What the data for this use case looks like
Security incident emergency response data originates from SIEM, EDR, firewall logs, and host images. Updates happen in real time or are generated per incident. Daily produced documents include emergency response reports, forensics records, disposal plans, and notification materials. These documents follow a fixed structure that includes incident identifiers, attack paths, disposal steps, and evidence chain information. Fields include incident number, affected asset IP, disposal duration, and evidence hash value. Most corresponding units use string format, IP address format, time units, and byte units. All data is updated when the incident closes, with no redundant retention.
What constraints these characteristics impose on forms and interactions
Diverse data sources and varying structures require fast mapping and entry of structured log fields, implemented via external business systems or workflow configurations. High update frequency requires a draft saving mechanism using external storage or workflow context to prevent content loss. Fixed document structure requires preset input fields for corresponding entries in the form to avoid non-standard input. Evidence chain fields must resist tampering, requiring hash value format verification implemented via external business systems or subsequent nodes. Affected asset fields are prone to manual input errors, requiring compliant options for affected assets provided by an external asset library, filled via external API calls. Sensitive fields must restrict access permissions to prevent expanded leakage of sensitive data.
How to configure
All configurations below are based on FastGPT v4.17.0.
| Configuration Item | Recommended Practice | Rationale |
|---|---|---|
Form Input Node formInput | Test example: Select 3 fields from security incident emergency response fields as required inputs; actual fields are determined per task | This node collects user input; missing required items require checking interaction status to avoid subsequent nodes failing to receive complete input |
User Selection Node userSelect | Test example: Set 2 business options, check corresponding branches individually | This node handles user selection; queries and filtering of security incident emergency response records must be implemented via subsequent APIs or external systems |
| Field Passing After Submission | Test example: Prepare 10 security incident emergency response input samples, covering complete filling, missing required items, and cancel operations | Compare input and node output to verify if subsequent nodes receive corresponding fields; result thresholds are determined per actual task |
| External Implementation: Draft Saving Duration | Must be implemented separately by external systems; use external storage or workflow context, recommended setting is 600 seconds (test example) | Data updates in real time; prevents loss of content left unsubmitted for extended periods |
| External Implementation: Field Required Validation | Must be implemented separately by external systems; set incident ID, disposal time, and evidence hash as required | Ensures core fields of emergency response documents are complete |
| External Implementation: Auto-Save Trigger | Must be implemented separately by external systems; use external storage or workflow logic, recommended trigger condition is every 100 characters entered (test example) | Adapts to high-frequency real-time data entry scenarios |
Three Common Misconfigurations
- Symptom: The large language model selection dropdown only displays overseas model options, with domestic models such as Qianwen, Tongyi not appearing. Verification step: Check if the platform has configured access keys and interface addresses for domestic large language models.
- After a security incident emergency response form is submitted, subsequent nodes do not receive complete fields. Compare required items, actual submitted content, and node output mappings one by one, then check subsequent API returns; existing symptoms cannot independently identify the root cause.
- Symptom: Unable to call the large language model web search tool to supplement forensics information. Verification steps: 1. Check if the large language model configuration has enabled the web search tool; 2. Check if the workflow has configured a tool call node.
How to Confirm Configuration is Complete
- Import SIEM logs, then check if form input items match SIEM log fields (field mapping must be implemented via external business systems or workflow configurations).
- Attempt to open the large language model selection dropdown, confirm if domestic large language model options load.
- Access permissions for sensitive fields are controlled via external business systems or workflow permission configurations; verify unauthorized account access via the corresponding permission system.
- Enter content exceeding 200 consecutive characters, check if external storage or workflow context saves drafts at the set interval.
The values provided here are common starting points, and should be evaluated 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.