🐍 PySentry
A fast, reliable security vulnerability scanner for Python projects, written in Rust.
Overview
PySentry audits Python projects for known security vulnerabilities by analyzing dependency files (uv.lock
, poetry.lock
, pyproject.toml
, requirements.txt
) and cross-referencing them against multiple vulnerability databases. It provides comprehensive reporting with support for various output formats and filtering options.
Key Features
- Multiple Project Formats: Supports
uv.lock
,poetry.lock
,pyproject.toml
, andrequirements.txt
files - External Resolver Integration: Leverages
uv
andpip-tools
for accurate requirements.txt constraint solving - Multiple Data Sources:
- PyPA Advisory Database (default)
- PyPI JSON API
- OSV.dev (Open Source Vulnerabilities)
- Flexible Output: Human-readable, JSON, and SARIF formats
- Performance Focused:
- Written in Rust for speed
- Async/concurrent processing
- Intelligent caching system
- Comprehensive Filtering:
- Severity levels (low, medium, high, critical)
- Dependency scopes (main only vs all [optional, dev, prod, etc] dependencies)
- Direct vs. transitive dependencies
- Enterprise Ready: SARIF output for IDE/CI integration
Installation
Choose the installation method that works best for you:
⚡ Via uvx (Recommended for occasional use)
Run directly without installing (requires uv):
This method:
- Runs the latest version without installation
- Automatically manages Python environment
- Perfect for CI/CD or occasional security audits
- No need to manage package versions or updates
📦 From PyPI (Python Package)
For Python 3.8+ on Linux and macOS:
Then use it with Python:
# or directly if scripts are in PATH
⚡ From Crates.io (Rust Package)
If you have Rust installed:
💾 From GitHub Releases (Pre-built Binaries)
Download the latest release for your platform:
- Linux x64:
pysentry-linux-x64.tar.gz
- Linux x64 (musl):
pysentry-linux-x64-musl.tar.gz
- Linux ARM64:
pysentry-linux-arm64.tar.gz
- macOS x64:
pysentry-macos-x64.tar.gz
- macOS ARM64:
pysentry-macos-arm64.tar.gz
- Windows x64:
pysentry-windows-x64.zip
# Example for Linux x64
|
🔧 From Source
The binary will be available at target/release/pysentry
.
Requirements
- For uvx: Python 3.8+ and uv installed (Linux/macOS only)
- For binaries: No additional dependencies
- For Python package: Python 3.8+ (Linux/macOS only)
- For Rust package and source: Rust 1.79+
Platform Support
Installation Method | Linux | macOS | Windows |
---|---|---|---|
uvx | ✅ | ✅ | ❌ |
PyPI (pip) | ✅ | ✅ | ❌ |
Crates.io (cargo) | ✅ | ✅ | ✅ |
GitHub Releases | ✅ | ✅ | ✅ |
From Source | ✅ | ✅ | ✅ |
Note: Windows Python wheels are not available due to compilation complexity. Windows users should use the pre-built binary from GitHub releases, install via cargo and build from source.
CLI Command Names
- Rust binary:
pysentry
(when installed via cargo or binary releases) - Python package:
pysentry-rs
(when installed via pip or uvx)
Both variants support identical functionality. The resolver tools (uv
, pip-tools
) must be available in your current environment regardless of which PySentry variant you use.
Requirements.txt Support Prerequisites
To scan requirements.txt
files, PySentry requires an external dependency resolver to convert version constraints (e.g., flask>=2.0,<3.0
) into exact versions for vulnerability scanning.
Install a supported resolver:
# uv (recommended - fastest, Rust-based)
# pip-tools (widely compatible, Python-based)
Environment Requirements:
- Resolvers must be available in your current environment
- If using virtual environments, activate your venv before running PySentry:
- Alternatively, install resolvers globally for system-wide availability
Auto-detection: PySentry automatically detects and prefers: uv
> pip-tools
. Without a resolver, only uv.lock
and poetry.lock
files can be scanned.
Quick Start
Basic Usage
# Using uvx (recommended for occasional use)
# Using installed binary
# Automatically detects project type (uv.lock, poetry.lock, pyproject.toml, requirements.txt)
# Force specific resolver
# Include all dependencies (main + dev + optional)
# Filter by severity (only show high and critical)
# Output to JSON file
Advanced Usage
# Using uvx for comprehensive audit
# Check only direct dependencies using OSV database
# Or with installed binary
# Ignore specific vulnerabilities
# Disable caching for CI environments
# Verbose output for debugging
Advanced Requirements.txt Usage
# Scan multiple requirements files
# Check only direct dependencies from requirements.txt
# Ensure resolver is available in your environment
# Debug requirements.txt resolution
Configuration
Command Line Options
Option | Description | Default |
---|---|---|
--format |
Output format: human , json , sarif |
human |
--severity |
Minimum severity: low , medium , high , critical |
low |
--source |
Vulnerability source: pypa , pypi , osv |
pypa |
--all |
Include all dependencies (main + dev + optional) | false |
--direct-only |
Check only direct dependencies | false |
--ignore |
Vulnerability IDs to ignore (repeatable) | [] |
--output |
Output file path | stdout |
--no-cache |
Disable caching | false |
--cache-dir |
Custom cache directory | ~/.cache/pysentry |
--verbose |
Enable verbose output | false |
--quiet |
Suppress non-error output | false |
--resolver |
Dependency resolver: auto , uv , pip-tools |
auto |
--requirements |
Additional requirements files (repeatable) | [] |
Cache Management
PySentry uses an intelligent caching system to avoid redundant API calls:
- Default Location:
~/.cache/pysentry/
(or system temp directory) - TTL-based Expiration: Separate expiration for each vulnerability source
- Atomic Updates: Prevents cache corruption during concurrent access
- Custom Location: Use
--cache-dir
to specify alternative location
To clear the cache:
Supported Project Formats
uv.lock Files (Recommended)
PySentry has support for uv.lock
files:
- Exact version resolution
- Complete dependency graph analysis
- Source tracking
- Dependency classification (main, dev, optional) including transitive dependencies
poetry.lock Files
Full support for Poetry lock files:
- Exact Version Resolution: Scans exact dependency versions locked by Poetry
- Lock-File Only Analysis: Relies purely on the lock file structure, no pyproject.toml parsing needed
- Complete Dependency Tree: Analyzes all resolved dependencies including transitive ones
- Dependency Classification: Distinguishes between main dependencies and optional groups (dev, test, etc.)
