Safe Pkgs
A tool for AI agents to check the security of software packages before installation, providing allow/deny decisions, risk scores, and audit logs
rating : 2.5 points
downloads : 6.9K
What is safe-pkgs?
safe-pkgs is a package security checking tool specifically designed for AI agents. When an AI agent attempts to install a software package, safe-pkgs automatically checks the package's security before installation, evaluates the risk level, and provides a clear allow or deny decision. It's like an intelligent security guard, ensuring that the AI does not install risky dependency packages.How to use safe-pkgs?
Using safe-pkgs is very simple: First, install the Rust binary, and then run it as an MCP server. AI agents (such as Claude Desktop) will automatically call safe-pkgs for checks before installing packages. You can also use the command-line tool to perform a one-time security audit on an existing project.Applicable scenarios
safe-pkgs is particularly suitable for the following scenarios: When AI-driven code assistants automatically add dependencies; Package security checks in CI/CD pipelines; When development teams want to ensure the security of dependency packages; When auditing the dependency risks of existing projects.Main features
Pre-installation security check
Automatically perform a security check before the AI agent installs any software package to prevent the installation of risky dependencies.
Intelligent risk scoring
Automatically calculate the risk level (low/medium/high/severe) based on multiple factors such as the package's age, download volume, and security announcements.
Multi-registry support
Supports the three major mainstream package managers, npm, crates.io, and PyPI, covering the JavaScript, Rust, and Python ecosystems.
Local cache mechanism
Use SQLite for local caching to reduce repeated network requests and improve the checking speed.
Complete audit log
Record all check decisions and provide a complete audit trail for post-hoc analysis and review.
No subscription required
Completely free to use, no paid plans, hosted accounts, or API keys are needed. All checks are performed locally.
Lock file audit
Supports batch security checks on the entire package-lock.json, Cargo.lock, or requirements.txt files.
Dependency relationship tracking
Display the dependency path of the package to help understand the source of indirect dependencies and the risk propagation path.
Advantages
Completely free and open source, no usage restrictions
Runs locally to protect privacy and data security
Seamlessly integrates with mainstream AI tools (such as Claude Desktop)
Provides clear decision-making basis and risk explanations
Supports both command-line and MCP server usage modes
Flexible configuration, supports global and project-level configurations
Limitations
Relies on the AI agent to actively call, cannot force the AI to use it
Currently only supports npm, crates.io, and PyPI, does not support other package managers
Requires a Rust environment to compile and run
For large projects, the first audit may be slow
Cannot check packages in private registries
How to use
Install safe-pkgs
Install the safe-pkgs binary using the Cargo package manager.
Run the MCP server
Start safe-pkgs as an MCP server for AI agents to call.
Configure AI tools
Configure the MCP server connection in AI tools such as Claude Desktop.
Perform a security check
The AI agent will automatically call safe-pkgs for checks when installing packages.
Usage examples
Security check when an AI assistant adds dependencies
When an AI code assistant (such as Claude) suggests installing the lodash package, safe-pkgs will automatically check the risk level of the package. If it finds that the lodash version is too old or has security vulnerabilities, it will block the installation and provide detailed reasons.
Batch audit of project dependencies
Before submitting code, developers use safe-pkgs to perform a security check on all dependencies of the project to discover potential security risks.
CI/CD pipeline integration
Integrate safe-pkgs into the continuous integration pipeline to automatically check the security of dependencies before each build, preventing risky packages from entering the production environment.
Frequently Asked Questions
Can safe-pkgs guarantee that AI agents will definitely use it?
Does safe-pkgs require an internet connection?
How to configure the allow list and deny list?
How to use it on Windows?
What happens when the check fails?
Does it support private registries?
Related resources
Official documentation
Complete configuration guide, API reference, and development documentation
GitHub repository
Source code, issue tracking, and contribution guidelines
GitHub Action
GitHub Actions integration for CI/CD pipelines
Configuration specification document
Detailed configuration file specification and option description
MCP protocol document
Official specification of the Model Context Protocol

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