🐍 PySentry

Help to test and improve | Latest PySentry - pip-audit benchmark

Please, send feedback to nikita@pysentry.com

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, Pipfile.lock, pylock.toml, pyproject.toml, Pipfile, 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, Pipfile.lock, pylock.toml, pyproject.toml, Pipfile, and requirements.txt files
External Resolver Integration: Leverages uv and pip-tools for accurate requirements.txt constraint solving
Multiple Data Sources (all sources used by default):
- PyPA Advisory Database
- PyPI JSON API
- OSV.dev (Open Source Vulnerabilities)
Flexible Output for different workflows: Human-readable, JSON, SARIF, and Markdown formats
Performance Focused:
- Written in Rust for speed
- Async/concurrent processing
- Multi-tier intelligent caching (vulnerability data + resolved dependencies)
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):

uvx pysentry-rs /path/to/project

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 3.9-3.14 on Linux, macOS, and Windows:

pip install pysentry-rs

Then use it with Python:

python -m pysentry /path/to/project
# or directly if scripts are in PATH
pysentry-rs /path/to/project

⚡ From Crates.io (Rust Package)

If you have Rust installed:

cargo install pysentry

💾 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
curl -L https://github.com/nyudenkov/pysentry/releases/latest/download/pysentry-linux-x64.tar.gz | tar -xz
./pysentry-linux-x64/pysentry --help

🔧 From Source

git clone https://github.com/nyudenkov/pysentry
cd pysentry
cargo build --release

The binary will be available at target/release/pysentry.

Requirements

For uvx: Python 3.9-3.14 and uv installed
For binaries: No additional dependencies
For Python package: Python 3.9-3.14
For Rust package and source: Rust 1.79+

Platform Support

Installation Method	Linux (x64)	Linux (ARM64)	macOS (x64)	macOS (ARM64)	Windows (x64)
uvx	✅	✅	✅	✅	✅
PyPI (pip)	✅	✅	✅	✅	✅
Crates.io (cargo)	✅	✅	✅	✅	✅
GitHub Releases	✅	✅	✅	✅	✅
From Source	✅	✅	✅	✅	✅

Supported Python Versions: 3.9, 3.10, 3.11, 3.12, 3.13, 3.14 Supported Architectures: x86_64 (x64), ARM64 (aarch64)

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 install uv

# pip-tools (widely compatible, Python-based)
pip install pip-tools

Environment Requirements:

Resolvers must be available in your current environment

If using virtual environments, activate your venv before running PySentry:

source venv/bin/activate  # Linux/macOS
venv\Scripts\activate     # Windows
pysentry /path/to/project

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)
uvx pysentry-rs
uvx pysentry-rs /path/to/python/project

# Using installed binary
pysentry
pysentry /path/to/python/project

# Automatically detects project type (uv.lock, poetry.lock, Pipfile.lock, pyproject.toml, Pipfile, requirements.txt)
pysentry /path/to/project

# Force specific resolver
pysentry --resolver uv /path/to/project
pysentry --resolver pip-tools /path/to/project

# Exclude extra dependencies (only check main dependencies)
pysentry --exclude-extra

# Filter by severity (only show high and critical)
pysentry --severity high

# Output to JSON file
pysentry --format json --output audit-results.json

Advanced Usage

# Using uvx for comprehensive audit (extras included by default)
uvx pysentry-rs --format sarif --output security-report.sarif

# Use specific vulnerability sources (all sources used by default)
uvx pysentry-rs --sources pypa /path/to/project
uvx pysentry-rs --sources pypa --sources osv /path/to/project

# Generate markdown report
uvx pysentry-rs --format markdown --output security-report.md

# Control CI exit codes - only fail on critical vulnerabilities
uvx pysentry-rs --fail-on critical

# Or with installed binary (extras included by default)
pysentry --format sarif --output security-report.sarif
pysentry --sources pypa,osv --direct-only
pysentry --format markdown --output security-report.md

