What the data for this category looks like
This category's data primarily comes from WAF, IDS, firewalls, and threat intelligence platforms. Update frequency is daily or triggered by protection events. Daily associated documents include rule change tickets, blocking logs, false positive analysis reports, and policy rollback records. Each record contains core fields such as rule ID, effective time, blocking hit count, and false positive rate. There is no unified fixed format, and differences exist based on the configuration of different protection products.
What constraints these characteristics impose on the "workflow orchestration" link
Differing log formats across protection products mean workflows must support multi-source data format adaptation and field extraction. Updates triggered daily or by events require workflows to have flexible trigger nodes, supporting scheduled execution or event callback startup. The non-standardized nature of document fields requires workflows to include built-in variable extraction rules that support target data with different field names. Additionally, the highly time-consuming links of false positive analysis and rule gray release require workflows to embed manual review and batch execution nodes, preventing excessive single-execution load that disrupts normal business processes.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Trigger mode | Triggered by protection events, or execute daily at 2:00 AM | Adapt to the rhythm of data updated by events or daily, avoid repeated execution or delayed processing |
variables | Extract rule ID, blocking hit count, false positive rate fields | Match the core field requirements of daily documents, support subsequent rule review and adjustment |
| Node timeout | 600 seconds | Cover the execution duration of complex false positive analysis and rule verification, avoid mid-execution interruptions |
| Retry strategy | First 2 retries with 120-second interval, terminate execution on the 3rd attempt | Address temporary network fluctuations or brief unavailability of data sources |
| Approval node permissions | Bind the security operations engineer role | Ensure rule changes require authorization, comply with security operation specifications |
| Result output path | Write to the specified policy rollback record document | Retain workflow execution results for subsequent auditing and traceback |
Three Common Misconfigurations
- The symptom is an error "localStorage is not defined" returned when the workflow executes a code node. The cause is that the FastGPT workflow code execution environment does not provide the browser-side localStorage object, and direct invocation will trigger an exception.
- The symptom is that the full URL of the shared application cannot be obtained in the workflow. The cause is that the workflow context variable extraction is not configured correctly, and the request parameters or environment variables at application startup are not bound.
- The symptom is that the custom prompt and reference template configuration items in the workflow cannot be displayed. The cause is that the current FastGPT version is lower than v4.9.7. This function is gradually rolled out in subsequent versions. It is recommended to use FastGPT v4.17.0 or higher to obtain complete functions.
How to Confirm Proper Configuration
- Trigger a test execution, check if the workflow logs contain expected fields such as rule ID and blocking hit count, confirm that the
variablesvariable extraction configuration is effective. - Simulate a protection event to trigger the workflow, check whether the execution completes within the configured timeout period without abnormal interruptions.
- Verify that the approval node only allows users with the specified role to operate, confirm that the permission configuration is correct.
- View the policy rollback record document, confirm that the workflow execution results have been correctly written, and confirm that the output path configuration is correct.
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.