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github/awesome-copilot/skills/security-review/SKILL.md

security-review

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", "audi

Source repository stars
37,126
Declared platforms
0
Static risk flags
2
Last source update
2026-07-28
Source checked
2026-07-28

Decision brief

What it does—and where it fits

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.

Best for

  • 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

Not for

  • Tasks that require unconfirmed production actions or broad system permissions.
  • Environments where the pinned source and install steps cannot be inspected.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/github/awesome-copilot --skill "skills/security-review"
Safe inspection promptEditorial

Inspect the Agent Skill "security-review" from https://github.com/github/awesome-copilot/blob/9933dcad5be5caeb288cebcd370eeeb2fc2f1685/skills/security-review/SKILL.md at commit 9933dcad5be5caeb288cebcd370eeeb2fc2f1685. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    Execution Workflow

    Follow these steps in order every time:

    If a path was provided (/security-review src/auth/), scan only that scopeIf no path given, scan the entire project starting from the rootIdentify the language(s) and framework(s) in use (check package.json, requirements.txt,
  2. 02

    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, po…

    If a path was provided (/security-review src/auth/), scan only that scopeIf no path given, scan the entire project starting from the rootIdentify the language(s) and framework(s) in use (check package.json, requirements.txt,
  3. 03

    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:…

    Node.js: Check package.json + package-lock.json for known vulnerable packagesPython: Check requirements.txt / pyproject.toml / PipfileJava: Check pom.xml / build.gradle
  4. 04

    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 st…

    Hardcoded API keys, tokens, passwords, private keys.env files accidentally committedSecrets in comments or debug logs
  5. 05

    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.

    SQL Injection: raw queries with string interpolation, ORM misuse, second-order SQLiXSS: unescaped output, dangerouslySetInnerHTML, innerHTML, template injectionCommand Injection: exec/spawn/system with user input

Permission review

Static risk signals and limitations

Reads files

low · line 19

The documentation asks the agent to read local files, directories, or repositories.

Any request phrasing like "is my code secure?", "scan this file", or "check my repo for vulnerabilities"

Network access

medium · line 157

The documentation includes network, browsing, or remote request actions.

Search patterns: `API key`, `token`, `private key`, `connection string`, `entropy`, `.env`, `GitHub Actions`, `Docker`, `Terraform`

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score88/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars37,126SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
github/awesome-copilot
Skill path
skills/security-review/SKILL.md
Commit
9933dcad5be5caeb288cebcd370eeeb2fc2f1685
License
MIT
Collected
2026-07-28
Default branch
main
View the original SKILL.md

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

SeverityMeaningExample
🔴 CRITICALImmediate exploitation risk, data breach likelySQLi, RCE, auth bypass
🟠 HIGHSerious vulnerability, exploit path existsXSS, IDOR, hardcoded secrets
🟡 MEDIUMExploitable with conditions or chainingCSRF, open redirect, weak crypto
🔵 LOWBest practice violation, low direct riskVerbose errors, missing headers
⚪ INFOObservation worth noting, not a vulnerabilityOutdated 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

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