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Python Security Scanner

Checked
jorgealves·vlatest·backend·GPL-3.0

Helps with Python, security as part of developing backend services and APIs workflows.

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 jorgealves/agent_skills --skill python-security-scanner -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

jorgealves

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 passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • 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 credential access: passed

    Reads no keys, tokens, keychains or credential files.

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

  • 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 jorgealves/agent_skills at 85014ad37d.

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

Commit
85014ad37d
Manifest
python-security-scanner/SKILL.md
Scanned
2 files, 50 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 enables AI agents to execute Python-based security scanning tasks directly within their environment. It automates the detection of vulnerabilities in codebases, infrastructure configurations, and dependencies using standard Python security libraries.

When to use it

  • Before deploying a new microservice to production to verify dependency integrity.
  • During a CI/CD pipeline stage to block builds containing known critical CVEs.
  • When auditing legacy monolithic applications for outdated cryptographic implementations.
  • To quickly assess the security posture of third-party integrations before connecting them to internal networks.

Key capabilities

  • Executes Python scripts designed for vulnerability assessment and penetration testing.
  • Integrates with popular open-source security tools like bandit, safety, and pip-audit.
  • Generates structured reports on identified risks, severity levels, and remediation steps.
  • Supports scanning of various file types including source code, Dockerfiles, and configuration files.

Example prompts

  • "Scan the current repository for any hardcoded secrets or API keys using Python security tools."
  • "Run a dependency check on our backend service to identify packages with known vulnerabilities rated high or critical."
  • "Analyze the provided Dockerfile for potential container escape vectors and insecure image configurations."

Tips & gotchas

Ensure the AI agent has read access to the target codebase and necessary permissions to execute scripts. False positives are common in automated scanning; always manually verify flagged issues before applying fixes.