# Ignore specific vulnerabilities
pysentry --ignore CVE-2023-12345 --ignore GHSA-xxxx-yyyy-zzzz

# Ignore unfixable vulnerabilities (only while they have no fix available)
pysentry --ignore-while-no-fix CVE-2025-8869

# Disable caching for CI environments
pysentry --no-cache

# Verbose output for debugging
pysentry --verbose

Advanced Requirements.txt Usage

# Scan multiple requirements files
pysentry --requirements requirements.txt --requirements requirements-dev.txt

# Check only direct dependencies from requirements.txt
pysentry --direct-only --resolver uv

# Ensure resolver is available in your environment
source venv/bin/activate  # Activate your virtual environment first
pysentry /path/to/project

# Debug requirements.txt resolution
pysentry --verbose --resolver uv /path/to/project

# Use longer resolution cache TTL (48 hours)
pysentry --resolution-cache-ttl 48 /path/to/project

# Clear resolution cache before scanning
pysentry --clear-resolution-cache /path/to/project

CI/CD Integration Examples

# Development environment - only fail on critical vulnerabilities
pysentry --fail-on critical --format json --output security-report.json

# Staging environment - fail on high+ vulnerabilities
pysentry --fail-on high --sources pypa,osv --format sarif --output security.sarif

# Production deployment - strict security (fail on medium+, default)
pysentry --sources pypa,pypi,osv --format json --output prod-security.json

# Generate markdown report for GitHub issues/PRs
pysentry --format markdown --output SECURITY-REPORT.md

# Comprehensive audit with all sources and full reporting (extras included by default)
pysentry --sources pypa,pypi,osv --format json --fail-on low

# CI environment with fresh resolution cache
pysentry --clear-resolution-cache --sources pypa,osv --format sarif

# CI with resolution cache disabled
pysentry --no-resolution-cache --format json --output security-report.json

Pre-commit Integration

PySentry integrates seamlessly with pre-commit to automatically scan for vulnerabilities before commits.

Setup

Add PySentry to your .pre-commit-config.yaml:

repos:
  - repo: https://github.com/pysentry/pysentry-pre-commit
    rev: v0.3.14
    hooks:
      - id: pysentry # default pysentry settings

Advanced Configuration

repos:
  - repo: https://github.com/pysentry/pysentry-pre-commit
    rev: v0.3.14
    hooks:
      - id: pysentry
        args: ["--sources", "pypa,osv", "--fail-on", "high"]

Installation Requirements

Pre-commit will automatically install PySentry, uv and pip-tools via PyPI.

Configuration

PySentry supports TOML-based configuration files for persistent settings management. Configuration files follow a hierarchical discovery pattern:

Project-level (in current or parent directories, walking up to .git root):
- .pysentry.toml (highest priority)
- pyproject.toml [tool.pysentry] section (lower priority, convenient for existing Python projects)
User-level: ~/.config/pysentry/config.toml (Linux/macOS)
System-level: /etc/pysentry/config.toml (Unix systems)

Priority: When both .pysentry.toml and pyproject.toml exist in the same directory, .pysentry.toml takes precedence. This allows you to override pyproject.toml settings when needed.

Configuration File Example (.pysentry.toml)

version = 1

[defaults]
format = "json"
severity = "medium"
fail_on = "high"
scope = "all"
direct_only = false

[sources]
enabled = ["pypa", "osv"]

[resolver]
type = "uv"
fallback = "pip-tools"

[cache]
enabled = true
resolution_ttl = 48
vulnerability_ttl = 72

[output]
quiet = false
verbose = false
color = "auto"

[ignore]
ids = ["CVE-2023-12345", "GHSA-xxxx-yyyy-zzzz"]
while_no_fix = ["CVE-2025-8869"]

[http]
timeout = 120
connect_timeout = 30
max_retries = 3
retry_initial_backoff = 1
retry_max_backoff = 60
show_progress = true

pyproject.toml Configuration

You can configure PySentry directly in your pyproject.toml using the [tool.pysentry] section:

[project]
name = "my-project"
version = "1.0.0"

[tool.pysentry]
version = 1

[tool.pysentry.defaults]
format = "json"
severity = "medium"
fail_on = "high"
scope = "main"
direct_only = false

[tool.pysentry.sources]
enabled = ["pypa", "osv"]

[tool.pysentry.resolver]
type = "uv"
fallback = "pip-tools"

