What Data for This Category Looks Like
Data for this category comes from private vulnerability reports, code repositories, CVE numbering bodies, and official release channels. Daily documents include security advisories, vulnerability reports, fix patches, and CVE application materials. Each entry is associated with a specific vulnerability event, and contains fields such as vulnerability ID, impact scope, fixed version, and disclosure coordination records. Data updates are triggered per individual vulnerability event, with no fixed cycle. Content is only added or modified during the full lifecycle of an event, and some content involves internal sensitive project information, so access permissions must be strictly controlled.
Constraints Imposed on Knowledge Base Retrieval and Recall
The data characteristics of this category impose multiple constraints on the retrieval and recall process. First, the source of sensitive data requires that recall results be strictly limited to authorized access scopes, to avoid leaking internal vulnerability coordination information. Event-driven update rhythms require the knowledge base to support incremental synchronization without fully rebuilding indexes, to adapt to the sudden update needs of vulnerability events. Diverse document structures require the retrieval system to adapt to multiple formats including text, code snippets, and structured tables, to ensure that different types of vulnerability documents can be effectively recalled. The field feature where each entry is bound to a specific vulnerability requires that retrieval must use precise filtering based on vulnerability ID, impact scope, and other fields, to avoid mixing irrelevant content across events. The rapid response requirement in operations on-duty scenarios requires that the relevance and timeliness of recall results meet high standards, to reduce the screening workload for on-duty personnel. If recall results contain errors, it may lead to incorrect impact assessments or disclosure coordination, resulting in damaged project reputation or user exposure to attacks.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Semantic matching for vulnerability-related content requires a high threshold to avoid mixing documents from unrelated vulnerabilities, adapting to the precise retrieval needs of security scenarios. This parameter is supported in FastGPT v4.17.0 |
limit | Top 3–5 results | Operations on-duty personnel need to quickly view core relevant vulnerability handling records. Too many results increase screening workload, aligning with rapid response scenario requirements |
searchMode | Hybrid vector retrieval + keyword search | Vulnerability documents have both semantically related processing workflows and clear keywords such as CVE numbers and vulnerability names. Hybrid mode improves recall accuracy |
usingReRank | Enabled | Further filter the most matching vulnerability handling solutions from multiple recall results, avoiding redundant information interfering with on-duty personnel's judgments |
datasetSearchUsingExtensionQuery | Enabled | Vulnerability IDs and impact scope can be used as extended query terms to enhance precise recall effects, adapting to the field characteristics of this category of data |
collectionIds | Specify exclusive collection ID for the vulnerability knowledge base | Isolate dedicated data for this category, avoiding mixing documents from other projects, and ensuring retrieval results only relate to the currently processed vulnerability event |
Three Common Misconfigurations
- Symptom: After a PDF vulnerability report is uploaded, the file's content does not appear in knowledge base retrieval results. Cause: The PDF structured recognition function is not enabled, or the file is encrypted or uses a non-standard format, preventing extraction of core fields such as CVE numbers and fix patches.
- Symptom: When a vulnerability-related query is submitted, the returned results do not include internal vulnerability handling processes from the local knowledge base. Cause:
collectionIdsis not specified as the vulnerability knowledge base exclusive collection, or the configuredsimilaritythreshold is too high, filtering out relevant content. - Symptom: The number of returned retrieval results does not match the configured
limit, or a large number of vulnerability documents from other projects appear. Cause:collectionIdsis not correctly configured to limit the exclusive collection, or thelimitparameter value is not adjusted, resulting in an unexpected recall scope.
How to Verify Proper Configuration
- A test vulnerability report PDF is uploaded, and a query containing the corresponding vulnerability ID is submitted to verify that the document content can be recalled.
- The knowledge base configuration panel in FastGPT v4.17.0 is reviewed to confirm that
collectionIdsis specified as the vulnerability knowledge base exclusive collection, and thesimilaritythreshold falls within the 0.75–0.85 range. - Multiple different vulnerability-related queries are submitted to verify that the number of returned results matches the range configured by
limit, and no documents from other projects are included. - After
usingReRankis enabled, the reordered results are checked to confirm they are sorted by semantic relevance, prioritizing the most matching vulnerability handling solutions.
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.