I've released the AI Vulnerability Scanner CLI, a new tool for integrating AI models into your code review process. This is a Python script that provides a command-line interface for scanning code files.
The scanner is designed to work with AI models to help identify potential vulnerabilities in your codebase. The intent is to offer a way to get an initial scan for common issues by leveraging AI, directly from your terminal.
It's built for developers who want to add an AI-powered check to their workflow without needing a complex setup. The CLI focuses on providing a straightforward method to pass code files to an AI model for a vulnerability assessment.
This tool is not a replacement for thorough security audits but serves as an additional layer for early detection of potential problems. It can be integrated into development pipelines for quick checks or used manually on specific files.
Top comments (1)
Interesting. As someone who does a fair bit of manual code review and pentesting, I’ve played with a few AI-assisted scanners. They tend to be decent at surface-level patterns (hardcoded secrets, unsafe deserialization signatures) but fall over on logic bugs or multi-step chains — exactly the kind of thing an attacker chains together. What's your experience been with false positives vs. false negatives so far? I’d be curious how it handles context across files, since most real-world vulns I find aren’t in a single function.
Also, the CLI approach is neat for quick local checks. Have you thought about shipping it as a pre-commit hook? If it runs in under a second, that’s where it’d really shine without breaking developer flow.