Event-Triggered AI Agent

A batch processing trigger occurs when an agent or model processes queued rows, files, records, or items in a scheduled data pipeline. This may include Extract, Transform, Load (ETL) jobs, bulk classification runs, document processing queues, ticket enrichment, record summarization, or scheduled workflow automation.

This deployment pattern creates an elevated exposure condition because each item is processed without per-item human review. A single poisoned row, file, record, or queued item may enter the model’s context and influence the run while appearing to be ordinary batch input.

The primary risk is hidden manipulation inside routine throughput. Because the run is bulk and scheduled, a tampered item may be difficult to distinguish from normal processing. If the agent has broad pipeline permissions, one poisoned record may trigger outputs, updates, classifications, external calls, or downstream actions across the job’s full data scope.

Investigators should review the pipeline directive, schedule, input queue, source records, transformation logs, model outputs, tool calls, downstream writes, error handling, and affected data scope. Particular attention should be given to anomalous individual records, repeated harmful outputs across a backlog, externally sourced rows or files, and changes that occurred without per-item approval.

Investigative Relevance

Batch processing triggers are relevant because they allow a synthetic subject to act across many records at machine speed with limited human visibility. A harmful instruction or manipulated input may be hidden inside otherwise normal pipeline activity.

A user action trigger occurs when an action in an application interface starts an agent run. This may include submitting a form, clicking a button, saving a record, uploading a file, updating a field, or completing another workflow step.

This deployment pattern creates an elevated exposure condition because the action that starts the run may not be the same as the content that shapes it. The agent may process free-text fields, attachments, comments, descriptions, or uploaded records as task context, even where that content was supplied by an external or low-trust submitter.

The primary risk is delayed execution of injected content. A malicious instruction may be planted in a frontend field or submitted record, then executed later when an internal employee opens, reviews, routes, or processes the item. The run may execute under the application, workflow, or employee identity, while the effective instruction came from the external submitter.

Investigators should review the trigger action, submitted fields, attachments, record history, user identity, workflow permissions, agent run logs, tool calls, and downstream actions. Particular attention should be given to free-text fields, externally supplied content, and cases where an internal user triggered processing of a record created or modified by someone else.

Investigative Relevance

User action triggers are relevant because they allow external or low-trust content to influence an agent run through normal application behavior. The employee may appear to have initiated the run, but the instruction path may originate in submitted data.

This sub-section is especially relevant where agents process web forms, customer relationship management records, support tickets, uploaded files, comments, case notes, lead forms, application records, or other frontend-supplied content.

A webhook event trigger occurs when an inbound event from another system automatically starts an agent run. This may include a new ticket, inbound email, status callback, chat application event, customer relationship management update, or other webhook-driven workflow.

This deployment pattern creates an elevated exposure condition because the agent may run without a human reviewing the event first. The event payload may contain free text, metadata, links, attachments, or structured fields that the synthetic subject treats as task context.

The primary risk is attacker-shaped event input. Public or weakly authenticated endpoints may allow an external actor to forge, replay, or manipulate event payloads. A single malicious event may then trigger downstream actions, such as ticket routing, message generation, record updates, external calls, or tool execution, before anyone notices.

Investigators should review the event source, webhook authentication, payload content, replay protections, trigger rules, agent run logs, tool calls, downstream actions, and output destinations. Particular attention should be given to forged or repeated events, unusual payload fields, newly observed sources, and actions that exceed the normal event workflow.

Investigative Relevance

Webhook event triggers are relevant because they allow external or third-party system events to initiate agent behavior without direct human oversight. The workflow may appear routine, while the effective instruction is carried in the event payload.

This sub-section is especially relevant where agents process inbound webhooks, status callbacks, chat events, ticket events, email events, customer updates, integration messages, or other automated triggers from public, partner, or weakly trusted systems.