What Data Looks Like for This Category
Data sources for cybersecurity research reports include public vulnerability disclosure documents, technical analysis reports from industry security vendors, cybersecurity bulletins released by regulatory agencies, and offensive and defensive drill materials from open-source communities. Update frequency adjusts based on event urgency. Vulnerability-related content updates in real time. Industry analysis reports release on a quarterly or monthly basis. Document structures typically include fields such as vulnerability identifiers (e.g., CVE-ID), affected asset types, CVSS risk scores, attack vectors, remediation solutions, and affected versions. Units include CVSS score ranges, asset quantity units, and timestamp formats.
What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering
The precisely structured fields and high-frequency update characteristics of cybersecurity research reports require multi-turn dialogue to retain independent context for each individual question. Merging context can cause accurate matching to fail. Long-form technical details require prompts to limit retrieval scope. Only uploaded research report data may be used. Fabricating unmentioned content is prohibited. The multi-field structured characteristics require prompts to prioritize extracting core fields such as CVE identifiers and risk levels. This improves the relevance of responses. High-frequency updated content requires the dialogue system to recall the latest data in real time. Using expired cached content must be avoided.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000-12000 characters | Cybersecurity research reports contain extensive technical details and long text passages. This range covers core content for most individual reports, and avoids exceeding model context windows |
recallTopK | Top 6-10 results | Cybersecurity scenarios have high requirements for retrieval accuracy. Too many recalled results introduce irrelevant information. This range balances retrieval coverage and relevance |
temperature | 0.1-0.3 | This value range reduces randomness in generated content. It ensures responses strictly follow factual information from research reports, and avoids technical misinformation |
pluginTimeout | 600 seconds | Cybersecurity research reports may include large vulnerability analysis documents. This duration covers retrieval and parsing time for most scenarios |
multiRoundMemoryWindow | Last 3 conversation turns | Contextual relevance is strong for cybersecurity-related questions. Limiting to the last 3 turns avoids interference from redundant historical information on current retrieval |
enableRerank | Enabled | Research report content is highly specialized. Reranking further optimizes the order of recalled results based on semantic similarity |
The parameter values provided on this page are general recommendations used as starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. Testing on independent samples is recommended before finalizing settings.
Three Common Misconfigurations
- Symptom: Individual content from a single user question cannot be retrieved during multi-turn dialogue. Only merged context is available. Cause: The
multiRoundMemoryWindowparameter is not configured, or context isolation storage for individual questions is not enabled. - Symptom: The temperature parameter setting entry is not displayed in the large model configuration interface. Adjusting generation randomness is not possible. Cause: Advanced configuration mode is not activated, or a model calling component that supports custom parameters is not selected.
- Symptom: Dialogue call duration exceeds 600 seconds, and the model call group count is only 1. Cause: The
pluginTimeoutparameter setting does not match the actual time required for research report parsing, or the timeout retry mechanism for database connection plugins is not configured, causing retrieval process blocking.
How to Verify Successful Configuration
- Initiate a test dialogue with 2 to 3 rounds of follow-up questions. Check the
userQueryfield in the dialogue log. Verify that each round of question content is independently identified. - Access the advanced panel of the large model configuration. Check the current value of the
temperatureparameter. Confirm that it matches the preset configuration. - Initiate a test with a long-text question. Check the duration field in the interface log. Confirm that the response time does not exceed the preset threshold of
pluginTimeout. - Test the calling process for database connection plugins. Check the return fields in the plugin call log. Confirm that research report data is properly pulled and parsed.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.