AI agents create a policy enforcement problem that is fundamentally different from securing conventional applications. A traditional application follows code paths defined in advance. An agent ...

Traditional methods can't keep up with autonomous agents. Agentic AI access controls can provide clear lines of ...

The Model Context Protocol gives AI applications a standard way to discover and use tools, data, prompts, and other capabilities. This guide explains MCP's architecture, primitives, security ...

AWS documentation states that input validation and prompt-injection prevention are customer responsibilities under the AgentCore Harness shared-responsibility model. The Harness validates the ...

Meta patched a zero-day in Muse’s Mac app, but VentureBeat found enterprise security teams still lack central visibility into ...

As autonomous agents execute business processes in real time, the distance between a decision and its consequences shrinks, ...

Prompt injection is an attack or failure mode in which untrusted content changes an AI system's behavior by supplying ...

Discover why autonomous AI agents are becoming the ultimate non-human administrator and why securing AI access is critical for Privileged Access Management PAM.

Agents can already discover assets, enumerate services, and map an attack surface with little human input.

Veteran industry analyst Sanjeev Mohan notes that AI is just the latest data-fueled technology, and AI tools are only as good ...

Researchers warn that trusted AI agents can act as proxies for privileged accounts when user permissions are not enforced ...

And it could do so without any consequence. Unlike the Microsoft Enterprise AI Services Code of Conduct, which defines how ...