Practical guidance on securing AI agents, tools, and the systems they act on, written by the team building the trust layer for AI agents.
Least privilege for AI agents means scoping tool access, data reach, and request-level authority as narrowly as the identity making the request, not the agent as a whole.
A trust boundary in an AI application marks where content or authority changes hands, and most AI security failures trace back to a boundary nobody enforced.
Model security protects the model itself from extraction, poisoning, and adversarial manipulation, while application security protects everything built around it.
Runtime protection for AI systems watches and enforces policy on live agent behavior in production, catching what pre-release testing cannot anticipate.
An AI security gateway sits between agents, models, and tools to enforce policy and record activity at runtime, complementing rather than replacing application-level controls.
Generative AI applications need layered controls across identity, tool scope, input and output handling, data protection, and monitoring, not a single guardrail.
Threat modeling an AI application means mapping trust boundaries around prompts, retrieval, memory, and tools, then asking what a compromised model could actually do.
AI security risks fall into five practical groups, model behavior, data exposure, tool and action risk, supply chain, and operational gaps, each needing different controls.
An AI application's attack surface spans prompts, models, retrieval, memory, tools, and the humans who operate it, not just the code a developer wrote.
Traditional application security remains necessary, but AI systems also require controls for prompt injection, model behavior, retrieval, memory, tools, and autonomous decisions.
AI security extends cybersecurity with controls for probabilistic behavior, natural-language attacks, model supply chains, sensitive context, and autonomous tool use.
AI security protects AI systems from misuse, manipulation, data exposure, unsafe actions, and failures that conventional software controls do not fully address.
