How do I fix the high false positive rate in our current Darktrace alerts before the audit tomorrow morning?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
How do I fix the high false positive rate in our current Darktrace alerts before the audit tomorrow morning?
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 2 queries…
Searches and sources
ChatGPT2 real searches · gpt-6
Darktrace documentation tuning model alerts false positives score thresholds exclusions audit model breach triage Google ↗
Darktrace official documentation model tuning alert management false positives tuning guide Google ↗
- Optimizing Darktrace Operations | Resources · darktrace.com
- Darktrace Threat Visualizer User Guide | PDF | Computer Network · scribd.com
- Product Specification: Darktrace DETECT/Network · manuals.plus
- Darktrace Threat Visualizer: User Guide V5.2 · pdfcoffee.com
- Darktrace System Administration Guide · pdfcoffee.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Darktrace documentation tuning model alerts false positives score thresholds exclusions audit model breach triage OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
Darktrace official documentation model tuning alert management false positives tuning guide OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |