What the Data for This Category Looks Like
Data for this category primarily comes from SIEM, EDR, firewall logs, and host images. Update frequency is real-time or triggered per individual security incident. Daily produced documents include emergency response reports, forensics records, disposal plans, and notification materials. Data fields include event unique identifier, attack source address, disposal action timestamp, evidence chain hash value, and compliance check items. No preset statistical units are used; data is only associated and archived by event dimension.
What Constraints These Characteristics Impose on Workflow Orchestration
Scattered data sources and flexible update rhythms require workflow orchestration to support parallel pull nodes for multi-source logs and images. This avoids overall process blocking caused by single-node processing delays. The document structure associated by event requires the workflow to bind the event ID parameter in variables. This ensures the context only covers data related to the current event, preventing cross-event data interference. Diverse document types and compliance requirements require the workflow to include a format verification node. This ensures field completeness for disposal plans and notification materials. Consequences of errors include data leaks and business outages, so the workflow must be configured with failure rollback and alert branches. This prevents expansion of impacts from disposal mistakes.
Configuration Settings
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind current event ID, log source type, evidence chain storage path | Ensure the workflow only processes data associated with the current security incident, avoiding cross-event context contamination |
| Trigger Timing | Start 10 seconds after SIEM alert is generated | Wait for complete log collection to avoid pulling incomplete original event data |
nodeId | Assign unique identifiers to log pull, format verification, and alert nodes | Facilitate workflow debugging and quick location of failed nodes |
| Failure Retry Count | 3 times, 60 seconds interval each | Address temporary log pull or API call failures, avoiding excessive retries that cause disposal delays |
| Maximum Context Entries | Top 20 event-associated logs | Cover complete log data required for attack path restoration, while avoiding context overload |
| Output Format | Adapt to fixed field structure for emergency response reports | Match daily document archiving and review requirements |
Three Common Configuration Mistakes
- Phenomenon: Only 2 context entries are displayed after workflow execution, even though 30 context entries are configured. Cause: The event context parameter in
variablesis not correctly bound to the AI node, causing the system to load a small amount of historical conversation context by default. - Phenomenon: The workflow cannot loop through the code review verification step, and cannot trigger regeneration or termination of the process based on review results. Cause: The loop trigger condition is not correctly configured, and the review result field in
variablesis not bound as the loop judgment basis. - Phenomenon: Uploaded forensics image files cannot be directly passed to the large model node, and can only be parsed into incomplete text content. Cause: File direct transfer configuration is not enabled, and the binary file is parsed into text by default before being passed in, resulting in loss of original image data.
How to Verify Correct Configuration
- Manually trigger a test workflow, check whether the
variablesparameters in the node logs include the correct identifier and associated data of the current event. - Check the context display area of the AI node, confirm that the number of loaded context entries matches the configured maximum context entries.
- Simulate a single failure scenario, check whether the workflow triggers the retry mechanism and generates a failure alert.
- Export the test document output by the workflow, confirm that the format matches the preset emergency response report structure.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.