Awesome-omni-skill perseus:report
Use when generating the final executive security report (Phase 4)
git clone https://github.com/diegosouzapw/awesome-omni-skill
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/development/perseus-report" ~/.claude/skills/diegosouzapw-awesome-omni-skill-perseus-report && rm -rf "$T"
skills/development/perseus-report/SKILL.mdPerseus Report (Phase 4)
Context & Authorization
IMPORTANT: This skill generates a professional security report for the user's own codebase. The report is intended to help developers and stakeholders understand and remediate security issues in their own software.
Multi-Language Support
Report generation adapts remediation guidance based on detected language/framework:
| Language | Frameworks |
|---|---|
| JavaScript/TypeScript | Express, Fastify, Next.js, Nest.js |
| Go | Gin, Echo, Fiber, Chi |
| PHP | Laravel, Symfony, Slim |
| Python | FastAPI, Django, Flask |
| Rust | Actix-web, Axum, Rocket |
| Java | Spring Boot, Quarkus |
| Ruby | Rails, Sinatra |
| C# | ASP.NET Core |
Overview
This skill executes the Reporting Phase of the Perseus framework. It synthesizes findings from Scan, Audit, Exploit, and Specialist phases into a professional executive report.
Goal: Communicate verified risks effectively to stakeholders and drive remediation.
Methodology:
- Collect: Gather all deliverables from previous phases.
- Verify: Prioritize verified exploits over theoretical risks.
- Contextualize: Explain business impact, not just technical flaws.
- Remediate: Provide language-specific, actionable fixes for each finding.
Execution Instructions
Step 1: Collect All Deliverables
Read all files in
deliverables/:
Core Phase Deliverables:
(Mode, scope, constraints)engagement_profile.md
(Scan)code_analysis_deliverable.md- All
files (Audit)*_analysis.md
(Exploit)exploitation_report.md
(Verification limits and approved window)verification_scope.md
Specialist Deliverables (if present):
(API + GraphQL + WebSocket + OAuth)api_security_analysis.md
(NoSQL + SSTI + Log4j)injection_deep_analysis.md
(JWT + Hashing + Encryption)crypto_security_analysis.md
(CVEs + Typosquatting)supply_chain_analysis.md
(Path Traversal + XXE + Zip Slip)file_security_analysis.md
(Race Conditions + AI Security)business_logic_analysis.md
(React/Vue/Angular + SSR)client_side_analysis.md
(Docker + CI/CD + Cloud + K8s)config_security_analysis.md
Step 2: Calculate Risk Metrics
Severity Scoring (CVSS-inspired):
| Severity | Criteria | Score |
|---|---|---|
| Critical | RCE, Auth Bypass, SQLi with data access, Admin takeover, Container escape, AI prompt injection leading to RCE | 9.0-10.0 |
| High | Stored XSS, SSRF to internal, Privilege Escalation, Sensitive data exposure, CI/CD injection, Public cloud storage | 7.0-8.9 |
| Medium | Reflected XSS, CSRF, Information disclosure, Missing security headers, Outdated dependencies, Docker misconfig | 4.0-6.9 |
| Low | Minor info leak, Best practice violations, Verbose errors, License issues | 0.1-3.9 |
Exploitability Factor:
- VERIFIED: Multiply by 1.0 (confirmed exploitable)
- POTENTIAL: Multiply by 0.7 (likely exploitable)
- THEORETICAL: Multiply by 0.4 (needs specific conditions)
Confidence Factor:
- High: Multiply by 1.0
- Medium: Multiply by 0.75
- Low: Multiply by 0.5
Verification Context Factor:
- VERIFIED in
: Multiply by 1.0PRODUCTION_SAFE - VERIFIED in
: Multiply by 0.9STAGING_ACTIVE - VERIFIED in
: Multiply by 0.85LAB_FULL - VERIFIED in
: Multiply by 0.8LAB_RED_TEAM
: Multiply by 0.7POTENTIAL-PROD-BLOCKED
Step 3: Generate Report
Create
deliverables/SECURITY_REPORT.md using this structure:
