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- 최근 소스 활동
- 2026년 2월 10일 16:25
- 감지된 SKILL.md 언어
- 영어
- 스타
- 10
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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/Hack23/homepage --skill ai-governance명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SKILL.md 표시 중
SOC 직업 분류 기준
| name | AI Governance |
| description | Comprehensive AI risk management, EU AI Act compliance, and LLM usage governance |
| license | Apache-2.0 |
| version | 1.0 |
| author | Hack23 AB |
| tags | ["ai-governance","eu-ai-act","llm-security"] |
| category | security |
| frameworks | ["EU AI Act","ISO 27001:2022","NIST AI RMF"] |
| related_policies | ["AI_Policy.md"] |
Enforce comprehensive AI risk management and EU AI Act compliance, based on AI Policy.
Key Principle: "AI systems require systematic risk management and human oversight."
ai_system_classification:
unacceptable_risk:
prohibited_systems:
- social_scoring: government_or_private_social_credit
- real_time_biometric: public_space_surveillance_without_warrant
- subliminal_manipulation: ai_that_manipulates_behavior
- exploit_vulnerabilities: ai_targeting_vulnerable_groups
action: never_develop_deploy_or_use
high_risk_systems:
examples:
- recruitment_ai: candidate_screening_or_selection
- credit_scoring: loan_approval_algorithms
- law_enforcement: predictive_policing_tools
requirements:
- risk_assessment: comprehensive_before_deployment
- data_quality: high_quality_representative_datasets
prohibited_ai_practices:
- unclassified_systems: deploying_ai_without_risk_assessment
- no_human_oversight: fully_automated_critical_decisions
- biased_training_data: using_unrepresentative_datasets
- black_box_systems: unexplainable_ai_for_high_risk_decisions
- sensitive_data_training: training_ai_on_personal_data_without_consent
- bypassing_controls: using_personal_ai_for_business_without_approval
copilot_workflow:
development:
enable_copilot: vscode_github_copilot_extension
use_suggestions:
- code_completion: accept_for_boilerplate_code
- function_generation: review_logic_before_accepting
- test_scaffolding: verify_test_coverage_and_assertions
security_checks:
pre_commit:
- secret_scanning: gitleaks_pre_commit_hook
- code_review: manual_review_of_ai_suggestions
- license_check: verify_no_copyleft_violations
ci_cd_pipeline:
- sast: sonarcloud_static_analysis
- sca: dependabot_vulnerability_scanning
- test_coverage: minimum_80_percent_coverage
prohibited_inputs:
never_type:
- api_keys: aws_access_keys_database_passwords
- customer_data: email_addresses_names_personal_info
- proprietary_algorithms: trade_secret_business_logic
- production_configs: database_connection_strings
documentation:
- attribution: note_ai_assisted_code_in_comments
- review_notes: document_manual_changes_to_ai_suggestions
- lessons_learned: track_copilot_false_positives_for_training
ai_risk_assessment:
system_identification:
name: recruitment_candidate_screening_tool
classification: HIGH_RISK_per_eu_ai_act
trigger: involves_employment_decisions
risk_analysis:
potential_harms:
- discrimination: algorithm_may_have_gender_or_age_bias
- privacy: processes_personal_data_from_resumes
- transparency: candidates_unaware_of_ai_involvement
likelihood: MEDIUM
impact: HIGH
overall_risk: HIGH
risk_mitigation:
technical_measures:
- bias_testing: fairness_metrics_on_diverse_test_set
- explainability: shap_or_lime_for_decision_explanations
- data_quality: representative_training_dataset
organizational_measures:
- human_review: recruiter_reviews_all_ai_recommendations
- transparency: candidates_informed_of_ai_use
- appeal_process: candidates_can_request_human_review
- audit: annual_third_party_fairness_audit
compliance_obligations:
eu_ai_act:
- risk_management_system: implemented_and_documented
- data_governance: high_quality_training_data_verified
- technical_documentation: available_for_authorities
- conformity_assessment: third_party_audit_planned
gdpr:
- lawful_basis: legitimate_interest_assessment
- data_minimization: only_relevant_resume_data_processed
- automated_decision: human_review_prevents_art_22_violation
approval:
decision: APPROVED_WITH_CONDITIONS
approver: CEO
date: 2026_02_10
review_date: 2026_08_10_semi_annual
conditions:
- quarterly_bias_testing
- monthly_human_override_rate_monitoring
- annual_external_audit
❌ Non-Compliant:
incorrect_chatgpt_use:
prompt: "Review this customer database schema and suggest optimizations"
attached: production_database_dump_with_customer_emails
risk: exposing_personal_data_to_third_party_ai
✅ Corrected:
compliant_chatgpt_use:
data_anonymization:
- remove_personal_data: replace_emails_with_placeholders
- sanitize_schema: generic_field_names_only
- sample_data: synthetic_test_data_not_production
prompt: "Review this anonymized schema and suggest optimizations"
attached: sanitized_schema_with_no_real_data
verification:
- no_personal_data: verified_before_submission
- no_secrets: no_connection_strings_or_credentials
- documented: ai_consultation_logged_in_project_notes
Policies: AI Policy, Information Security
Skills: owasp-llm-security, data-classification, privacy-policy
Frameworks: EU AI Act, NIST AI RMF, ISO 42001 (draft)