garagon/nanostack · Archived

security

Use before shipping to production. Performs OWASP Top 10 audit and STRIDE threat modeling against the codebase. Supports --quick, --standard, --thorough modes. Also use when the user asks to check security, audit code, or review for vulnerabilities. Triggers on /security.

First seen Mar 29, 2026

Installation

$ npx skills add garagon/nanostack --skill security

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Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
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Repository health

Stars 204
License LICENSE
Default branch main
Open issues 0
Status Archived

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 14,831 B
  • docs SUMMARY.md 288 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 16 installs

SKILL.md

/security — Security Audit

You think like an attacker but report like a defender. The real attack surface is rarely the code you wrote. It is the secrets in git history, the dependency you forgot to update, the CI pipeline that leaks tokens, and the AI endpoint without rate limiting. Start there, not at the application logic.

Telemetry preamble

Defensive telemetry init. No-op if telemetry is disabled via NANOSTACKNOTELEMETRY=1, ~/.nanostack/.telemetry-disabled, or if the helpers are removed.

_P="$HOME/.claude/skills/nanostack/bin/lib/skill-preamble.sh"
[ -f "$_P" ] && . "$_P" security
unset _P

Intensity Mode

Mode Flag Scope Confidence gate
Quick --quick OWASP A01-A03 (top 3) + secrets scan + dependency check 9/10 — only verified findings
Standard (default) Full OWASP A01-A10 + STRIDE per component + dependencies 7/10 — report anything with evidence
Thorough --thorough Full OWASP + STRIDE + variant analysis + conflict detection + LLM security check 3/10 — flag tentative findings marked as TENTATIVE

Auto-suggest:

  • Pre-commit on small changes → suggest --quick
  • Pre-ship standard feature → --standard (default)
  • Pre-ship auth/payment/infra, or first audit of a codebase → suggest --thorough

Thorough-only features:

  • Variant analysis: When a finding is VERIFIED, search the entire codebase for the same pattern. One confirmed SQL injection means there may be more.
  • Conflict detection: Cross-reference with /review artifacts in .nanostack/review/ for contradictions.
  • TENTATIVE findings: Below confidence gate but worth noting. Mark as TENTATIVE: <description>.

Setup (first run per project)

Resolve context — load plan, review artifacts, matched solutions, and config:

~/.claude/skills/nanostack/bin/resolve.sh security --diff

The output is JSON with upstreamartifacts (plan and review paths), solutions (matched by file overlap and security tags), conflictprecedents (path to precedents doc), diarizations (module briefs), and config (intensity, detected stack, conflict precedence).

From the plan artifact (if present):

  • planned_files[] → focus your audit on these files and their dependencies. Deeper analysis on fewer files is better than shallow analysis on everything.
  • risks[] → treat each planned risk as a security hypothesis to verify. If the plan says "AWS SDK version compatibility" is a risk, check for insecure SDK usage patterns.

From config: use detectedstack to scope which checks to run (skip Python checks in a Go project). Use conflictprecedence for cross-skill conflicts.

Then check if security/config.json exists. If not, ask the user to classify the project:

What type of project is this?
1. Public-facing (users/customers on the internet)
2. Internal (employees/team only, no public access)
3. Compliance-driven (fintech, health, regulated)
4. Library/SDK (consumed by other developers)

Store the answer:

// security/config.json
{
  "project_type": "public_facing",
  "conflict_precedence": "security > review > qa",
  "configured_at": "2026-03-25"
}

This determines:

  • Conflict precedence: public_facing → security wins. internal → review wins. compliance → security wins hard.
  • Default intensity: public_facing/compliance → suggest --thorough on first audit. internal/library → --standard.
  • OWASP priority: public_facing → A01, A03, A07 first. internal → A02, A05, A09 first.

If config already exists, read it and skip setup.

Graduated Rules

<!-- Auto-maintained by bin/graduate.sh. Do not edit manually. --> <!-- Each rule was promoted from a solution with 3+ applications and validation. --> <!-- END GRADUATED RULES -->

Check these rules during your audit. Each one represents a proven security pattern from past sprints.

Process

1. Detect Stack

Auto-detect everything. Do NOT ask the user.

  • package.json → Node.js (check for next, express, fastify, hono)
  • requirements.txt / pyproject.toml → Python (flask, django, fastapi)
  • go.mod → Go (gin, echo, chi)
  • Database deps: prisma, drizzle, mongoose, sqlalchemy, gorm
  • BaaS: supabase, firebase, convex
  • Auth: next-auth, clerk, passport, lucia, jwt
  • AI/LLM: openai, anthropic, langchain, vercel ai sdk
  • Payments: stripe, paddle
  • Infra: Dockerfile, docker-compose.yml, .github/workflows/

Report one-line: Detected: Next.js 14 + Prisma + Stripe, Docker, GitHub Actions

2. Scan

CORE (always run): secrets, injection, auth, config, dependencies, data-exposure.

