Skills github awesome-copilot

security-review

Use it when:
You ask "is my code secure?", or want a project or one folder audited for vulnerabilities, leaked secrets and risky dependencies.
It does:
Audits dependencies, scans every file for secrets, reasons through the code for injection, access control, data handling, crypto and logic flaws, then traces input across files.
You get:
A report led by counts per severity, findings grouped by category with file, line, confidence and plain-English risk, and patches for critical and high ones.
Won't:
Apply any patch: it says nothing has been changed yet.
Covers:
JavaScript, TypeScript, Python, Java, PHP, Go, Ruby and Rust, with bundled pattern guides and a watchlist of vulnerable packages.
Unlike Sentry's security-review:
That one reports only high-confidence exploitable findings; this one reports every severity down to info, each with a confidence rating.

TL;DR

Run as /security-review, optionally with a path, it scans that scope or the whole project in eight steps. It identifies the languages and frameworks from manifests such as package.json or go.mod and loads matching vulnerability patterns. It audits dependencies first against a curated CVE watchlist, then scans all files, including config, CI, Dockerfiles and infrastructure code, for hardcoded keys, committed .env files and credentials in connection strings, using regex and entropy patterns. The deep scan reasons about the code rather than matching patterns: SQL, command and other injection, XSS, missing authentication, IDOR, JWT and CSRF weaknesses, sensitive data in logs, path traversal, SSRF, weak cryptography and randomness, race conditions and missing rate limits. A cross-file pass follows user input from HTTP parameters and uploads to queries, exec calls and HTML output. It then re-reads each finding to drop false positives and sets a final severity, from critical to info. The report follows a bundled template, and every critical and high finding gets a before-and-after patch in your code's style, with a comment explaining the fix. If the code is clean, it says so and what it scanned.

Summarizes the skill at 797337f.

npx skills add https://github.com/github/awesome-copilot --skill security-review
Total Downloads
5,800 on skills.sh, Nov 9, 2026
Repo stars
40,943 github/awesome-copilot
First seen
Mar 30, 2026 on skills.sh
Weekly Downloads
99
0% over the 8 weeks to Nov 9
Weekly values
Week toInstalls
Sep 2199
Sep 2883
Oct 5102
Oct 1296
Oct 1974
Oct 2695
Nov 2112
Nov 999
Category

Compliance, guardrails, skill vetting and browser fingerprinting.

Find root causes, review code and test what you built.

Everything for building software: planning, coding, debugging, design, frameworks, cloud, agents and skills.

Type

A multi-step process the agent follows: interview, debug, run a TDD loop, review.

Effect

Adds no side effects of its own. It shapes how the agent thinks, writes or reviews. Guidelines and routers are always effect:none, even when the task they support edits code.

Needs

Instructions only. Works in any agent that supports skills.

Publisher

A verified publisher on skills.sh, or the company or maintainer behind the product the skill operates.

Topics

SKILL.md

From github/awesome-copilot at 797337f. Checked daily, last changed Nov 6, 2026.

Frontmatter
name: security-review
description: '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", "audit this codebase", or "check for vulnerabilities". Covers injection flaws, authentication and access control bugs, secrets exposure, weak cryptography, insecure dependencies, and business logic issues across JavaScript, TypeScript, Python, Java, PHP, Go, Ruby, and Rust.'

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
  2. Traces across files — following how user input moves through your application
  3. Self-verifies findings — re-examines each result to filter false positives
  4. Assigns severity ratings — CRITICAL / HIGH / MEDIUM / LOW / INFO
  5. Proposes targeted patches — every finding includes a concrete fix
  6. Requires human approval — nothing is auto-applied; you always review first

Execution Workflow

Follow these steps in order every time:

Step 1 — Scope Resolution

Determine what to scan:

  • If a path was provided (/security-review src/auth/), scan only that scope
  • If no path given, scan the entire project starting from the root
  • Identify the language(s) and framework(s) in use (check package.json, requirements.txt, go.mod, Cargo.toml, pom.xml, Gemfile, composer.json, etc.)
  • Read references/language-patterns.md to load language-specific vulnerability patterns
Step 2 — Dependency Audit

Before scanning source code, audit dependencies first (fast wins):

  • Node.js: Check package.json + package-lock.json for known vulnerable packages
  • Python: Check requirements.txt / pyproject.toml / Pipfile
  • Java: Check pom.xml / build.gradle
  • Ruby: Check Gemfile.lock
  • Rust: Check Cargo.toml
  • Go: Check go.sum
  • Flag packages with known CVEs, deprecated crypto libs, or suspiciously old pinned versions
  • Read references/vulnerable-packages.md for a curated watchlist
Step 3 — Secrets & Exposure Scan

Scan ALL files (including config, env, CI/CD, Dockerfiles, IaC) for:

  • Hardcoded API keys, tokens, passwords, private keys
  • .env files accidentally committed
  • Secrets in comments or debug logs
  • Cloud credentials (AWS, GCP, Azure, Stripe, Twilio, etc.)
  • Database connection strings with credentials embedded
  • Read references/secret-patterns.md for regex patterns and entropy heuristics to apply
Step 4 — Vulnerability Deep Scan

This is the core scan. Reason about the code — don't just pattern-match. Read references/vuln-categories.md for full details on each category.

