security-review

Identify security vulnerabilities in codebases by tracing data flows and component interactions.

Updated Mar 31, 2026

Search Tags:#code analysis #code audit #security scanning #vulnerability detection #AI-powered

Ready to run

npx skills add https://github.com/TKlerx/webapp-template --skill security-review-tklerx

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: security-review
Source: https://github.com/TKlerx/webapp-template/tree/main/.agents/skills/security-review
Command: npx skills add https://github.com/TKlerx/webapp-template --skill security-review-tklerx

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pypdf, pdfplumber, pdf2image, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the need for a comprehensive, AI-powered codebase security scanner that can quickly identify vulnerabilities that may be missed by traditional tools.

Core Features & Use Cases

AI-Powered Security Scanning: Identifies common and complex security issues in code.
Code Understanding: Analyzes code like a human, understanding context and intent.
Vulnerability Analysis: Scans for SQL injection, XSS, command injection, and more.
Use Case: When a developer needs to perform a security audit on a new codebase or during the development process.

Quick Start

Use the security-review skill to scan your project's codebase for security vulnerabilities.

Frequently Asked Questions about security-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I scan my codebase for security vulnerabilities like SQL injection and XSS?▼

To scan a codebase for security vulnerabilities like SQL injection and XSS, you can use an AI-powered security scanner that traces data flows and understands component interactions. This approach identifies complex issues often missed by traditional automated tools.

What is AI-powered code analysis and how does it detect vulnerabilities?▼

AI-powered code analysis detects vulnerabilities by reasoning about code like a human security researcher. It understands context and intent, traces data flows across components, and catches complex security issues that traditional pattern-matching scanners might miss.

Do I need Python libraries to run an AI-powered code audit?▼

Yes, you need Python libraries such as pypdf, pdfplumber, and pdf2image to run this AI-powered code audit. The security analysis process also relies on accessing external tools and environments like databases and file systems.

Can I use vulnerability detection during the development process instead of waiting for a final audit?▼

Yes, you can use AI-powered vulnerability detection during the active development process. It functions effectively for continuous security scanning, allowing developers to identify and resolve vulnerabilities in new codebases before a final audit.

Why does AI-powered security scanning catch vulnerabilities that traditional tools miss?▼

AI-powered security scanning catches missed vulnerabilities because it analyzes code context and developer intent rather than relying solely on static patterns. By tracing data flows and understanding component interactions, it identifies complex security issues.

What are the limitations of using AI for vulnerability detection in a codebase?▼

Limitations of using AI for vulnerability detection include its reliance on external tools like databases and file systems for full codebase context. Additionally, processing requires specific Python libraries and may involve complex setup for comprehensive security analysis.