OWASP Top 10 2025 Security Audit

Goal

Systematic codebase audit against the OWASP Top 10 2025 framework. Produces a structured severity-rated report with evidence-backed findings. Emphasizes semantic code understanding over regex pattern matching — grep patterns are starting points, real analysis happens by reading and reasoning about code context.

When to use

• "Run an OWASP audit on this codebase"
• "Check for OWASP Top 10 vulnerabilities"
• "Security audit against OWASP 2025"
• "Audit A01 and A03 only"
• "Check this repo for common vulnerabilities"
• "OWASP security review"

When not to use

• PR code review (use review skill)
• npm audit / pip audit / dependency scanning only
• SOC2 / ISO 27001 compliance checks (use drata-api skill)
• General security questions without audit intent
• Threat modeling (use security-threat-model skill)
• Single-file code review

Inputs

• Codebase accessible via Glob/Grep/Read
• Optional: specific OWASP categories (e.g. "A01 and A03 only")
• Optional: focus areas or known concerns

Outputs

• Markdown report inline (write to file only if user requests)
• Executive summary table
• Per-category findings with severity/confidence/evidence/remediation
• Summary statistics and next steps

Workflow

Phase 1: Reconnaissance

Classify the project before auditing. Use Glob/Read on key files:

Glob: package.json, requirements.txt, go.mod, Cargo.toml, *.tf, *.csproj, pom.xml
Glob: Dockerfile*, docker-compose*, .github/workflows/*
Glob: **/routes/*, **/api/*, **/controllers/*, **/handlers/*
Read: README.md (first 100 lines), main entry points

Determine:

• Project type: web-app | api | iac | library | cli | mobile | monorepo
• Languages/frameworks: e.g. Node/Express, Python/Django, Go/Gin, Terraform/AWS
• Deployment model: serverless, containers, VMs, static hosting
• Data sensitivity signals: auth, PII, payments, healthcare, crypto

Phase 2: Relevance Filtering

Use project type to set audit depth per category. Prevents nonsensical checks (e.g. SQL injection on Terraform).

Category	web-app	api	iac	library	cli	mobile
A01 Broken Access Control	Full	Full	Full	Light	Light	Full
A02 Security Misconfiguration	Full	Full	Full	Light	Light	Full
A03 Supply Chain Failures	Full	Full	Light	Full	Full	Full
A04 Cryptographic Failures	Full	Full	Light	Full	Light	Full
A05 Injection	Full	Full	Skip	Light	Full	Full
A06 Insecure Design	Full	Full	Light	Light	Light	Full
A07 Authentication Failures	Full	Full	Skip	Light	Skip	Full
A08 Data Integrity Failures	Full	Full	Light	Full	Light	Full
A09 Logging & Alerting	Full	Full	Light	Light	Light	Full
A10 Exceptional Conditions	Full	Full	Light	Full	Full	Full

• Full: run all grep patterns + semantic analysis
• Light: grep patterns only, flag but don't deep-dive
• Skip: mention as not applicable in report, move on

Phase 3: Evidence Gathering

For each relevant category, run Grep/Glob patterns from CATEGORIES.md. Use parallel tool calls for independent categories. Collect file paths and matching lines as evidence.

Phase 4: Semantic Analysis

For each flagged file/pattern:

1. Read surrounding code context (not just matched line)
2. Determine if finding is true positive or false positive
3. Check for existing mitigations (guards, validators, middleware)
4. Assign severity: Critical / High / Medium / Low
5. Assign confidence: High / Medium / Low
6. Note specific remediation

Severity criteria:

• Critical: exploitable without authentication, leads to data breach or RCE
• High: exploitable with low-privilege access, significant data exposure
• Medium: requires specific conditions, limited exposure
• Low: defense-in-depth issue, minimal direct impact

Phase 5: Report Generation

Use this template:

# OWASP Top 10 2025 Security Audit Report

**Project**: <name>
**Type**: <project-type> | **Languages**: <langs> | **Date**: <date>
**Scope**: <full audit | partial: categories listed>

## Executive Summary

| Severity | Count |
|----------|-------|
| Critical | N |
| High     | N |
| Medium   | N |
| Low      | N |
| Info     | N |

<1-3 sentence summary of key findings and overall posture>

## Findings

### A0X: <Category Name> — <PASS | FINDINGS | N/A>

> Relevance: Full | Light | Skip

#### Finding X.1: <title>
- **Severity**: Critical | High | Medium | Low
- **Confidence**: High | Medium | Low
- **Location**: `path/to/file:line`
- **Evidence**: <code snippet or pattern match>
- **Issue**: <what's wrong and why it matters>
- **Remediation**: <specific fix>

(repeat per finding)

---

## Summary Table

| Category | Status | Critical | High | Medium | Low |
|----------|--------|----------|------|--------|-----|
| A01 | ... | ... | ... | ... | ... |
(all 10 categories)

## Methodology

- Automated pattern matching via Grep/Glob
- Semantic code analysis of flagged locations
- False positive filtering based on code context
- Project-type relevance filtering applied

## Next Steps

1. <prioritized remediation actions>
2. <recommended tooling or processes>
3. <categories needing deeper manual review>

Partial Audit Support

When user requests specific categories (e.g. "audit A01 and A03 only"):

1. Skip Phase 2 (relevance filtering)
2. Minimal Phase 1 — detect language/framework only
3. Run only requested categories through Phases 3-5
4. Report covers only requested categories, notes others as out-of-scope

Decision Points

• Large codebase (>500 files): Focus on entry points, auth boundaries, and config files. Note coverage limitations in report.
• Monorepo: Run Phase 1 per sub-project. Produce per-project section or single unified report based on user preference.
• No findings: Report as clean audit with methodology notes. Don't fabricate issues.

Validation Checklist

• All 10 categories addressed (or noted as N/A/out-of-scope)
• Every finding has severity + confidence + location + evidence + remediation
• False positives filtered (not just raw grep output)
• Project type correctly identified and relevance matrix applied
• Report uses consistent severity definitions
• Executive summary accurately reflects findings

References

• Category details, grep patterns, semantic checks: CATEGORIES.md
• Evaluation prompts: EVALUATIONS.md