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ui
XML layouts, ConstraintLayout, Jetpack Compose, Material Design 3.
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测试与安全 AI 技能
发现 测试与安全 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。
分类目录: 测试与安全
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vulnerability-discovery
Systematic vulnerability finding, threat modeling, and attack surface analysis for AI/LLM security assessments
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defense-implementation
Implement mitigations, create input filters, design output guards, and build defensive prompting for LLM security
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responsible-disclosure
Ethical vulnerability reporting, coordinated disclosure, and bug bounty participation for AI systems
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GitHub
red-team-frameworks
Tools and frameworks for AI red teaming including PyRIT, garak, Counterfit, and custom attack automation
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adversarial-examples
Generate adversarial inputs, edge cases, and boundary test payloads for stress-testing LLM robustness
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safety-filter-bypass
Techniques to test and bypass AI safety filters, content moderation systems, and guardrails for security assessment
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GitHub
rag-exploitation
Attack techniques for Retrieval-Augmented Generation systems including knowledge base poisoning
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infrastructure-security
Securing AI/ML infrastructure including model storage, API endpoints, and compute resources
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data-poisoning
Test AI training pipelines for data poisoning vulnerabilities and backdoor injection
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continuous-monitoring
Real-time monitoring and detection of adversarial attacks and model drift in production
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model-inversion
Privacy attacks to extract training data and sensitive information from AI models
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input-output-guardrails
Implementing safety filters, content moderation, and guardrails for AI system inputs and outputs
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GitHub
testing-methodologies
Structured approaches for AI security testing including threat modeling, penetration testing, and red team operations
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secure-deployment
Security best practices for deploying AI/ML models to production environments
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GitHub
prompt-hacking
Advanced prompt manipulation including direct attacks, indirect injection, and multi-turn exploitation
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GitHub
llm-jailbreaking
Advanced LLM jailbreaking techniques, safety mechanism bypass strategies, and constraint circumvention methods
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GitHub
adversarial-training
Defensive techniques using adversarial examples to improve model robustness and security
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GitHub
automated-testing
CI/CD integration and automation frameworks for continuous AI security testing
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GitHub
code-injection
Test AI systems for code injection vulnerabilities including prompt-to-code attacks and agent exploitation
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GitHub
model-extraction
Techniques to extract model weights, architecture, and training data through API queries
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GitHub
certifications-training
Professional certifications, CTF competitions, and training resources for AI security practitioners
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GitHub
red-team-reporting
Professional security report generation, executive summaries, finding documentation, and remediation tracking
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GitHub
security-testing
Comprehensive security testing automation for AI/ML systems with CI/CD integration
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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。