responsible-disclosure
Ethical vulnerability reporting, coordinated disclosure, and bug bounty participation for AI systems
发现 数据库 相关 Skills,比较来源仓库和用途,查看适合你工作流的技能说明。
Ethical vulnerability reporting, coordinated disclosure, and bug bounty participation for AI systems
Tools and frameworks for AI red teaming including PyRIT, garak, Counterfit, and custom attack automation
Generate adversarial inputs, edge cases, and boundary test payloads for stress-testing LLM robustness
Techniques to test and bypass AI safety filters, content moderation systems, and guardrails for security assessment
Attack techniques for Retrieval-Augmented Generation systems including knowledge base poisoning
Securing AI/ML infrastructure including model storage, API endpoints, and compute resources
Test AI training pipelines for data poisoning vulnerabilities and backdoor injection
Real-time monitoring and detection of adversarial attacks and model drift in production
Privacy attacks to extract training data and sensitive information from AI models
Implementing safety filters, content moderation, and guardrails for AI system inputs and outputs
Structured approaches for AI security testing including threat modeling, penetration testing, and red team operations
Security best practices for deploying AI/ML models to production environments
Advanced prompt manipulation including direct attacks, indirect injection, and multi-turn exploitation
Advanced LLM jailbreaking techniques, safety mechanism bypass strategies, and constraint circumvention methods
Defensive techniques using adversarial examples to improve model robustness and security
CI/CD integration and automation frameworks for continuous AI security testing
Test AI systems for code injection vulnerabilities including prompt-to-code attacks and agent exploitation
Techniques to extract model weights, architecture, and training data through API queries
Professional certifications, CTF competitions, and training resources for AI security practitioners
Professional security report generation, executive summaries, finding documentation, and remediation tracking
Comprehensive security testing automation for AI/ML systems with CI/CD integration
Master prompt injection attacks, jailbreak techniques, input manipulation, and payload crafting for LLM security testing
Standard datasets and benchmarks for evaluating AI security, robustness, and safety
Git fundamentals - init, add, commit, status, log, and core concepts
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。