What the data for this category looks like
Core data for penetration testing services originates from target systems, public vulnerability databases, automated scanner results, and manual verification records. Updates align with individual test projects or major version iterations. Daily deliverables include test authorization letters, penetration test reports, vulnerability recurrence records, and remediation recommendations. Fields include vulnerability severity, CVSS scores, recurrence steps, impact scope, and repair solutions. CVSS scores use a 0-10 scale. Vulnerability counts are recorded as integers. Recurrence records use structured text format.
What constraints these characteristics impose on workflow orchestration
Scattered, varied-format data sources for penetration testing services require workflows to support multi-source data pulling and format conversion. Updates follow individual project or major version completion timelines, so on-demand triggering is needed to match project progress. Errors can lead to business interruptions and legal risks, so failure retries and pre-check links must be configured. Standardized report generation requires fixed field mapping rules to prevent chaotic aggregated data formats. Processes combining manual verification and tool scanning need flexible orchestration of serial and parallel nodes.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Trigger Node Configuration | Trigger on project completion node output, 1 time/project | Matches the project-based update rhythm of penetration testing |
| Variable Binding Configuration | Bind authorization letter ID and vulnerability scan result path from variables | Associates unique test authorization and scan data sources for this category |
| Loop Node Configuration | Traverse vulnerability recurrence record array, process 1 item/loop | Adapts to the serial processing logic of single vulnerability verification |
| Failure Retry Configuration | Retry 2 times, interval 30 seconds | Addresses scanner interface fluctuations or manual data staging delays |
| Output Node Configuration | Associate report generation node via nodeId | Ensures aggregated data flows to the correct document generation link |
| Server Environment Variables | Set AIPROXY_API_ENDPOINT and AIPROXY_API_TOKEN during deployment | AIPROXY_API_ENDPOINT is the root address of the AI Proxy service. AIPROXY_API_TOKEN is the AI Proxy administrator token and cannot be empty. Do not use application API keys, model vendor keys, or similar alternatives. Meets dependency requirements for FastGPT v4.17.0 and above |
Three common configuration mistakes
- Symptom: External service messages spliced by loop nodes return empty content. Cause: No variable cache node is configured, so only the last loop result is read during splicing.
- Symptom: Database results queried via DB nodes cannot be directly used for report generation, and field formats are abnormal. Cause: No result parsing rule is configured via
variables, directly using the original JSON array causes field mapping failures. - Symptom: Default values of form input nodes cannot reference global variables. Cause: Variables are not bound to the corresponding form configuration items, directly filling variable names in the default value field does not trigger parsing.
How to confirm the configuration is complete
- Trigger a test project workflow, check node logs to confirm that variables such as authorization letter ID and scan result path have been loaded correctly
- Simulate high-concurrency calls (such as 2-3 times per second) to check whether external service node return results are normal and have no empty values
- Verify that the spliced content output by the loop node matches all vulnerability recurrence records
- Check FastGPT service startup logs to confirm that
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENconfigurations are valid, with no startup verification failures
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.