How AgentTrust limits risk in autonomous AI systems
Agents are autonomous, long-running, and capable of taking actions across many systems with minimal oversight. When they fail, they often fail quietly-and impact can accumulate before anyone notices.
AgentTrust is built to govern actions before they execute. Not prompts. Not reasoning quality. This page outlines threats we mitigate-and boundaries we intentionally do not cross.
AgentTrust assumes agents can be manipulated or compromised. The loop ensures failures remain bounded, attributable, and provable.
- • Agents run continuously
- • Tools chain into tools
- • Credentials outlive intent
- • “Looks normal” abuse accumulates
Threats we’re designed to address
These threats are mitigated by enforcing explicit intent, bounded scope, time limits, and audit-grade evidence at the moment of action.
Agent identity spoofing
An agent, tool, or service claims an identity or privilege level it does not possess.
Many agent stacks infer trust from context. Identity becomes implied instead of enforced at execution time.
AgentTrust authorizes only policy-backed actions and validates a scoped session before execution. Self-asserted identity does not execute.
Long-horizon / delayed-execution attacks
An agent behaves benignly then escalates over hours/days (enumeration, staged changes, delayed destructive steps).
Long-lived credentials and no enforced mission duration allow quiet escalation outside review windows.
AgentTrust issues time-bound sessions. When a session expires, intent must be re-declared and re-evaluated. This limits blast radius.
Privilege creep during execution
An agent starts with limited access and gradually expands privileges through tool chaining or implicit scope growth.
Permissions are often coarse and static for the lifetime of the agent.
Scope is defined at decision time and enforced for the session duration. Scope cannot expand without a new policy decision (and approval if required).
Unregistered / shadow agents
New agents or automations appear without visibility, review, or governance.
There is no centralized enforcement point across frameworks and tool boundaries.
AgentTrust is the pre-execution decision point. Actions that don’t pass through policy evaluation are not authorized to execute.
Threats we do not attempt to solve
AgentTrust is intentionally scoped. Some risks require different layers of control.
Prompt injection
Prompt security is model- and application-level. AgentTrust assumes agents may be manipulated and focuses on limiting the impact of resulting actions.
Hallucinations or reasoning errors
AgentTrust enforces authorization, not correctness. It bounds what can happen when reasoning fails.
Insider abuse with legitimate approval
Human approval is a trust boundary. AgentTrust provides attribution, auditability, and replayability rather than prevention.
Downstream system vulnerabilities
AgentTrust controls who can act, for how long, and with what scope. It does not replace patching or hardening downstream systems.
Pairs well with
AgentTrust is a control layer, so it relies on adjacent safeguards to close the loop.
- • Prompt injection defenses (app-level)
- • Data loss prevention / downstream data controls
- • Vulnerability mgmt / hardening for target systems
- • Identity controls (SCIM/OIDC/OAuth patterns)
Design principle
AgentTrust assumes agents may hallucinate, be manipulated, behave unexpectedly, or be compromised. The goal is not perfect agents. The goal is safe operation at scale.