Building
Identify threats specific to AI systems including adversarial attacks, data poisoning, model theft, and prompt injection.
Essential practices for minimally viable AI assurance. Core practices established with basic automation and human oversight.
Advanced practices with extensive automation and safety controls. Integrated security, metrics-driven improvement.
Continuous threat monitoring, thought leadership, automated intelligence production, industry contribution.
AI applications, models, code security, vulnerability detection, and AI-powered SAST/DAST.
View Details →Training and operational data protection, privacy, classification, and DLP systems.
View Details →Cloud and on-premise security, configuration management, network security, and CSPM.
View Details →Third-party AI service risk management, supply chain security, and vendor assessments.
View Details →Business workflows, incident response, SOAR automation, and governance processes.
View Details →User interfaces, APIs, endpoint protection, EDR, and mobile security for AI systems.
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