security-audit
Skill1 starsChanged 17 days agoMITView on GitHub
Use for code security audits or checks before commits/deployments. Trace data flows to find injection, auth, secrets, dependency, cryptography and business logic vulnerabilities.
- Reads credentials
192 other projects use a version of this, 1 of them edited.
Adopted by
Most recently taken up by
- argos-ci/argostheir own version, first seen Nov 9, 2026
- classroomio/classroomiotheir own version, first seen Nov 9, 2026
- dio-az/dotfilestheir own version, first seen Nov 8, 2026
- roke22/Squadratheir own version, first seen Nov 8, 2026
- qwwiwi/agentos-skills-publictheir own version, first seen Nov 8, 2026
- craigcossairt/trellistheir own version, first seen Nov 8, 2026
Used with
Projects with it also use create-stories, story-done and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
lilangMaxSkillcreate-stories
Break a single epic into implementable story files. Reads the epic, its GDD, governing ADRs, and control manifest. Each story embeds its GDD requirement TR-ID, ADR guidance, acceptance criteria, story type, and test evidence path. Run after /create-epics for each epic.
Also in 11 projects that use this
lilangMaxSkillstory-done
End-of-story completion review. Reads the story file, verifies each acceptance criterion against the implementation, checks for GDD/ADR deviations, prompts code review, updates story status to Complete, and surfaces the next ready story from the sprint.
Also in 11 projects that use this
nicepkgSkillcommunity-led-growth
Expert in community-led growth (CLG) - leveraging user communities to drive acquisition, retention, and expansion. Covers building developer communities, user groups, ambassador programs, and turning customers into advocates. Knows the difference between community as a feature vs community as a growth engine, and how to measure community ROI. Use when "community-led, CLG, ambassador program, champion program, user community, developer community, word of mouth, user group, " mentioned.
Also in 5 projects that use this
nicepkgSkillph-community-outreach
Engage Reddit, Indie Hackers, Hacker News and other communities for Product Hunt launches. Use this skill to identify relevant communities, craft appropriate posts, and drive cross-platform engagement without appearing spammy.
Also in 5 projects that use this
- +7 more from lilangMax
- +1 more from nicepkg
Other versions192 projects use a version of this.
Word for word · 0
None found.
Edited · 1
- Cogni-AI-OU/cogni-ai-agent-skills★ 416% same
Wrote their own version · 191
- ruvnet/claude-flow★ 80ksame name
- ruvnet/ruflo★ 79ksame name
- PostHog/posthog★ 40ksame name
- Donchitos/Claude-Code-Game-Studios★ 27ksame name
- cloudflare/security-audit-skill★ 18ksame name
- rommapp/romm★ 14ksame name
- kubeshark/kubeshark★ 12ksame name
- maximhq/bifrost★ 9.4ksame name
- mono/SkiaSharp★ 5.6ksame name
- MaxMiksa/Auto-Company★ 3.2ksame name
181 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.
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- The first 60 shown.
The file
Show its rules and text
We split this skill into the rules it gives an agent
25 rules. 0 are common, 12 are distinctive, and 13 are very specific to this project.
0
Common
Most of the 173 edited versions we read keep these.
12
Distinctive
This author's own choices. Worth a look.
13
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 15
Use this skill when the request involves:
- Distinctive: line 42
Follow these steps in order every time:
- Very specific: line 46
If a path was provided (/security-review src/auth/), scan only that scope
- Distinctive: line 47
If the request is about changes (a diff, staged files, a pre-commit or pre-deploy check), scope to the changed files (git diff, git diff …
- Distinctive: line 51
If no path given, scan the entire project starting from the root
- Very specific: line 54
Read references/language-patterns.md to load language-specific vulnerability patterns
- Distinctive: line 57
Before scanning source code, audit dependencies first (fast wins):
- Very specific: line 58
Node.js: Check package.json + package-lock.json for known vulnerable packages
- Very specific: line 59
Python: Check requirements.txt / pyproject.toml / Pipfile
- Very specific: line 60
Java: Check pom.xml / build.gradle
- Very specific: line 64
If available, run the ecosystem's audit tool (npm audit, pip-audit, or equivalent) — it reflects current advisories.
- Very specific: line 68
Read references/vulnerable-packages.md for a curated watchlist
- Very specific: line 77
Read references/secret-patterns.md for regex patterns and entropy heuristics to apply
- Very specific: line 81
Read references/vuln-categories.md for full details on each category.
- Distinctive: line 109
Use of MD5, SHA1, DES for security purposes
- Distinctive: line 127
After the per-file scan, perform a holistic review:
- Distinctive: line 131
Check for insecure trust boundaries between services or modules
- Distinctive: line 136
Ask: "Is this actually exploitable, or is there sanitization I missed?"
- Distinctive: line 137
Check if a framework or middleware already handles this upstream
- Distinctive: line 152
Add a comment explaining the fix inline
- Distinctive: line 174
If the codebase is clean, say so clearly: "No vulnerabilities found" with what was scanned
- Very specific: line 181
Search patterns: SQL injection, XSS, command injection, SSRF, BOLA, IDOR, JWT, CSRF, secrets, cryptography, race condition, path traversal
- Very specific: line 183
Search patterns: API key, token, private key, connection string, entropy, .env, GitHub Actions, Docker, Terraform
- Very specific: line 185
Search patterns: Express, React, Next.js, Django, Flask, FastAPI, Spring Boot, PHP, Go, Rails, Rust
- Very specific: line 187
Search patterns: lodash, axios, jsonwebtoken, Pillow, log4j, nokogiri, CVE
“Common” is measured: kept by at least 6 in 10 of the 173 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 changed code before a commit or deployment — especially auth, API, database, dependency, or config changes
- 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 the request is about changes (a diff, staged files, a pre-commit or pre-deploy check),
scope to the changed files (
git diff,git diff --staged). Still read the surrounding code they call into or are called from — a change is often only exploitable in context. Run Step 2 only if a dependency manifest or lock file changed - 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 - If available, run the ecosystem's audit tool (
npm audit,pip-audit, or equivalent) — it reflects current advisories. These tools need network access to the package registry; if it's unavailable, fall back to the watchlist below and say the audit was offline - 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 in scope (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
- Session cookies missing
Secure/HttpOnly/SameSite - Passwords stored in plaintext or with a fast hash; weak password policy; no MFA on privileged accounts
- 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
Security Misconfiguration & Logging
- Permissive CORS, debug mode in production, missing security headers
(framework specifics in
references/language-patterns.md) - Security events (failed logins, access-control denials, privilege changes) not logged, leaving attacks undetectable
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.
For a snippet or diff scope, drop sections that don't apply (e.g. the dependency audit when
no manifest changed) rather than filling them with zeros.
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:
External references for each finding's Reference line: OWASP Top 10, CWE Top 25
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