Injection Flaws

  • SQL Injection: raw queries with string interpolation, ORM misuse, second-order SQLi
  • XSS: unescaped output, dangerouslySetInnerHTML, innerHTML, template injection
  • Command Injection: exec/spawn/system with user input
  • LDAP, XPath, Header, Log injection

Authentication & Access Control

  • Missing authentication on sensitive endpoints
  • Broken object-level authorization (BOLA/IDOR)
  • JWT weaknesses (alg:none, weak secrets, no expiry validation)
  • Session fixation, missing CSRF protection
  • Privilege escalation paths
  • Mass assignment / parameter pollution

Data Handling

  • Sensitive data in logs, error messages, or API responses
  • Missing encryption at rest or in transit
  • Insecure deserialization
  • Path traversal / directory traversal
  • XXE (XML External Entity) processing
  • SSRF (Server-Side Request Forgery)

Cryptography

  • Use of MD5, SHA1, DES for security purposes
  • Hardcoded IVs or salts
  • Weak random number generation (Math.random() for tokens)
  • Missing TLS certificate validation

Business Logic

  • Race conditions (TOCTOU)
  • Integer overflow in financial calculations
  • Missing rate limiting on sensitive endpoints
  • Predictable resource identifiers
Step 5 — Cross-File Data Flow Analysis

After the per-file scan, perform a holistic review:

  • Trace user-controlled input from entry points (HTTP params, headers, body, file uploads) all the way to sinks (DB queries, exec calls, HTML output, file writes)
  • Identify vulnerabilities that only appear when looking at multiple files together
  • Check for insecure trust boundaries between services or modules
Step 6 — Self-Verification Pass

For EACH finding:

  1. Re-read the relevant code with fresh eyes
  2. Ask: "Is this actually exploitable, or is there sanitization I missed?"
  3. Check if a framework or middleware already handles this upstream
  4. Downgrade or discard findings that aren't genuine vulnerabilities
  5. Assign final severity: CRITICAL / HIGH / MEDIUM / LOW / INFO
Step 7 — Generate Security Report

Output the full report in the format defined in references/report-format.md.

Step 8 — Propose Patches

For every CRITICAL and HIGH finding, generate a concrete patch:

  • Show the vulnerable code (before)
  • Show the fixed code (after)
  • Explain what changed and why
  • Preserve the original code style, variable names, and structure
  • Add a comment explaining the fix inline

Explicitly state: "Review each patch before applying. Nothing has been changed yet."

Severity Guide

Severity Meaning Example
🔴 CRITICAL Immediate exploitation risk, data breach likely SQLi, RCE, auth bypass
🟠 HIGH Serious vulnerability, exploit path exists XSS, IDOR, hardcoded secrets
🟡 MEDIUM Exploitable with conditions or chaining CSRF, open redirect, weak crypto
🔵 LOW Best practice violation, low direct risk Verbose errors, missing headers
⚪ INFO Observation worth noting, not a vulnerability Outdated dependency (no CVE)

Output Rules

  • Always produce a findings summary table first (counts by severity)
  • Never auto-apply any patch — present patches for human review only
  • Always include a confidence rating per finding (High / Medium / Low)
  • Group findings by category, not by file
  • Be specific — include file path, line number, and the exact vulnerable code snippet
  • Explain the risk in plain English — what could an attacker do with this?
  • If the codebase is clean, say so clearly: "No vulnerabilities found" with what was scanned

Reference Files

For detailed detection guidance, load the following reference files as needed:

  • references/vuln-categories.md — Deep reference for every vulnerability category with detection signals, safe patterns, and escalation checkers
    • Search patterns: SQL injection, XSS, command injection, SSRF, BOLA, IDOR, JWT, CSRF, secrets, cryptography, race condition, path traversal
  • references/secret-patterns.md — Regex patterns, entropy-based detection, and CI/CD secret risks
    • Search patterns: API key, token, private key, connection string, entropy, .env, GitHub Actions, Docker, Terraform
  • references/language-patterns.md — Framework-specific vulnerability patterns for JavaScript, Python, Java, PHP, Go, Ruby, and Rust
    • Search patterns: Express, React, Next.js, Django, Flask, FastAPI, Spring Boot, PHP, Go, Rails, Rust
  • references/vulnerable-packages.md — Curated CVE watchlist for npm, pip, Maven, Rubygems, Cargo, and Go modules
    • Search patterns: lodash, axios, jsonwebtoken, Pillow, log4j, nokogiri, CVE
  • references/report-format.md — Structured output template for security reports with finding cards, dependency audit, secrets scan, and patch proposal formatting
    • Search patterns: report, format, template, finding, patch, summary, confidence