[tool.pysentry.cache]
enabled = true
resolution_ttl = 48
vulnerability_ttl = 72

[tool.pysentry.output]
quiet = false
verbose = false
color = "auto"

[tool.pysentry.ignore]
ids = ["CVE-2023-12345"]
while_no_fix = ["CVE-2025-8869"]

[tool.pysentry.http]
timeout = 120
connect_timeout = 30
max_retries = 3

Benefits of pyproject.toml configuration:

Keep all project configuration in a single file
No additional config files to manage
Works seamlessly with existing Python project tooling
Graceful fallback: Invalid [tool.pysentry] sections log a warning and continue to next configuration source

Environment Variables

Variable	Description	Example
`PYSENTRY_CONFIG`	Override config file path (supports `.pysentry.toml` or `pyproject.toml`)	`PYSENTRY_CONFIG=/path/to/pyproject.toml`
`PYSENTRY_NO_CONFIG`	Disable all config file loading	`PYSENTRY_NO_CONFIG=1`

Command Line Options

Option	Description	Default
`--format`	Output format: `human`, `json`, `sarif`, `markdown`	`human`
`--severity`	Minimum severity: `low`, `medium`, `high`, `critical`	`low`
`--fail-on`	Fail (exit non-zero) on vulnerabilities ≥ severity	`medium`
`--sources`	Vulnerability sources: `pypa`, `pypi`, `osv` (multiple)	`pypa,pypi,osv`
`--exclude-extra`	Exclude extra dependencies (dev, optional, etc)	`false`
`--direct-only`	Check only direct dependencies	`false`
`--detailed`	Show full vulnerability descriptions instead of truncated	`false`
`--ignore`	Vulnerability IDs to ignore (repeatable)	`[]`
`--ignore-while-no-fix`	Ignore vulnerabilities only while no fix is available	`[]`
`--output`	Output file path	`stdout`
`--no-cache`	Disable all caching	`false`
`--cache-dir`	Custom cache directory	Platform-specific
`--resolution-cache-ttl`	Resolution cache TTL in hours	`24`
`--no-resolution-cache`	Disable resolution caching only	`false`
`--clear-resolution-cache`	Clear resolution cache on startup	`false`
`--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 multi-tier caching system for optimal performance:

Vulnerability Data Cache

Location: {CACHE_DIR}/pysentry/vulnerability-db/
Purpose: Caches vulnerability databases from PyPA, PyPI, OSV
TTL: 24 hours (configurable per source)
Benefits: Avoids redundant API calls and downloads

Resolution Cache

Location: {CACHE_DIR}/pysentry/dependency-resolution/
Purpose: Caches resolved dependencies from uv/pip-tools
TTL: 24 hours (configurable via --resolution-cache-ttl)
Benefits: Dramatically speeds up repeated scans of requirements.txt files
Cache Key: Based on requirements content, resolver version, Python version, platform

Platform-Specific Cache Locations

Linux: ~/.cache/pysentry/
macOS: ~/Library/Caches/pysentry/
Windows: %LOCALAPPDATA%\pysentry\

Finding Your Cache Location: Run with --verbose to see the actual cache directory path being used.

Cache Features

Atomic Updates: Prevents cache corruption during concurrent access
Custom Location: Use --cache-dir to specify alternative location
Selective Clearing: Control caching behavior per cache type
Content-based Invalidation: Automatic cache invalidation on content changes

Cache Control Examples

# Disable all caching
pysentry --no-cache

# Disable only resolution caching (keep vulnerability cache)
pysentry --no-resolution-cache

# Set resolution cache TTL to 48 hours
pysentry --resolution-cache-ttl 48

# Clear resolution cache on startup (useful for CI)
pysentry --clear-resolution-cache

# Custom cache directory
pysentry --cache-dir /tmp/my-pysentry-cache

To manually clear all caches:

# Linux
rm -rf ~/.cache/pysentry/

# macOS
rm -rf ~/Library/Caches/pysentry/

# Windows (PowerShell)
Remove-Item -Recurse -Force "$env:LOCALAPPDATA\pysentry"

To clear only resolution cache:

