security-review
Skill0 starsChanged 6 months agoMITView on GitHub
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.
- Reads credentials
195 other projects use a version of this, 2 of them edited; 1 new project in the last 4 weeks, against 0 the 4 before.
Adopted by
Surging: 1 new project took it in the last 4 weeks, none the 4 weeks before.thin data
Most recently taken up by
- AOSSIE-Org/Resonate-Websitetheir own version, first seen Nov 9, 2026
- dimastriann/odoo-erp-mcptheir own version, first seen Nov 8, 2026
- ksprashu/agent-skill-forgetheir own version, first seen Nov 8, 2026
- enes-alatas/spooltheir own version, first seen Nov 8, 2026
- sgaabdu4/appwrite-backendtheir own version, first seen Nov 8, 2026
- AndersonAndrad/skillstheir own version, first seen Nov 8, 2026
Used with
Projects with it also use linkerd-patterns, dependency-cve-sweep and 10 more.
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Other versions195 projects use a version of this.
Word for word · 6
- github/awesome-copilot★ 41k100% same
- docdyhr/simplenote-mcp-server★ 21100% same
- Adhamxon/claude-code-skills★ 2100% same
- BlueChonk/BlueChonk-skills★ 1100% same
- amrmrkjr/m3j-workspace★ 0100% same
- ReaperOAK/ForgeOS★ 0100% same
Edited · 2
- PracticalSwan/agent-skills★ 2276% same
- MarieLynneBlock/arcanum-artifex★ 499% same
Wrote their own version · 187
- affaan-m/ECC★ 246ksame name
- langfuse/langfuse★ 37ksame name
- nearai/ironclaw★ 13ksame name
- joe-bell/cva★ 6.9ksame name
- doorkeeper-gem/doorkeeper★ 5.5ksame name
- github/squad★ 3.4ksame name
- compozy/compozy★ 2.9ksame name
- getsentry/sentry-python★ 2.2ksame name
- trycompai/comp★ 2.1ksame name
- xu-xiang/everything-claude-code-zh★ 1.9ksame name
177 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository14 other files it gives its agents.
- AGENTS.mdAGENTS.md
- template/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- template/CLAUDE.mdCLAUDE.md
- .github/copilot-instructions.mdCopilot instructions
- acquire-codebase-knowledgeSkill
- agent-governanceSkill
- bootstrap-prompt-builderSkill
- code-tourSkill
- doublecheckSkill
- mcp-security-auditSkill
- quality-playbookSkill
- security-auditSkill
- suggest-awesome-github-copilot-skillsSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
23 rules. 0 are common, 11 are distinctive, and 12 are very specific to this project.
0
Common
Most of the 164 edited versions we read keep these.
11
Distinctive
This author's own choices. Worth a look.
12
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 14
Use this skill when the request involves:
- Distinctive: line 39
Follow these steps in order every time:
- Very specific: line 43
If a path was provided (/security-review src/auth/), scan only that scope
- Distinctive: line 44
If no path given, scan the entire project starting from the root
- Very specific: line 47
Read references/language-patterns.md to load language-specific vulnerability patterns
- Distinctive: line 50
Before scanning source code, audit dependencies first (fast wins):
- Very specific: line 51
Node.js: Check package.json + package-lock.json for known vulnerable packages
- Very specific: line 52
Python: Check requirements.txt / pyproject.toml / Pipfile
- Very specific: line 53
Java: Check pom.xml / build.gradle
- Very specific: line 58
Read references/vulnerable-packages.md for a curated watchlist
- Very specific: line 67
Read references/secret-patterns.md for regex patterns and entropy heuristics to apply
- Very specific: line 71
Read references/vuln-categories.md for full details on each category.
- Distinctive: line 96
Use of MD5, SHA1, DES for security purposes
- Distinctive: line 108
After the per-file scan, perform a holistic review:
- Distinctive: line 112
Check for insecure trust boundaries between services or modules
- Distinctive: line 117
Ask: "Is this actually exploitable, or is there sanitization I missed?"
- Distinctive: line 118
Check if a framework or middleware already handles this upstream
- Distinctive: line 131
Add a comment explaining the fix inline
- Distinctive: line 153
If the codebase is clean, say so clearly: "No vulnerabilities found" with what was scanned
- Very specific: line 160
Search patterns: SQL injection, XSS, command injection, SSRF, BOLA, IDOR, JWT, CSRF, secrets, cryptography, race condition, path traversal
- Very specific: line 162
Search patterns: API key, token, private key, connection string, entropy, .env, GitHub Actions, Docker, Terraform
- Very specific: line 164
Search patterns: Express, React, Next.js, Django, Flask, FastAPI, Spring Boot, PHP, Go, Rails, Rust
- Very specific: line 166
Search patterns: lodash, axios, jsonwebtoken, Pillow, log4j, nokogiri, CVE
“Common” is measured: kept by at least 6 in 10 of the 164 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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
- Search patterns:
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
- Search patterns:
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
- Search patterns:
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
- Search patterns:
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
- Search patterns:
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