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If you’ve been letting Claude Code, Codex, or any other AI agent loose on your machine with elevated permissions, there’s a question that probably nags at the back of your mind: what did it actually do? Not what it *said* it did in that nice little summary — what really happened at the OS level. [Logira](https://github.com/melonattacker/logira) is a new open-source tool that answers exactly that question, and it does it in a way that feels both simple and genuinely useful.

Built by [melonattacker](https://github.com/melonattacker), Logira is a Linux CLI that uses eBPF to hook into the kernel and record every exec call, file operation, and network connection that happens during an AI agent run. It scopes everything through cgroup v2, so you get a clean per-run timeline rather than a firehose of system-wide noise. After a run finishes, all the events sit in JSONL and SQLite files under `~/.logira/runs/`, ready for you to query, review, or pipe into whatever analysis tool you prefer.

What makes it more than just a raw event logger is the built-in detection ruleset. Out of the box, it flags things like credential reads (SSH keys, AWS configs), persistence changes (cron jobs, systemd units), sketchy execution patterns like `curl | sh` or base64-decoded payloads, and outright dangerous commands — think `rm -rf /`, `terraform destroy`, or `mkfs`. The rules are defined in YAML files, so you can customize them per run if the defaults don’t fit your workflow.

The design philosophy here is deliberately hands-off: Logira observes and records, but never blocks. The creator’s reasoning — which came up in the [Show HN discussion](https://news.ycombinator.com/item?id=47211914) — is that an auditing system needs to be independent from the thing being audited. If your agent is the one telling you what it did, that’s the fox guarding the henhouse. An OS-level trace doesn’t care about the agent’s narrative; it just logs what the kernel saw.

The project [hit Hacker News](https://news.ycombinator.com/item?id=47211914) in early March 2026 and got picked up by [bestofshowhn.com](https://bestofshowhn.com/) as a featured project. The HN thread had some solid discussion around agent safety architecture, with commenters pointing out that this kind of independent observability layer is exactly what’s been missing as teams push AI agents into production. One commenter suggested having a second model review the Logira logs after each run — essentially using AI to audit AI, which is a fun idea.

If you’re running any kind of AI-powered automation on Linux and want an honest record of what happened, [Logira](https://github.com/melonattacker/logira) is worth a look. It requires Linux kernel 5.8+ with cgroup v2, and installation is a one-liner. Apache 2.0 licensed, no strings attached.