# Security Assessment Report **Project:** [Project Name] **Assessment Date:** [Date] **Methodology:** Perseus Security Framework v2.0 **Scope:** [Repository/Application name] **Engagement Mode:** [PRODUCTION_SAFE/STAGING_ACTIVE/LAB_FULL/LAB_RED_TEAM] --- ## Executive Summary ### Assessment Status [Complete/Partial] - [X] phases completed, [Y] specialists run ### Technologies Analyzed | Category | Detected | |----------|----------| | Language | [e.g., TypeScript, Go, Python] | | Framework | [e.g., Next.js 14, Gin, FastAPI] | | Database | [e.g., PostgreSQL, MongoDB, Redis] | | Infrastructure | [e.g., Docker, Kubernetes, AWS] | | CI/CD | [e.g., GitHub Actions, GitLab CI] | | AI/LLM | [e.g., OpenAI, Anthropic, LangChain] | ### Risk Overview | Severity | Verified | Potential | Total | |----------|----------|-----------|-------| | Critical | X | Y | Z | | High | X | Y | Z | | Medium | X | Y | Z | | Low | X | Y | Z | ### Verification Coverage | Category | Count | |----------|-------| | Verified | X | | Failed Verification | Y | | Potential (Prod Blocked) | Z | | Aborted (Safety Kill-Switch) | W | ### Key Findings 1. **[Most Critical Finding]** - Brief description and impact 2. **[Second Critical Finding]** - Brief description and impact 3. **[Third Critical Finding]** - Brief description and impact ### Business Impact - **Data Breach Risk:** [High/Medium/Low] - [Explanation] - **Service Disruption:** [High/Medium/Low] - [Explanation] - **Compliance Impact:** [Regulations affected: GDPR, PCI-DSS, HIPAA, SOC2, etc.] - **Reputation Risk:** [High/Medium/Low] - [Explanation] ### Top 3 Recommendations 1. [Highest priority fix] 2. [Second priority fix] 3. [Third priority fix] --- ## Attack Surface Summary ### Technology Stack - **Language:** [e.g., TypeScript] - **Framework:** [e.g., Next.js 14 (App Router)] - **Database:** [e.g., MongoDB, PostgreSQL] - **Authentication:** [e.g., JWT, NextAuth, OAuth] - **Infrastructure:** [e.g., Docker, Kubernetes, Vercel] ### Entry Points Analyzed | Type | Count | Critical Paths | |------|-------|----------------| | API Endpoints | X | `/api/auth/*`, `/api/admin/*` | | GraphQL | X | `mutation { ... }` | | WebSocket | X | `/ws/chat` | | File Upload | X | `/upload` | | Server Actions | X | `app/actions/*` | ### Dependencies - **Total Packages:** X - **With Known CVEs:** Y - **Critical CVEs:** Z (list package names) ### Infrastructure - **Docker Images:** X - **CI/CD Pipelines:** Y - **Cloud Resources:** Z --- ## Critical Findings (Verified Exploits) > Only findings verified in the Exploit Phase appear here. ### CRITICAL-001: [Title] **Severity:** Critical (9.5) **Status:** VERIFIED EXPLOITABLE **Category:** [Injection/Auth/Config/AI/etc.] **Language:** [Node.js/Go/Python/etc.] #### Description [Clear explanation of the vulnerability] #### Location - **File:** `path/to/file.js` - **Line:** 42-48 - **Endpoint:** `POST /api/vulnerable` #### Proof of Concept
[Minimal reproduction steps or payload]
#### Evidence [Screenshot, response, or output proving exploitation] #### Impact - [Specific impact: data access, RCE, etc.] - [Business impact: what could attacker do?] #### Remediation ```javascript // Vulnerable code [code snippet] // Fixed code (language-specific) [code snippet]
References
- [OWASP Link]
- [CWE Link]
CRITICAL-002: ...
Infrastructure Security Findings
Findings from Docker, CI/CD, Cloud, and Kubernetes analysis.
Docker Security
| Check | Status | Issue |
|---|---|---|
| Non-root user | PASS/FAIL | [Details] |
| Pinned base image | PASS/FAIL | [Details] |
| No secrets in image | PASS/FAIL | [Details] |
| Minimal base | PASS/FAIL | [Details] |
CI/CD Security
| Check | Status | Issue |
|---|---|---|
| No command injection | PASS/FAIL | [Details] |
| Minimal permissions | PASS/FAIL | [Details] |
| Secrets not in logs | PASS/FAIL | [Details] |
Cloud Security
| Resource | Issue | Severity |
|---|---|---|
| S3 Bucket | Public access | Critical |
| Security Group | Open ports | High |
Kubernetes Security
| Check | Status |
|---|---|
| Non-root pods | PASS/FAIL |
| Network policies | PASS/FAIL |
| RBAC configured | PASS/FAIL |
| Secrets encrypted | PASS/FAIL |
AI/LLM Security Findings
Findings from AI security analysis (if applicable).
