AI-powered codebase security scanner that reasons about code like a security researcher — tracing data flows, understanding component interactions, and catching vulnerabilities that pattern-matching tools miss. Use this skill when asked to scan code for security vulnerabilities, find bugs, check for SQL injection, XSS, command injection, exposed API keys, hardcoded secrets, insecure dependencies, access control issues, or any request like "is my code secure?", "review for security issues…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Security Review
An AI-powered security scanner that reasons about your codebase the way a human security
researcher would — tracing data flows, understanding component interactions, and catching
vulnerabilities that pattern-matching tools miss.
## When to Use This Skill
Use this skill when the request involves:
- Scanning a codebase or file for security vulnerabilities
- Running a security review or vulnerability check
- Checking for SQL injection, XSS, command injection, or other injection flaws
- Finding exposed API keys, hardcoded secrets, or credentials in code
- Auditing dependencies for known CVEs
- Reviewing authentication, authorization, or access control logic
- Detecting insecure cryptography or weak randomness
- Performing a data flow analysis to trace user input to dangerous sinks
- Any request phrasing like "is my code secure?", "scan this file", or "check my repo for vulnerabilities"
- Running `/security-review` or `/security-review <path>`
## How This Skill Works
Unlike traditional static analysis tools that match patterns, this skill:
1. **Reads code like a security researcher** — understanding context, intent, and data flow
…
The line at the top of this page pins the label git:20260828.866dec6, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
A 17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
pass: Frontmatter block present
pass: Frontmatter declares a name
pass: Frontmatter declares a description
pass: Size between 200 bytes and 200 KB (9094 bytes)
pass: No zero-width or bidi control characters
pass: No instruction hidden inside an HTML comment
pass: No link to an exfiltration or paste host
pass: No credential-shaped string
pass: No instruction to send local credentials anywhere
pass: No text hidden with inline styles
pass: No prompt-injection phrasing
pass: No curl or wget piped into a shell
pass: No recursive delete of root, home or parent
pass: No instruction to read or print local credentials
pass: No base64 blob over 200 characters
pass: No link to a raw IP address
pass: No script tag
Source
GitHub
okhp3/skillz · 3 stars · license MIT · pushed 2026-11-06 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_tswnayi5zngkfbtw
GET https://markdownregistry.com/api/v1/resolve?ref=okhp3/skillz/security-review
GET https://markdownregistry.com/api/v1/blob/002392d88637b89e4cbc409a0531834970937f3b57c0b448a17e04b5ca6d356c
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
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