القائمة
Comprehensive AI risk management, EU AI Act compliance, and LLM usage governance
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
GitHub Agentic Workflows (gh-aw) - markdown-based AI automation with 5-layer security, safe outputs, and Continuous AI patterns
gh-aw CLI usage, compilation, testing, debugging, add-wizard, and CI/CD practices for GitHub Agentic Workflows
Multi-agent coordination, orchestrator-worker patterns, /plan decomposition, and project coordination for GitHub Agentic Workflows
5-layer defense-in-depth security for GitHub Agentic Workflows - safe outputs, threat detection, AWF firewall, and zero-trust patterns
Continuous AI patterns from Agent Factory - issue triage, documentation sync, code quality, security scanning, and project coordination
GDPR compliance including privacy by design, data protection requirements, consent management, right to be forgotten, and data breach response
| 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
- documentation: technical_docs_and_user_manuals
- human_oversight: meaningful_human_review_required
- transparency: users_informed_of_ai_involvement
- conformity_assessment: third_party_audit_required
limited_risk_systems:
examples:
- chatbots: customer_service_bots
- deepfakes: synthetic_media_generation
requirements:
- transparency_obligations: users_informed_interacting_with_ai
- disclosure: ai_generated_content_labeled
minimal_risk_systems:
examples:
- spam_filters: email_filtering
- ai_video_games: entertainment_applications
- github_copilot: code_completion_assistance
requirements:
- voluntary_codes: follow_best_practices
- basic_transparency: disclose_ai_use_in_documentation
llm_usage_governance:
github_copilot:
approved_use:
- code_completion: autocomplete_and_suggestions
- documentation: generating_code_comments
- test_generation: creating_unit_test_scaffolding
security_controls:
- code_review: all_ai_generated_code_manually_reviewed
- secret_scanning: automated_pre_commit_hooks
- license_compliance: verify_suggested_code_licenses
- no_sensitive_data: never_input_customer_or_confidential_data
prohibited_use:
- production_secrets: entering_api_keys_or_passwords
- customer_data: inputting_personal_or_business_data
- unreviewed_deployment: deploying_ai_code_without_review
chatgpt_claude:
approved_use:
- research: general_information_gathering
- brainstorming: idea_generation_and_planning
- documentation: writing_assistance_for_public_docs
prohibited_use:
- confidential_data: client_information_or_trade_secrets
- source_code: proprietary_code_or_algorithms
- personal_data: customer_or_employee_information
human_oversight:
ai_decisions:
code_generation:
- review_required: all_copilot_suggestions_reviewed
- testing: ai_code_must_pass_automated_tests
- security_scan: sast_sca_checks_mandatory
business_decisions:
- ai_as_advisor: ai_provides_recommendations_only
- human_final_decision: ceo_makes_final_call
- documentation: record_ai_input_and_human_decision
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)
