|---|
| 🕵️ Secret Scanning | Detects API keys, tokens, and credentials with high-entropy validation. |
| ⚙️ Config Audit | Discovers misconfigurations in Dockerfile, .env, Kubernetes, and more. |
| 🧠 AI Advisory | (New) Integrated AI Agents explain vulnerabilities and suggest fixes. |
| 🏗️ Architecture Analysis | AI agents analyze your project structure for design flaws. |
| 🛡️ Threat Modeling | auto-generates STRIDE threat models based on your codebase. |
| 🔌 Integrations | Native support for CI/CD pipelines (GitHub Actions, GitLab CI). |
| 📝 JSON Reporting | Export findings for easy integration with dashboards like DefectDojo. |
Install simply via pip:
pip install openauditRun a security scan on your current directory:
openaudit scan .Unlock the full potential with AI agents that analyze architecture and data flow:
# Set your OpenAI API Key
openaudit config set-key sk-your-api-key
# Run an AI-enhanced scan
openaudit scan . --aiopenaudit explain src/complex_logic.pyTurn your favorite AI Editor (Cursor, Claude Desktop) into a security expert. OpenAuditKit now supports the Model Context Protocol (MCP).
-
Install OpenAuditKit:
pip install openaudit[mcp]
-
Configure your AI Tool (e.g.,
claude_desktop_config.json):{ "mcpServers": { "openaudit": { "command": "openaudit", "args": ["mcp"] } } } -
Chat with your AI:
"Hey, can you scan this workspace for security issues?" "Check this file for any vulnerabilities or tech debt."
The AI will invoke OpenAuditKit locally and report back findings instantly!
Prevent security issues from being committed by using our pre-configured git hooks.
-
Install pre-commit:
pip install pre-commit
-
Install the hooks:
pre-commit install
Now, openaudit will automatically scan your code before every commit!
Define your own security and quality rules that match your team's standards.
-
Create a custom rules file:
openaudit custom-rules init
-
Edit the generated file (
.openaudit/custom_rules.yaml):rules: - id: "CUSTOM_COMPANY_SECRET" description: "Company API key detected" regex: "MYCOMPANY_[A-Z0-9]{32}" severity: "high" confidence: "high" category: "secret" remediation: "Move to secrets manager."
-
Run scan - Custom rules are automatically loaded:
openaudit scan .
Custom rules can be placed in:
- Project-level:
.openaudit/custom_rules.yaml(committed to repo) - User-level:
~/.openaudit/custom_rules.yaml(personal rules)
We know "vibecodin" happens. OpenAuditKit now includes VibeGuard, a scanner designed to catch non-engineering practices before they hit production:
- 🔍 Annotations: Catches
TODO,FIXME,BUGleftovers. - 🐛 Debug Trash: Finds forgotten
console.log,print(),debugger. - 🤫 Silent Failures: Alerts on
except: pass. - 🌐 Hardcoding: Detects hardcoded IPs and potential secrets.
VibeGuard runs automatically with openaudit scan.
| Feature | OpenAuditKit | Gitleaks | TruffleHog |
|---|---|---|---|
| Finding Secrets | ✅ | ✅ | ✅ |
| Config Analysis | ✅ | ❌ | ❌ |
| AI Context Analysis | ✅ | ❌ | ❌ |
| Architecture Review | ✅ | ❌ | ❌ |
| Offline Capabilities | ✅ | ✅ | ❌* |
*TruffleHog often requires API connectivity for verification.
Secure your pipeline with zero effort. Add this to your .github/workflows/security.yml:
name: Security Audit
on: [push, pull_request]
jobs:
openaudit:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: '3.10'
- run: pip install openaudit
- run: openaudit scan . --ci --fail-on high --ai
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} # Optional for AI featuresAt NeuralForge, we believe security tools should be:
- Silent but Deadly: Only alert on real issues (Low False Positives).
- Educational: Don't just find bugs, explain them.
- Private: Your code never leaves your machine unless you explicitly opt-in to AI features (which are redacted by default).
We love contributions! Please check out our Contributing Guide to get started.
