Agent Security

AI agent security is the practice of protecting autonomous and semi-autonomous AI agents and the systems they access. It covers discovering where agents run, giving each agent its own identity, controlling what it can access, and monitoring its actions so that agents operate safely as accountable members of the workforce.

Agents act independently: they call APIs, read data, and trigger workflows. When they borrow a human’s credentials or a shared service account, their actions can’t be attributed, scoped, or revoked on their own. A distinct identity for each agent makes it possible to enforce least privilege and keep a clear audit trail.

Discovery combines scanning cloud platforms, SaaS applications, developer tools, and MCP servers for agent activity, API keys, OAuth grants, and tokens. The goal is a continuously updated inventory showing each agent, its owner, what it can reach, and how it authenticates.

Common risks include over-permissioned agents, long-lived static credentials, agents inheriting a user’s full access, unclear ownership, and prompt injection that steers an agent into misusing legitimate permissions. Because agents act at speed and scale, a single misconfigured agent can cause outsized impact.

Scope each agent to the minimum permissions its task requires, issue short-lived credentials instead of static keys, require human approval for sensitive actions, and route tool access through a policy-enforcing gateway. Log every action back to the agent and its accountable owner.