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Securing Ai Generated Code

Listed
chrbailey·vlatest·security·MIT

Automates code review & vulnerability scanning of AI-generated code to ensure security best practices are followed.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add chrbailey/agent-security-skills --skill securing-ai-generated-code -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

chrbailey

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No credential access: failed

    Touches credential material in 1 place.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

    What it found

    • skills/securing-ai-generated-code/references/vulnerability-patterns.md:30AWS credentials file
      # Uses AWS credential chain: env vars -> ~/.aws/credentials -> IAM role

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned chrbailey/agent-security-skills at 312b94862a.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
312b94862a
Manifest
skills/securing-ai-generated-code/SKILL.md
Scanned
2 files, 893 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill helps AI agents identify and mitigate common security vulnerabilities in code generated by other AI models. It can analyze the code for potential issues like SQL injection, cross-site scripting (XSS), and insecure dependencies. The goal is to produce more robust and secure applications built with AI assistance.

When to use it

  • Automated Code Review: Integrate this skill into your CI/CD pipeline to automatically scan AI-generated code for vulnerabilities before deployment.
  • Security Training for Agents: Use the skill to teach an agent about common coding errors and how to avoid them during generation.
  • Rapid Prototyping Security: When quickly generating code prototypes, use this skill to identify potential security risks early in the development process.
  • Reducing Technical Debt: Retroactively analyze existing AI-generated codebases to find and fix vulnerabilities that might have been missed initially.

Key capabilities

  • Vulnerability scanning for SQL injection
  • Cross-site scripting (XSS) detection
  • Insecure dependency identification

Example prompts

  • "Analyze this Python script for potential security vulnerabilities: [code snippet]"
  • "Review the following JavaScript code and identify any XSS risks: [code snippet]"
  • "Can you check this generated SQL query for injection flaws? [query]"

Tips & gotchas

The skill's effectiveness depends on the quality of the AI-generated code; it may not catch all vulnerabilities. It is recommended to combine this skill with other security best practices and manual review processes.