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Security Review Openai

Checked
lawvable·vlatest·ai-ml

Helps with security, code review, OpenAI as part of building AI and machine learning applications 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 lawve-ai/awesome-legal-skills --skill security-review-openai -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

lawvable

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 lawvable/awesome-legal-skills at 180fd1582c.

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

Commit
180fd1582c
Manifest
skills/code-security-review-openai/SKILL.md
Scanned
13 files, 9,053 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 leverages OpenAI's capabilities to perform a security review of provided text, identifying potential vulnerabilities and risks. It can analyze code snippets, configuration files, or even natural language descriptions of systems for common security flaws. The output includes categorized findings with severity levels to prioritize remediation efforts.

When to use it

  • Code Review: Quickly scan newly written code for potential injection flaws or insecure practices before deployment.
  • Configuration Analysis: Evaluate cloud infrastructure configurations (e.g., Terraform, AWS CloudFormation) for misconfigurations that could lead to security breaches.
  • Policy Assessment: Check internal policies and procedures against established security best practices.
  • Threat Modeling Input: Generate a preliminary list of potential threats based on a system description.

Key capabilities

  • Vulnerability identification
  • Severity level assessment (e.g., High, Medium, Low)
  • Categorized findings (e.g., Injection, Authentication, Authorization)
  • Analysis of code snippets and configuration files
  • Natural language processing for policy review

Example prompts

  • "Review the following Python code snippet for security vulnerabilities: [code snippet]"
  • "Analyze this Terraform configuration file for potential misconfigurations: [Terraform code]"
  • "Assess this company's data retention policy against common privacy regulations."

Tips & gotchas

The quality of the review depends on the clarity and completeness of the input provided. While helpful, always supplement AI-generated security reviews with human expert analysis for critical systems.