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AI agent for security engineers

Log Anomaly Investigation Agent

Unexplained log anomalies turned into evidence-backed draft incidents, and explained ones closed

Log Anomaly Investigation Agent: what goes in, what the agent does and what you get

What it does

Unusual log entries are noticed late and investigated by hand. This agent scans logs for rare errors, sign-in spikes and new processes. It correlates entries across servers and tests simple explanations first, such as a scheduled job, a deployment or a known vendor update. Items that have an explanation are dropped with the reason recorded. Unexplained items become a draft incident with the evidence timeline. If new data arrives, it rechecks the item. The administrator approves any containment action. Edge case: sign-ins spike at midnight on one server, but a backup job explains it, so the agent closes it and notes the schedule.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedYes, continueNoNo 1 STARTS WHEN Log scan runs 2 USES A TOOL Scan logs for rare errors, sign-in spikes and newprocesses 3 DOES Correlate entries across servers by time and account 4 USES A TOOL Check the change calendar and scheduled jobs 5 CHECKS THE RESULT Is the anomaly explained by a known job or change? If not: search related logs for another explanation.Back to step 3. 6 DOES Drop explained items and record the reason 7 DOES Build an evidence timeline for each unexplained item 8 USES A TOOL Open a draft incident 9 YOU APPROVE Administrator approves any containment action 10 CHECKS THE RESULT After any action, do the symptoms stop? If not: review the new logs and update the incident.Back to step 3. 11 RESULT Incident draft or closed item list
Read the steps as a list
  1. Log scan runs
  2. Scan logs for rare errors, sign-in spikes and new processes
  3. Correlate entries across servers by time and account
  4. Check the change calendar and scheduled jobs
  5. Is the anomaly explained by a known job or change?If not: search related logs for another explanation. Back to step 3.
  6. Drop explained items and record the reason
  7. Build an evidence timeline for each unexplained item
  8. Open a draft incident
  9. Administrator approves any containment actionThe agent waits here for your OK.
  10. After any action, do the symptoms stop?If not: review the new logs and update the incident. Back to step 3.
  11. Incident draft or closed item list

How it decides

An anomaly is explained when a scheduled job, change or known pattern matches its time and source. Otherwise it becomes a draft incident.

  • Compare each anomaly with scheduled jobs and changes before raising it
  • Raise an item that touches several servers first
  • Treat a new process on a server as unexplained until matched
  • Keep the evidence and timestamps for every item

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Scan frequency (default: hourly)
  • Known benign patterns
  • Spike threshold
  • Incident severity rules

What keeps you in control

It always asks you first

  • Administrator approves any containment action

Hard limits

  • Never contains or shuts down systems itself
  • Never deletes logs

It stops when

  • Done: every anomaly is explained or in an incident
  • Stop: logs are missing for the period

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensAt 2 am, sign-ins to a file server spiked fivefold. The agent matched them to a nightly backup job and closed it. It found a new process on a second server that matched nothing, and it appeared on a third within the hour. It opened a draft incident with the timeline. The administrator approved isolating the first server.

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