github/awesome-copilot

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

88CollectingReads filesNetwork access
See how to use itView GitHub source
npx skills add https://github.com/github/awesome-copilot --skill "skills/security-review"

Quick start

Start using it in three steps

Install it or open the source, trigger it with a clear task, then follow the source workflow.

1

Install the Skill

npx skills add https://github.com/github/awesome-copilot --skill "skills/security-review"
2

Describe the task

Use security-review to help me with: [describe your task]. Before you begin, tell me what input you need, the steps you will follow, and the expected output.

3

Follow the workflow

No structured workflow was detected; follow the original SKILL.md below.

Continue to the workflow

Direct answers

Answers to review before you install

What is 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. ", "review for security issues", "audi

Who should use security-review?

It is relevant to workflows involving Data analysis, Engineering, Operations, Research.

How do you install security-review?

SkillSignal detected this source-specific command: npx skills add https://github.com/github/awesome-copilot --skill "skills/security-review". Inspect the repository and command before running it.

Which Agent platforms does it support?

The upstream source does not declare a dedicated Agent platform.

What permissions or risks should you review?

Static analysis detected read-files, network signals. Review the cited source lines before installing; these signals are not a security audit.

What are the current evidence limits?

This page combines upstream documentation with deterministic repository, quality, and static-risk signals. It is not described as a manual test or security review.

SkillSignal brief

Decide whether it fits your work first

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. ", "review for security issues", "audi

Useful in these contexts

Not yet included in a workflow collection

Core capabilities

Data analysisEngineeringOperationsResearchPython

Distilled from the source

Understand this Skill in one minute

About 6 min · 7 sections

When it is worth using

  1. Scanning a codebase or file for security vulnerabilities

  2. Running a security review or vulnerability check

  3. Checking for SQL injection, XSS, command injection, or other injection flaws

  4. Finding exposed API keys, hardcoded secrets, or credentials in code

Repository stars
37,126
Repository forks
4,654
Quality
88/100
Source repository last pushed

Quality breakdown

Based on traceable docs and repository signals; stars are not treated as quality.

88/100
Documentation24/30
Specificity25/25
Maintenance18/20
Trust signals21/25

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View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 6 min

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
Skill path
skills/security-review/SKILL.md
Commit SHA
9933dcad5be5
Repository license
MIT
Data collected