소스 정보
- 저장소
- Miosa-osa/canopy
- 최근 소스 활동
- 2026년 8월 16일 14:17
- 감지된 SKILL.md 언어
- 영어
- 스타
- 228
- 포크
- 54
설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/Miosa-osa/canopy --skill security-auditor명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Evaluate retrieval and generation quality in RAG pipelines. Separate scoring for retrieval (recall, precision, MRR) and generation (faithfulness, relevance, completeness). End-to-end pipeline assessment with bottleneck identification. Triggers on: "eval rag", "rag evaluation", "retrieval evaluation", "rag quality", "rag metrics"
Design binary pass/fail LLM-as-Judge evaluators. Structured prompt engineering for evaluation: criteria definition, rubric construction, few-shot calibration, and bias mitigation. Produces a ready-to-deploy judge prompt with scoring instructions. Triggers on: "judge prompt", "llm judge", "evaluator prompt", "scoring prompt", "grading rubric"
Language Agent Tree Search - Monte Carlo planning - 92.7% on HumanEval
SOC 직업 분류 기준
SKILL.md 표시 중
| name | security-auditor |
| description | Comprehensive security analysis and vulnerability detection |
| trigger | security|vulnerability|CVE|OWASP|audit|pentest|harden|compliance|secret|exploit |
| priority | 1 |
This skill activates when:
.env*, *secret*, *credential*, Dockerfile, *.tf, *security*Identify the security surface and project characteristics.
Actions:
1. Detect project type and languages
2. Identify sensitive file patterns
3. Check for existing security configurations
4. Review .gitignore for security patterns
Run static code analysis for vulnerabilities.
Tools:
- Semgrep: Multi-language SAST
- Bandit: Python-specific security
- ESLint security plugin: JavaScript/TypeScript
- Gosec: Go security
Rulesets:
- p/security-audit
- p/owasp-top-ten
- p/secrets
- p/sql-injection
- p/xss
Check for vulnerable dependencies.
Tools:
- Trivy: Universal vulnerability scanner
- npm audit: Node.js dependencies
- pip-audit: Python dependencies
- OSV-Scanner: Cross-language CVE database
Focus:
- Known CVEs (Critical/High priority)
- Outdated packages
- License compliance
Find exposed credentials and sensitive data.
Tools:
- Gitleaks: Fast secret detection
- TruffleHog: Verified secret scanning
Patterns:
- AWS credentials (AKIA...)
- API keys
- Private keys
- Database connection strings
- JWT tokens
Analyze security configurations.
Checks:
- Security headers (HSTS, CSP, X-Frame-Options)
- CORS configuration
- Cookie security flags
- TLS configuration
- Authentication settings
Generate prioritized findings report.
Format:
- SARIF for tool integration
- Markdown for human review
- CVSS scoring
- OWASP Top 10 mapping
- CWE correlation
| Category | Checks |
|---|---|
| A01 Broken Access Control | Authorization checks, IDOR, CORS |
| A02 Cryptographic Failures | TLS, encryption, key management |
| A03 Injection | SQLi, XSS, Command injection |
| A04 Insecure Design | Threat modeling, secure patterns |
| A05 Security Misconfiguration | Headers, defaults, errors |
| A06 Vulnerable Components | Dependencies, CVEs |
| A07 Auth Failures | Session, passwords, MFA |
| A08 Data Integrity | Signatures, CI/CD security |
| A09 Logging Failures | Audit logs, sensitive data |
| A10 SSRF | URL validation, network segmentation |
| Severity | CVSS | Response Time | Examples |
|---|---|---|---|
| CRITICAL | 9.0+ | Immediate | RCE, Active exploit, Secrets |
| HIGH | 7.0-8.9 | 24 hours | SQLi, XSS, Auth bypass |
| MEDIUM | 4.0-6.9 | 7 days | Info disclosure, CSRF |
| LOW | 0.1-3.9 | 30 days | Minor misconfig |
{
"finding_id": "SEC-001",
"severity": "CRITICAL",
"cvss": 9.8,
"category": "A03:2021-Injection",
"cwe": "CWE-89",
"title": "SQL Injection",
"location": {
"file": "src/db/queries.ts",
"line": 45,
"column": 12
},
"description": "User input directly interpolated in SQL query",
"evidence": "const query = `SELECT * FROM users WHERE id = ${userId}`",
"remediation": "Use parameterized queries with prepared statements",
"references": [
# Security Audit Summary
## Risk Assessment: HIGH
## Findings Overview
| Severity | Count | Categories |
|----------|-------|------------|
| Critical | 2 | A03, A06 |
| High | 5 | A01, A02, A07 |
| Medium | 8 | A05, A09 |
| Low | 3 | A05 |
## Critical Issues (Immediate Action)
1. SQL Injection in user input handling
2. Hardcoded AWS credentials
## Recommendations
1. Fix critical issues within 24 hours
2. Update vulnerable dependencies
3. Add security headers
4. Implement proper secret management
@dependency-analyzer: Deep SCA analysis@code-reviewer: Security-focused code review@devops-engineer: Infrastructure security@master-orchestrator: Status updatesAfter completing security audits:
/mem-save pattern "SQL injection pattern in TypeScript template literals"
/mem-save solution "Remediated XSS by switching to React's built-in escaping"
/mem-save decision "Adopted parameterized queries project-wide"