Security teams drown in SIEM alerts, most of which are noise that still takes minutes each to investigate by hand. This automation does the first-pass research before a human ever looks.
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README.md
Why this subagent
Security teams drown in SIEM alerts, most of which are noise that still takes minutes each to investigate by hand. This automation does the first-pass research before a human ever looks.
It enriches every indicator with threat intel, asset ownership, and related events, then scores the alert. Analysts only get paged for the ones that matter, with the evidence already attached, so triage starts from context instead of a blank screen.
How it runs
Used at step 01 to kick off the pipeline.
Write
Used at step 01 to kick off the pipeline.
WebFetch
Used at step 01 to kick off the pipeline.
WebSearch
Used at step 01 to kick off the pipeline.
Look up every indicator against threat intel feeds and reputation services for known-bad matches.
pending
Add asset owner, recent login history, and any related alerts so the analyst sees full context.
pending
Score the enriched alert and route low-confidence noise to a queue while paging humans only on real risk.
pending
Sample output
json
// Sample output
// (generated when the pipeline finishes)
Take a raw SIEM alert, enrich every indicator with threat-intel and asset context, then return a triage verdict (escalate or suppress) with a confidence score and the evidence behind it.
Unlock the rest
The full agent definition, install snippet, and starter task are gated for community members.
Members get the full `.md` agent file, the npm / pnpm install one-liners, a starter prompt that we've tuned against real runs, and the open-source repo when this automation ships there. One email, magic link, done.