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AI Security Skills
AI security combines established security practices with threats affecting models, prompts, training data, retrieval systems, agents, tools, and third-party services. Employers seek threat modeling, secure architecture, identity and access management, secrets handling, data protection, adversarial testing, supply-chain review, logging, monitoring, and incident response.
Applied skill means analyzing the whole system rather than treating the model as an isolated object. Create a threat model for an AI assistant that can retrieve internal data and call tools. Document assets, trust boundaries, attack paths, controls, detection, residual risk, and test cases for prompt injection, unauthorized access, data leakage, and unsafe action.
Related: AI Security Architect, AI Incident Response Lead, Cybersecurity GRC Skills, Privacy Engineering.
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