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TL;DR: The OWASP Top 10 for Agentic Applications is a list of the ten most critical security risks facing autonomous AI agents, published in December 2025. It is a taxonomy to assess exposure against, not a compliance mandate.
TL;DR: AI agent identity management replaces shared service accounts with agent-specific identities, scopes authorization to each task, and produces access records an auditor can follow from request to outcome.
TL;DR: AI agent orchestration is the coordination of multiple agents, tools, models, and shared state, and in production it only works when operational controls run inside every agent, tool call, and handoff. Each orchestration pattern fails in its own way, so each needs its own controls.
It is 2:14 in the morning. A payments reconciliation agent at a large bank starts pulling customer account records it has never touched before. Within seconds, a runtime control flags the behavior, the agent is quarantined, and a kill switch severs its access to every downstream tool.
MCP has become the default way AI agents connect to real systems: internal databases, business APIs, file systems, third-party services. Introduced in late 2024, it's since been adopted across OpenAI, Google DeepMind, Microsoft, and thousands of engineering teams, with SDK downloads now in the tens…
Most conversations about prompt injection assume the attacker's instruction arrives through content: a message a user typed, a webpage an agent scraped, a document it summarized. Tool poisoning breaks that assumption.
Gartner published its first Magic Quadrant for AI Governance Platforms in June and a Hype Cycle for AI Governance Technologies in August. Both are rigorous. Both answer the question they set out to answer. Our argument is with the title, "AI Governance," not the research under it.
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