CONDITIONAL (only if detected): AI/LLM endpoints, payment webhook verification, Docker misconfig, CI/CD pipeline security, file upload handling.

For extended check patterns, reference the OWASP checklist at security/references/owasp-checklist.md.

Read security/references/owasp-checklist.md for the OWASP A01-A10 framework.

Secrets Scan (CRITICAL — always first)

Search for hardcoded credentials using regex patterns:

Pattern What
AKIA[0-9A-Z]{16} AWS access key
sklive[a-zA-Z0-9]{24,} Stripe live key
sk-proj-[a-zA-Z0-9\-_]{20,} OpenAI project key
sk-ant-[a-zA-Z0-9\-_]{80,} Anthropic key
ghp_[a-zA-Z0-9]{36} GitHub PAT
`-----BEGIN (RSA\ EC\ OPENSSH) PRIVATE KEY` Private key in code
`(postgres\ mysql\ mongodb\+srv):\/\/[^:\s]+:[^@\s]+@` DB connection string with password

Context rules: In .test., .example, README, or values containing xxx, TODO, placeholder → downgrade to INFO.

Git history check (mandatory):

git log --all --oneline -- '.env' '.env.local' '*.pem' '*.key' 2>/dev/null | head -10

If results: secrets may be in history even if currently gitignored. CRITICAL — credentials must be rotated.

IMPORTANT: Credential redaction. When reporting secrets, NEVER show the full value. First 4 chars + ** (e.g., sk-pr**).

CI/CD Pipeline Security (if .github/workflows/ exists)

Check What to look for
Unpinned actions uses: action@main instead of uses: action@sha256
pullrequesttarget Runs with write access on fork PRs — code injection vector
Secrets in logs echo ${{ secrets.* }} or debug mode exposing secrets
Overpermissioned GITHUB_TOKEN permissions: write-all when only contents: read needed

AI/LLM Security (if AI deps detected)

Check What to look for
API keys in client bundle NEXTPUBLICOPENAI, NEXTPUBLICANTHROPIC
Prompt injection User input interpolated into system prompts (prompt + req.body)
Missing rate limiting AI endpoints without rate limiter — attacker runs up your bill
Unsanitized LLM output LLM response rendered as HTML without escaping

3. False Positive/Negative Awareness

False positives (skip): .env.example, sktest keys, UUIDs, React/Angular output (XSS-safe by default, only flag escape hatches like dangerouslySetInnerHTML), eval() in build configs, 0.0.0.0 in Docker, SQL in migrations.

False negatives (don't miss): Auth on route but not on query (IDOR), secrets in git history, rate limiting on login but not password reset, SSRF via URL params to 169.254.169.254, dangerouslySetInnerHTML without DOMPurify.

4. STRIDE per component

Spoofing (impersonation?), Tampering (data integrity?), Repudiation (audit trail?), Info Disclosure (leaks?), DoS (overwhelm?), Elevation (privilege escalation?).

4. Produce Report

Report findings progressively. Don't wait until the end. As each phase completes, output its findings immediately so the user sees work happening.

Open with a summary line:

Security: CRITICAL (0) HIGH (1) MEDIUM (2) LOW (1) = 4 findings. Score: B

Scoring: A = 0 critical, 0 high, ≤3 medium. B = 0 critical, 1-2 high. C = 3+ high. D = 1-2 critical. F = 3+ critical.

Use security/templates/security-report.md for the full structure. Every finding must include:

  • What the vulnerability is (specific, not vague)
  • Where it exists (file path and line number)
  • How to exploit it (proof of concept or clear scenario)
  • Fix with actual code, before and after (not "consider sanitizing input")
  • Severity using the classification below

Always close with What's solid: 2-3 specific things the codebase does well on security. Not filler. If the auth is well implemented, say so and say why.

Severity Classification

Severity: Critical (RCE, unauth admin, hardcoded creds), High (stored XSS, IDOR, privilege escalation), Medium (CSRF, info disclosure, missing rate limit), Low (headers, verbose errors, outdated non-vulnerable deps).

Conflict Detection

Always check for conflicts with prior /review findings. The resolver output from Setup includes upstreamartifacts.review (if a review artifact exists) and conflictprecedents (path to the precedents doc). When a conflict is detected, mark inline:

### SEC-005: Excessive error detail
**Conflicts with:** REV-003 → RESOLUTION: structured errors (code + generic msg to user, details to logs)

In --quick mode, apply default precedence (security > review) without documenting. In --standard mode, document conflicts inline. In --thorough mode, document conflicts AND flag as BLOCKING until user confirms.

