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-reviewor/security-review <path>
How This Skill Works
Unlike traditional static analysis tools that match patterns, this skill:
- Reads code like a security researcher — understanding context, intent, and data flow
- Traces across files — following how user input moves through your application
- Self-verifies findings — re-examines each result to filter false positives
- Assigns severity ratings — CRITICAL / HIGH / MEDIUM / LOW / INFO
- Proposes targeted patches — every finding includes a concrete fix
- 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.mdto 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.jsonfor 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.mdfor 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
.envfiles 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.mdfor 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:
- Re-read the relevant code with fresh eyes
- Ask: "Is this actually exploitable, or is there sanitization I missed?"
- Check if a framework or middleware already handles this upstream
- Downgrade or discard findings that aren't genuine vulnerabilities
- 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