What the data for this category looks like
This category of data originates from private vulnerability reports, code repositories, CVE numbering bodies, and publicly released channels. Daily processed documents include security advisories, vulnerability reports, repair patches, and CVE application materials. Structurally, these documents contain fields such as vulnerability ID, impact scope, patch links, and disclosure time. Data updates are performed on a per-vulnerability-event basis, with one update completed each time a vulnerability disclosure process concludes. The core processing steps center on vulnerability impact assessment, patch preparation, and disclosure time coordination. All data is directly linked to the specific vulnerabilities of a single project.
Constraints imposed on the multi-turn dialogue and prompt engineering link
Private data sources require dialogue contexts to be strictly bound to a single vulnerability event, to prevent cross-event data leaks or confusion. The event-based update rhythm means multi-turn dialogue must focus exclusively on a single vulnerability workflow, with no irrelevant historical information included. Structured fields like CVE numbers and impact scope in documents require prompts to guide large models to extract them accurately, avoiding fuzzy scraping. The high-risk nature of vulnerability response requires multi-turn dialogue to confirm key parameters step by step, to prevent premature patch deployment or damage to project reputation from incorrect information.
Configuration Settings
The following configurations are based on FastGPT v4.17.0, and are tailored for the security vulnerability disclosure handling scenario.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Session Binding | Bind the chatId of a single vulnerability event | Ensure the dialogue context only associates with the current vulnerability disclosure process, avoiding cross-event data confusion |
| Context Window | Retain the most recent 2000 characters of messages | Focus on the report and patch information of the current vulnerability, preventing redundant data from interfering with large model output |
| Variable Extraction | Enable automatic extraction of variables | Extract key fields such as CVE numbers and impact scope from vulnerability reports and patch content |
| Multi-turn Guidance | Prompt for only 1 parameter to confirm per dialogue turn | Align with the step-by-step coordination rhythm of vulnerability disclosure, avoiding information overload |
| Session Timeout | Automatically terminate after 600 seconds of no response | Match the urgency of vulnerability response, preventing process blocking |
Three Common Misconfigurations
- Dialogue return results do not display associated patch screenshots or security advisory images. This happens because the prompt does not explicitly require converting linked images from the knowledge base into displayable formats, so the image rendering logic is not triggered.
- Extracted vulnerability key fields are missing or incorrect, such as inaccurate CVE number extraction. This happens because the
variablesconfiguration is not used to specify the range of fields to extract, leading the large model to scrape irrelevant information. - The same parameter is requested repeatedly in multi-turn dialogue, such as asking about the vulnerability impact scope multiple times. This happens because confirmed parameters are not marked in the dialogue workflow, resulting in context loss.
How to Verify the Configuration
- Manually input a simulated vulnerability report, and check whether the large model can accurately extract preset
variablesfields, such as CVE numbers and impact scope. - Test the session binding logic by switching the
chatIdof different vulnerability events, confirming that dialogue contexts do not interfere with each other. - Send test data containing image links, and check whether the large model can render image displays as required by the prompt.
- Simulate a multi-turn parameter extraction workflow, confirming that only one parameter to confirm is prompted per turn, with no repeated requests.
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.