# Linux
rm -rf ~/.cache/pysentry/dependency-resolution/

# macOS
rm -rf ~/Library/Caches/pysentry/dependency-resolution/

# Windows (PowerShell)
Remove-Item -Recurse -Force "$env:LOCALAPPDATA\pysentry\dependency-resolution"

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

Pipfile.lock Files

Full support for Pipenv lock files with exact version resolution:

Exact Version Resolution: Scans exact dependency versions locked by Pipenv
Lock-File Only Analysis: Relies purely on the lock file structure, no Pipfile parsing needed
Complete Dependency Tree: Analyzes all resolved dependencies including transitive ones
Dependency Classification: Distinguishes between default dependencies and development groups

Key Features:

No external tools required
Fast parsing with exact version information
Handles Pipenv's dependency groups (default and develop)
Perfect for Pipenv-managed projects with established lock files

Pipfile Files (External Resolution)

Support for Pipfile specification files using external dependency resolvers:

Key Features:

Dependencies Resolution: Converts version constraints from Pipfile 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
Dependency Groups: Supports both default packages and dev-packages sections
Complex Constraint Handling: Supports version ranges, Git dependencies, and environment markers

Resolution Workflow:

Detects Pipfile in your project (when Pipfile.lock is not present)
Auto-detects available resolver (uv or pip-tools) in current environment
Resolves version constraints to exact dependency versions
Scans resolved dependencies for vulnerabilities
Reports findings with dependency group classification

Note: When both Pipfile and Pipfile.lock are present, PySentry prioritizes the lock file for better accuracy. Consider using pipenv lock to generate a lock file for the most precise vulnerability scanning.

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 or pip-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
source venv/bin/activate      # Activate virtual environment
pip install uv               # Install preferred resolver
pysentry /path/to/project    # Run security scan

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 or pip-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

PySentry uses all three vulnerability sources by default for comprehensive coverage.

PyPA Advisory Database

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.

Markdown

GitHub-friendly format with structured sections and severity indicators. Perfect for documentation, GitHub issues, and security reports.

JSON

{
  "summary": {
    "total_dependencies": 245,
    "vulnerable_packages": 2,
    "total_vulnerabilities": 3,
    "by_severity": {
      "critical": 1,
      "high": 1,
      "medium": 1,
      "low": 0
    }
  },
  "vulnerabilities": [...]
}

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 from multiple sources
Multi-tier Caching: Intelligent caching for both vulnerability data and resolved dependencies
Efficient Matching: In-memory indexing for fast vulnerability lookups
Streaming: Large databases processed without excessive memory usage

Resolution Cache Performance

The resolution cache provides dramatic performance improvements for requirements.txt files:

First scan: Standard resolution time using uv or pip-tools
Subsequent scans: Near-instantaneous when cache is fresh (>90% time savings)
Cache invalidation: Automatic when requirements content, resolver, or environment changes
Content-aware: Different cache entries for different Python versions and platforms

Requirements.txt Resolution Performance

PySentry leverages external resolvers with intelligent caching:

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
Resolution caching: Eliminates repeated resolver calls for unchanged requirements

Development

Building from Source

git clone https://github.com/nyudenkov/pysentry
cd pysentry
cargo build --release

Running Tests

cargo test

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
ls pyproject.toml uv.lock poetry.lock requirements.txt

# Or specify the path explicitly
pysentry /path/to/python/project

Error: "No dependency resolver found" or "uv resolver not available"

# Install a supported resolver in your environment
pip install uv           # Recommended - fastest
pip install pip-tools    # Alternative

# Verify resolver is available
uv --version
pip-compile --version

# If using virtual environments, ensure resolver is installed there
source venv/bin/activate
pip install uv
pysentry /path/to/project

Error: "Failed to resolve requirements"

# Check your requirements.txt syntax
cat requirements.txt

# Try different resolver
pysentry --resolver pip-tools  # if uv fails
pysentry --resolver uv         # if pip-tools fails

# Ensure you're in correct environment
which python
which uv  # or which pip-compile

# Debug with verbose output
pysentry --verbose /path/to/project

Error: "Failed to fetch vulnerability data"

