What this category of data looks like
Data for this category primarily originates from source code repositories, dependency lists, static code scanning tools, and public vulnerability databases. Updates are completed alongside code version releases or within project audit cycles. Daily deliverables include code audit reports, vulnerability proof materials, repair recommendation documents, and retest records. Common fields include vulnerability identifiers, risk levels, affected code scopes, repair statuses, and retest verification results. There is no unified mandatory format, and content adjusts based on audit project requirements. FastGPT v4.17.0 and later versions support pulling this type of data via integrated interfaces.
What constraints do these characteristics impose on HTTP interfaces and external systems
Because data sources for this category are scattered and there is no unified data format, HTTP interfaces must support multi-type input parsing and custom field mapping to adapt to the report structures of different audit projects. Data updates are tied to code versions or audit projects, so interfaces must support filtering and pulling data by project identifier and version number to avoid redundant full-volume requests. Since data contains high-risk vulnerability information, interface authentication must be independent of basic application permissions. The volume of data returned in a single request must also be limited to prevent batch leakage of sensitive information. Additionally, the need for incremental updates to retest records requires interfaces to support incremental pulling logic based on timestamps or update statuses.
How to configure settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Authorization | Bearer format string carrying AI Proxy administrator Token | Used for interface identity verification, compliant with FastGPT server authentication requirements |
variables | Custom parameter set containing project ID and version number | Used to filter audit report data for the corresponding code version |
responseData | Custom structure mapped to vulnerability identifiers, risk levels, and repair statuses | Adapts to code audit report formats from different sources |
| Single request data limit | Top 100 records | Prevents batch return of sensitive vulnerability information, adapts to interface transmission limits |
| Request timeout | 600 seconds | Covers parsing and pulling time for complex audit reports |
Three common misconfigurations
- Phenomenon: Duplicate historical audit records appear in operation reports returned after calling the interface. Cause: Incremental pulling logic is not configured, and full data is pulled with each request, resulting in duplicate entries.
- Phenomenon: The interface returns status code 401, and code audit reports cannot be pulled. Cause: The application API Key is mistakenly used instead of the AI Proxy administrator Token as the authentication parameter, and server environment variable configuration requirements are not followed.
- Phenomenon: When calling the interface in stream mode, the final release note summary result cannot be obtained correctly. Cause: Segmented streaming response data is not handled properly, and complete content splicing is not completed.
How to confirm the configuration is correct
- Check that AI Proxy-related environment variables in the App/Admin server have been correctly configured, and authentication parameters are not repeatedly filled in the application layer or workflow.
- Initiate a test request to verify that fields returned by the interface match the preset
responseDatamapping rules, with no missing key audit information. - Simulate an incremental pull request to confirm that only updated data within the specified time range is returned, with no duplicate entries.
- Check the interface response status code to confirm no abnormal statuses such as 401 or 500, which aligns with authentication and processing logic.
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.