After completing the audit and conflict detection, save the artifact. Run this command now — do not skip it. The save is validated against the per-phase schema (see reference/artifact-schema.md); a security artifact requires summary (object), findings (array), and context_checkpoint.

SEC_JSON=$(jq -n \
  --arg  mode              "$SEC_MODE" \
  --argjson summary        '{"total_findings":0,"critical":0,"high":0,"medium":0,"low":0}' \
  --argjson findings       '[]' \
  --argjson conflicts      '[]' \
  --arg  checkpoint_summary "Security audit found N findings across OWASP categories." \
  '{
     phase: "security",
     mode: $mode,
     summary: $summary,
     findings: $findings,
     conflicts: $conflicts,
     context_checkpoint: {
       summary: $checkpoint_summary,
       key_files: [],
       decisions_made: [],
       open_questions: []
     }
   }')
~/.claude/skills/nanostack/bin/save-artifact.sh security "$SEC_JSON"

Mode Summary

Aspect Quick Standard Thorough
OWASP scope A01-A03 only Full A01-A10 Full + variant analysis
STRIDE Skip Per component Per component + attack trees
Dependencies npm audit only Full scan Full + license check
Conflict detection Auto-resolve Document inline BLOCKING until resolved
Tentative findings Skip Skip Report as TENTATIVE
Confidence gate 9/10 7/10 3/10

Session state

Read profile, runmode, autopilot, and planapproval per reference/session-state-contract.md. When runmode == reportonly, do not apply fixes; only report findings.

Next Step

After the security audit is complete and the artifact is saved:

If autopilot == true and no critical/high findings: Proceed to next pending skill. Show: Autopilot: security grade X (0 critical, 0 high). Running /qa...

If autopilot and critical or high findings: Stop and ask the user to review. Show the findings and wait. After resolution, continue autopilot.

Otherwise: Read the next action from session state:

~/.claude/skills/nanostack/bin/next-step.sh --json

Use .usermessage for the prose and .nextphase for the phase name. The legacy positional form (next-step.sh security) is still supported.

When profile == "guided", the user-facing output follows the four-block skeleton in reference/plain-language-contract.md (Result / How to try / What was checked / What remains). Whether it is safe to try goes inside Result; do not add a separate block. Use plain words (no "vulnerability", "threat model", "STRIDE"). Example:

<!-- guided-output:start -->

Resultado: Es seguro para probar. No vi problemas que te expongan.

Como verlo:
1. Corre el comando que te indique mas arriba y segui las instrucciones.

Que revise:
- Nadie entra sin permiso a lo que deberia estar protegido.
- Los datos sensibles no quedan a la vista.
- Las entradas raras no rompen ni dejan escapar informacion.

Pendiente:
- No probe contra un ataque dirigido y sostenido.
- No revise servicios externos que no controlamos.

<!-- guided-output:end -->

Final Headline

After the user-facing message above, print one summary line as the very last thing — useful for autopilot logs and quick scanning:

[security] OK: grade <A-F>, <N critical, M high>. Next: <first pending skill or "/ship">.

Use WARN instead of OK if any critical or high findings exist.

After Fixes

When the model or user fixes security findings, do NOT re-run the full audit. Instead:

  • CRITICAL/HIGH fixes: Re-audit only the affected files and the specific vulnerability class. Verify the fix resolves the finding. Save a new artifact.
  • MEDIUM/LOW fixes: Verify the specific fix by reading the changed code. No re-audit needed. Do not save a new artifact — the original audit with the fix note is sufficient.

Re-running the full OWASP scan after fixing a missing Content-Type header wastes time and tokens. Target the verification.

Telemetry finalize

Before returning control:

_F="$HOME/.claude/skills/nanostack/bin/lib/skill-finalize.sh"
[ -f "$_F" ] && . "$_F" security success
unset _F

Pass abort or error instead of success if the audit did not complete normally.

Gotchas

  • Zero findings is valid. Don't manufacture findings.
  • Don't inflate severity. Calibrate to actual exploitability.
  • Show evidence. Input path, sink, missing sanitization. Not "could be vulnerable."
  • Run dependency scanning. npm audit, pip audit, go vuln check.
  • Auth ≠ authz. Logged in ≠ has permission.
  • Check git history for secrets. git log -p --all -S 'password\|secret\|key\|token'
  • Variant analysis in --thorough. One finding = search for the pattern elsewhere.