What data looks like for this category
Vulnerability scanning service data primarily comes from vulnerability scanners, asset inventories, CVE databases, and patch announcements. Update frequency is weekly or monthly. Daily produced documents include scanning plans, vulnerability lists, rectification work orders, and rescan reports. Core fields include asset IP addresses, vulnerability CVE numbers, risk levels, repair statuses, and rescan results. The content length of a single document typically ranges from hundreds to thousands of characters. Clear relational links exist between fields; for example, a vulnerability list must be bound to corresponding scanning plans and asset information.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
Data sources are scattered and have different update cycles. Multi-turn dialogue is needed to gradually confirm asset scope and scanning targets, avoiding missing critical assets. There are many document fields with close relational links, so prompts must guide extraction and association of corresponding fields to prevent data misalignment. The false positive elimination and rescan result verification steps require comparison with historical data. Limited dialogue context must be retained to avoid redundant information interfering with core processes. The document volume for a single task is large, so the processing length of single-turn prompts must be limited to prevent exceeding model context thresholds.
Configuration settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum single-turn prompt length | 800–1200 characters | Matches the typical length of single-segment content from vulnerability scanning documents |
| Context window size | First 10 dialogue history entries | Adapts to the relational needs of weekly updated scanning plans and rescan reports |
variables variable binding | Bind asset inventory and CVE database path | Automatically populate standardized, category-specific data fields |
chatId session identifier | Bind single scanning task ID | Isolate dialogue contexts for different scanning tasks to avoid data cross-contamination |
messages historical context | Retain the most recent 3 rounds of vulnerability troubleshooting dialogues | Focus on core processes of false positive elimination and rescan verification |
| Multi-turn dialogue trigger condition | Trigger at the asset scope confirmation node | Avoid initiating redundant dialogue in non-essential links |
Three common mistakes
- Phenomenon: Irrelevant knowledge base content is introduced when calling dialogue. Cause: The processing scope of the prompt is not limited to vulnerability scanning-specific documents, causing non-target data to be mixed into the context.
- Phenomenon: A single dialogue triggers prompts multiple times. Cause: No execution upper limit is set for single-turn prompt calls, leading to repeated calls to plugins or knowledge base resources.
- Phenomenon: Empty asset or vulnerability fields are returned in dialogue. Cause:
variablesare not bound correctly, making it impossible to automatically populate required fields such as asset IP addresses and CVE numbers.
How to confirm configurations are correct
- Initiate multi-turn dialogue for asset scope confirmation, check that returned content only includes specified fields from scanning plans and asset inventories, with no irrelevant data.
- Trigger a single vulnerability troubleshooting dialogue, review logs to confirm only one prompt call is executed, with no duplicate request records.
- Import test scanning task data, check that automatically populated
variablesin dialogue fully match the source test data. - Switch the
chatIdof different scanning tasks, confirm that dialogue contexts for the two tasks are isolated from each other, with no data crossover.
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.