- Source Tracking: Supports PyPI registry, Git repositories, local paths, and direct URLs
Key Features:
- No external tools required
- Fast parsing with exact version information
- Handles Poetry's dependency groups and optional dependencies
- Perfect for Poetry-managed projects with established lock files
requirements.txt Files (External Resolution)
Advanced support for requirements.txt
files using external dependency resolvers:
Key Features:
- Dependencies Resolution: Converts version constraints (e.g.,
flask>=2.0,<3.0
) to exact versions using mature external tools - Multiple Resolver Support:
- uv: Rust-based resolver, extremely fast and reliable (recommended)
- pip-tools: Python-based resolver using
pip-compile
, widely compatible
- Auto-detection: Automatically detects and uses the best available resolver in your environment
- Multiple File Support: Combines
requirements.txt
,requirements-dev.txt
,requirements-test.txt
, etc. - Dependency Classification: Distinguishes between direct and transitive dependencies
- Isolated Execution: Resolvers run in temporary directories to prevent project pollution
- Complex Constraint Handling: Supports version ranges, extras, environment markers, and conflict resolution
Resolution Workflow:
- Detects
requirements.txt
files in your project - Auto-detects available resolver (
uv
orpip-tools
) in current environment - Resolves version constraints to exact dependency versions
- Scans resolved dependencies for vulnerabilities
- Reports findings with direct vs. transitive classification
Environment Setup:
# Ensure resolver is available in your environment
pyproject.toml Files (External Resolution)
Support for projects without lock files:
- Parses version constraints from
pyproject.toml
- Resolver Required: Like requirements.txt, needs external resolvers (
uv
orpip-tools
) to convert version constraints to exact versions for accurate vulnerability scanning - Limited dependency graph information compared to lock files
- Works with both Poetry and PEP 621 formats
Vulnerability Data Sources
PyPA Advisory Database (Default)
- Comprehensive coverage of Python ecosystem
- Community-maintained vulnerability database
- Regular updates from security researchers
PyPI JSON API
- Official PyPI vulnerability data
- Real-time information
- Limited to packages hosted on PyPI
OSV.dev
- Cross-ecosystem vulnerability database
- Google-maintained infrastructure
Output Formats
Human-Readable (Default)
Most comfortable to read.
JSON
SARIF (Static Analysis Results Interchange Format)
Compatible with GitHub Security tab, VS Code, and other security tools.
Performance
PySentry is designed for speed and efficiency:
- Concurrent Processing: Vulnerability data fetched in parallel
- Smart Caching: Reduces API calls and parsing overhead
- Efficient Matching: In-memory indexing for fast vulnerability lookups
- Streaming: Large databases processed without excessive memory usage
Requirements.txt Resolution Performance
PySentry leverages external resolvers for optimal performance:
- uv resolver: 2-10x faster than pip-tools, handles large dependency trees efficiently
- pip-tools resolver: Reliable fallback, slower but widely compatible
- Isolated execution: Prevents project pollution while maintaining security
Benchmarks
Typical performance on a project with 100+ dependencies:
- Cold cache: 15-30 seconds
- Warm cache: 2-5 seconds
- Memory usage: ~50MB peak
Development
Building from Source
Running Tests
Project Structure
src/
├── main.rs # CLI interface
├── lib.rs # Library API
├── cache/ # Caching system
├── dependency/ # Dependency scanning
├── output/ # Report generation
├── parsers/ # Project file parsers
├── providers/ # Vulnerability data sources
├── types.rs # Core type definitions
└── vulnerability/ # Vulnerability matching
Troubleshooting
Common Issues
Error: "No lock file or pyproject.toml found"
# Ensure you're in a Python project directory
# Or specify the path explicitly
Error: "No dependency resolver found" or "uv resolver not available"
# Install a supported resolver in your environment
# Verify resolver is available
# If using virtual environments, ensure resolver is installed there
Error: "Failed to resolve requirements"
# Check your requirements.txt syntax
# Try different resolver
# Ensure you're in correct environment
# Debug with verbose output
Error: "Failed to fetch vulnerability data"
# Check network connectivity
# Try with different source
Slow requirements.txt resolution
# Use faster uv resolver instead of pip-tools
# Install uv for better performance (2-10x faster)
# Or use uvx for isolated execution
Requirements.txt files not being detected
# Ensure requirements.txt exists
# Specify path explicitly
# Include additional requirements files
# Check if higher-priority files exist (they take precedence)
Performance Issues
# Clear cache and retry
# Use verbose mode to identify bottlenecks