Tag: AI Workloads

The global research and advisory firm is pushing the industry toward a more practical model for securing AI agents and non-human access.
AI agents exchange sensitive contexts across MCP servers in seconds. Without context-aware auditing, you can’t trace who accessed what.
Static access rules fail in dynamic MCP environments. Context-based access control evaluates identity, context and resources in real time.
An agent behaved like a true insider threat. Unmanaged API keys made those mistakes devastatingly consequential. Both can be true at the same time.
Teams can query workload identity data in plain language, investigate activity, and move faster without leaving the Aembit platform.
Most workload credentials, the API keys, tokens and passwords that connect your services, carry “always on” access that never expires.
Built in the open with customers, now ready to run against real agent workflows.
What starts as a tooling decision ends up shaping cost, reliability, and how far your workflows actually scale before they break down.
AI agent identity breaks down when agents authenticate across OAuth, API keys and managed identities simultaneously. Learn why single-protocol solutions fail.
By combining identity-based access control with content inspection, this closes a gap most teams are still trying to manage with separate tools and after-the-fact controls.