security-review

作者: github

基于AI的代码库安全扫描器,像安全研究员一样推理代码——追踪数据流、理解组件交互,并…

npx skills add https://github.com/github/awesome-copilot --skill security-review

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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