GenAI Security

GenAI security refers to the practice of protecting generative AI systems, such as chatbots, coding assistants, and content tools, from misuse, data leakage, and manipulation. It covers risks like prompt injection, where a crafted input tricks a model into ignoring its instructions, and the chance that employees expose confidential data through these tools. For compliance and risk teams, it is the set of controls that determines whether a company can deploy generative AI without creating new legal, privacy, or reputational exposure.

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ResearchGlobal2026-10-22

OWASP Red-Teaming Manual Sets a GenAI Security Evidence Benchmark

The OWASP GenAI Security Project published its GenAI Red Teaming Manual Version 1.0, a structured methodology for testing the security, safety, and robustness of generative AI systems. The manual covers six testing phases: planning, reconnaissance, attack-surface mapping, exploitation, persistence, and impact assessment. Enterprises can use it to define red-team scope, produce adversarial testing evidence, and evaluate vendor security assurances.

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