AI Security Status
| Check | Status | Risk |
|---|---|---|
| Prompt Injection Protection | PASS/FAIL | [Details] |
| Output Filtering | PASS/FAIL | [Details] |
| Tool Use Validation | PASS/FAIL | [Details] |
| RAG Access Control | PASS/FAIL | [Details] |
| Rate Limiting | PASS/FAIL | [Details] |
AI-VULN-001: [Title]
Type: [Prompt Injection/Data Leakage/Tool Abuse] ...
High Severity Findings
HIGH-001: ...
Medium Severity Findings
MEDIUM-001: ...
Low Severity Findings
LOW-001: ...
Potential Vulnerabilities (Unverified)
Findings from Audit that could not be verified but remain risky.
POTENTIAL-001: [Title]
Severity: [Estimated] Reason Not Verified: [Why exploitation wasn't confirmed] Mode Constraint: [Why blocked in current mode] Recommendation: [What to do about it]
Supply Chain Summary
Vulnerability Overview
| Severity | Count | Notable Packages |
|---|---|---|
| Critical | X | [packages] |
| High | X | [packages] |
| Medium | X | [packages] |
License Issues
| Package | License | Risk |
|---|---|---|
| [pkg] | GPL-3.0 | Copyleft in proprietary |
Outdated Dependencies
| Package | Current | Latest | Gap |
|---|---|---|---|
| [pkg] | X.Y.Z | A.B.C | [major/minor] |
Secure Components
Components analyzed and found to be properly secured.
| Component | Security Measures | Notes |
|---|---|---|
| Authentication | bcrypt, rate limiting, MFA | Properly implemented |
| SQL Queries | Parameterized queries | No injection found |
| Docker | Non-root, minimal image | Best practices followed |
| ... | ... | ... |
Strategic Recommendations
Immediate Actions (0-7 days)
- [Critical fix 1] - [Language-specific guidance]
- [Critical fix 2] - [Language-specific guidance]
Short-term (1-4 weeks)
- [High priority improvements]
- [Security configuration changes]
- [Dependency updates]
Long-term (1-3 months)
- [Architectural improvements]
- [Security tooling implementation]
- [Training recommendations]
Infrastructure Hardening
- Docker: [Specific recommendations]
- CI/CD: [Specific recommendations]
- Cloud: [Specific recommendations]
- Kubernetes: [Specific recommendations]
Defense-in-Depth Suggestions
- Input Validation: Implement schema validation (Zod, Joi, Pydantic)
- Output Encoding: Use context-aware encoding
- Security Headers: Implement CSP, HSTS, X-Frame-Options
- Monitoring: Add security logging and alerting
- Dependencies: Implement automated vulnerability scanning in CI/CD
- AI Security: Implement prompt injection detection and output filtering
Appendix
A. Tools Used
- Perseus Security Framework v2.0
- Static Analysis: Code pattern matching, AST analysis
- Dynamic Testing: Safe payload verification
B. Languages & Frameworks Analyzed
- [List all detected with versions]
C. Scope Exclusions
- [What was not tested and why]
D. Glossary
- SQLi: SQL Injection
- XSS: Cross-Site Scripting
- SSRF: Server-Side Request Forgery
- SSTI: Server-Side Template Injection
- XXE: XML External Entity
- IDOR: Insecure Direct Object Reference
- BOLA: Broken Object Level Authorization
- RCE: Remote Code Execution
## Tone & Style * **Professional:** Objective and factual. No hyperbole or fear-mongering. * **Actionable:** Every finding has a language-specific remediation. * **Developer-Focused:** Code examples for fixes in the detected language. * **Business-Aware:** Explain impact in business terms, not just technical. * **Infrastructure-Aware:** Include Docker, CI/CD, Cloud, K8s findings. ## Quality Checklist Before finalizing the report, verify: - [ ] All verified exploits are documented with evidence - [ ] All findings have language-specific remediation guidance - [ ] Severity ratings are consistent - [ ] Infrastructure findings are included (Docker, CI/CD, Cloud, K8s) - [ ] AI/LLM findings are included (if applicable) - [ ] Supply chain summary is complete - [ ] No sensitive data (real credentials, PII) is included - [ ] Report can be shared with stakeholders **Assessment Complete.** Report saved to `deliverables/SECURITY_REPORT.md`.