What data for this category consists of
Data for this category primarily comes from WAF, IDS, firewalls, and threat intelligence platforms. Updates occur daily or when a protection event triggers. Daily output documents include rule change tickets, intercept logs, false positive analysis reports, and policy rollback records. Document fields include rule ID, effective time, intercept features, false positive sample hash values, rollback version numbers, and additional items. No unified fixed units exist; values adjust based on specific protection scenarios. Security operation engineers, WAF/IDS product administrators, and SOC teams perform core work focused on maintaining protection policies and rule sets.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
These data characteristics impose multiple constraints on multi-turn dialogue and prompt engineering configurations. Decentralized data updated per event requires multi-turn dialogue flows to support real-time pulling of the latest intercept logs and threat intelligence, and avoid using expired rule data. Unstandardized document fields require prompt engineering to adapt to field structures across different protection scenarios, reducing parsing error probability. The high time cost of false positive analysis and gray release requires multi-turn dialogue to support retrospective of historical context via rule ID and effective time, to assist rule review. Severe consequences of incorrect protection policy changes require prompt engineering to include a risk verification step, ensuring the rigor of rule configuration. Stable delivery of dialogue context is also required, preventing loss of historical dialogue information.
How to set configurations
The following configurations are formulated based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
messages | An array containing user input, historical replies, and rule datasets | Adapts to the context delivery needs of multi-turn dialogue, ensuring historical interactions and current rule data are fully included |
chatId | A unique identifier bound to the current rule operation task | Used to associate dialogue context with specific rule change or false positive analysis tasks, avoiding context confusion |
| Maximum context length | 8000–12000 characters | Adapts to the typical length of documents such as rule change tickets and intercept logs, preventing truncation of critical protection rule information |
| Number of historical dialogues to retain | First 10 entries | Balances context completeness and inference efficiency, matching the information volume of single tasks in this category |
variables | Inject exclusive fields such as current rule ID, intercept feature values, and rollback version numbers | Used to dynamically replace placeholders in prompt engineering, adapting to rule configurations across different protection scenarios |
| Risk verification trigger switch | Enabled | A risk verification step must be added in rule change-related dialogue, matching the constraint of severe consequences from protection policy change errors |
Three common mistakes
- Phenomenon: When calling the rule analysis node, historical dialogue is not correctly included, and the prompt engineering does not read past false positive analysis records. Cause: The
chatIdparameter is not correctly bound, leading to no association between dialogue context and the task, resulting in loss of historical dialogue data. - Phenomenon: Context truncation errors occur during dialogue, or returned rule suggestions lack key fields. Cause: The maximum context length is set too small, truncating long document content such as rule change tickets and intercept logs.
- Phenomenon: Rule configuration suggestions returned by dialogue do not trigger risk verification, and change instructions are generated directly. Cause: The risk verification trigger switch is not enabled, and no risk verification step is added to the prompt engineering, failing to avoid misoperation risks.
How to confirm configurations are complete
- Manually trigger a rule change-related dialogue, check the dialogue context panel, and confirm that historical false positive analysis records and intercept log data are fully included.
- Enter a query containing rule ID and intercept features, check whether exclusive fields are dynamically replaced in the returned results, matching the rule information of the current task.
- Trigger a dialogue flow that includes risk verification, confirm that the returned results contain prompts or steps related to risk verification.
- Check the dialogue log, confirm that the
messagesparameter includes all current and historical interaction content, with no missing items.
The values provided here are common starting points, and should be evaluated 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.