What safety boundary would you expect from a local AI incident investigation tool?
Source Reddit BlueTeam
Discussion
This report discusses design considerations for a local AI-assisted incident investigation tool used in cybersecurity. The tool is intended to run locally on Linux or Windows hosts to assist first-pass investigations without making production changes. It collects evidence from various system sources and produces reviewable reports without executing potentially disruptive actions like killing processes or changing firewall settings. The discussion focuses on defining safe operational boundaries and trust requirements for such AI tools in incident response workflows. No active exploitation or vulnerability is described.
r/blueteamsec (opens in a new tab)u/ResponsibleJello31990 points0 comments
Disclosure: I maintain Open Investigator at Arvanta Cyber. It is Apache-2.0 and the pages below are freely accessible.
I am trying to design a safer pattern for AI-assisted first-pass server investigation.
The operational problem is familiar: incident response often starts with weak clues, not clean hypotheses.
- a suspicious IP
- a possible WebShell
- a Java service that looks odd
- a weird login time
- a host that feels different from yesterday
The design question: if AI helps with first-pass investigation, what authority should it have on a production host?
My current answer is: give AI an investigation toolbox, not production-changing authority.
The pattern I am testing:
- run locally on the Linux/Windows host being investigated
- expose sealed read-only tools instead of raw shell in safe mode
- collect evidence from auth, accounts, process, network, persistence, services, web logs, Java processes, recent files, containers, packages, and shell history
- write evidence.jsonl, commands.log, report.json, and report.md
- do not isolate hosts, block IPs, kill processes, delete files, disable accounts, restart services, or change firewall/registry state
The useful output should not be "AI says compromised." It should be a reviewable case folder that another responder can challenge, extend, and hand off.
Question for blue team / DFIR / SRE folks:
What would you require before trusting this kind of local AI investigator for first-pass triage?
- More command-policy transparency?
- Signed binaries?
- Offline model support?
- Better evidence IDs?
- Collector coverage for specific logs or middleware?
- A stricter no-shell mode only?
- Something else?
Practical guide:
https://www.arvantacyber.com/open-investigator/articles/local-ai-server-incident-response/
Safety-boundary article:
https://www.arvantacyber.com/open-investigator/articles/ai-incident-tool-safety-boundary/
Open-source project:
References
- report.md (opens in a new tab)
- reddit.com/r/blueteamsec/comments/1tqw41l/what_safety_boundary_would_you_expect_from_a/ (opens in a new tab)
- arvantacyber.com/open-investigator/articles/local-ai-server-incident-response/ (opens in a new tab)
- arvantacyber.com/open-investigator/articles/ai-incident-tool-safety-boundary/ (opens in a new tab)
- github.com/SEc-123/open-investigator (opens in a new tab)