# Check network connectivity
curl -I https://osv-vulnerabilities.storage.googleapis.com/

# Try with different or multiple sources
pysentry --sources pypi
pysentry --sources pypa,osv

# For slow or unstable networks, increase timeout and retries
# Create/edit .pysentry.toml in your project:

[http]
timeout = 300           # 5 minute timeout
max_retries = 5         # More retry attempts
retry_max_backoff = 120 # Longer backoff delays

# Then run again
pysentry

Network timeout errors:

PySentry includes automatic retry with exponential backoff for network issues. If you still experience timeouts:

# Increase timeout values in config
pysentry config init --output .pysentry.toml
# Edit .pysentry.toml and adjust [http] section

Rate limiting (HTTP 429 errors):

PySentry automatically handles rate limiting. If rate limits persist:

[http]
max_retries = 5              # More attempts
retry_initial_backoff = 5    # Longer initial wait
retry_max_backoff = 300      # Up to 5 minute backoff

Slow requirements.txt resolution

# Use faster uv resolver instead of pip-tools
pysentry --resolver uv

# Install uv for better performance (2-10x faster)
pip install uv

# Or use uvx for isolated execution
uvx pysentry-rs --resolver uv /path/to/project

Requirements.txt files not being detected

# Ensure requirements.txt exists
ls requirements.txt

# Specify path explicitly
pysentry /path/to/python/project

# Include additional requirements files
pysentry --requirements requirements-dev.txt --requirements requirements-test.txt

# Check if higher-priority files exist (they take precedence)
ls uv.lock poetry.lock Pipfile.lock pyproject.toml Pipfile requirements.txt

Performance Issues

# Clear all caches and retry
rm -rf ~/.cache/pysentry      # Linux
rm -rf ~/Library/Caches/pysentry  # macOS
pysentry

# Clear only resolution cache (if vulnerability cache is working)
rm -rf ~/.cache/pysentry/dependency-resolution/      # Linux
rm -rf ~/Library/Caches/pysentry/dependency-resolution/  # macOS
pysentry

# Clear resolution cache via CLI
pysentry --clear-resolution-cache

# Use verbose mode to identify bottlenecks
pysentry --verbose

# Disable caching to isolate issues
pysentry --no-cache

Resolution Cache Issues

# Clear stale resolution cache after environment changes
pysentry --clear-resolution-cache

# Disable resolution cache if causing issues
pysentry --no-resolution-cache

# Extend cache TTL for stable environments
pysentry --resolution-cache-ttl 168  # 1 week

# Check cache usage with verbose output
pysentry --verbose  # Shows cache hits/misses

# Force fresh resolution (ignores cache)
pysentry --clear-resolution-cache --no-resolution-cache

Acknowledgments

Inspired by pip-audit and uv #9189 issue
Originally was a command for uv
Vulnerability data from PyPA, PyPI, and OSV.dev

pysentry 0.3.14

🐍 PySentry

Overview

Key Features

Installation

⚡ Via uvx (Recommended for occasional use)

📦 From PyPI (Python Package)

⚡ From Crates.io (Rust Package)

💾 From GitHub Releases (Pre-built Binaries)

🔧 From Source

Requirements

Platform Support

CLI Command Names

Requirements.txt Support Prerequisites

Quick Start

Basic Usage

Advanced Usage

Advanced Requirements.txt Usage

CI/CD Integration Examples

Pre-commit Integration

Setup

Advanced Configuration

Installation Requirements

Configuration

Configuration File Example (.pysentry.toml)

pyproject.toml Configuration

Environment Variables

Command Line Options

Cache Management

Vulnerability Data Cache

Resolution Cache

Platform-Specific Cache Locations

Cache Features

Cache Control Examples

Supported Project Formats

uv.lock Files (Recommended)

poetry.lock Files

Pipfile.lock Files

Pipfile Files (External Resolution)

requirements.txt Files (External Resolution)

pyproject.toml Files (External Resolution)

Vulnerability Data Sources

PyPA Advisory Database

PyPI JSON API

OSV.dev

Output Formats

Human-Readable (Default)

Markdown

JSON

SARIF (Static Analysis Results Interchange Format)

Performance

Resolution Cache Performance

Requirements.txt Resolution Performance

Development

Building from Source

Running Tests

Project Structure

Troubleshooting

Common Issues

Acknowledgments