An event-triggered AI agent is a synthetic subject whose runs are started by a system event rather than a direct conversational request. This may include a frontend action, webhook, queue item, form submission, file drop, inbound email, application event, or record arriving in a data pipeline.

This deployment pattern creates an elevated exposure condition because the person or system that triggers the run may be different from the person who controls the input. The agent may run with a standing application identity and access to customer records, ticket queues, internal documents, communications, or pipeline data, while the event content may originate from an external or low-trust source.

The primary risk is event-driven indirect prompt injection. Form fields, payloads, queued rows, uploaded files, or inbound messages may contain instructions that the agent treats as task context. A malicious instruction can therefore be planted by a malicious individual and executed later when the workflow processes the item.

A related risk is unattended repetition. Event-triggered agents often process backlogs, queues, or recurring inputs without a human reviewing each run. A poisoned input or flawed directive may produce harmful outputs at machine speed while appearing to be normal workflow throughput.

Investigators should review the agent’s directive, trigger conditions, event payloads, queue records, service identity, workflow permissions, input sources, run history, tool calls, output destinations, and downstream actions. Particular attention should be given to externally controlled fields, repeated adverse outcomes across similar records, and logs that fail to show which input content caused the agent’s action.

Investigative Relevance

Event-triggered AI agents are relevant because they decouple human oversight from agent execution. The run may be authorized by the workflow, while the effective instruction is supplied through data controlled by an external party, customer, vendor, compromised account, or low-trust source.

This section is especially relevant where agents process public forms, inbound webhooks, emails, file uploads, watched folders, customer relationship management records, ticket queues, data pipelines, or application events without human review before action.

Directive

Autonomous AI Agent

Embedded AI Feature

Event-Triggered AI Agent

Internal AI Assistant

Misaligned Directive

Public-Facing Conversational AI

Directive

Sections (6)