Per-axis breakdown will be refreshed on the next collection.
GitHub Stars are excluded — popularity does not prove a project is still alive.
Checked 2026-06-16 · Formula & source · tool_master CSV
Stomped — ToolStack Analysis
Key Strengths
- The tool provides an automated triage loop specifically for USN change journal analysis.
- It utilizes a read-only architecture to ensure forensic integrity during investigations.
- The integration with Claude Code facilitates autonomous DFIR operations within MCP environments.
Key Limitations
- The project lacks a public GitHub repository, limiting transparency and collaborative review.
- With 0 GitHub stars and minimal maintenance history, it poses a significant operational risk.
- The tool is currently limited to the SANS SIFT Workstation environment, restricting broader use cases.
Angel — when it fits
- If you need to automate USN journal analysis on SIFT, this tool hits different by automating the triage loop.
- It’s basically a read-only agent, so you don't have to worry about it messing up your evidence files.
- Integrating it with Claude Code for DFIR workflows is lowkey a game changer if you're already deep into the MCP ecosystem.
Devil — when it does not
- Ngl, with 0 stars and no GitHub repo, you're pretty much on your own if this thing breaks in the middle of a case.
- It’s a total ghost town project—don't expect any updates or community support when you run into bugs.
Stomped functions as an autonomous agent designed to detect timestomping and file laundering activities on SANS SIFT Workstations. By leveraging the USN change journal and a read-only architecture, it provides a self-correcting triage loop that simplifies complex forensic analysis. It is primarily intended for developers and security researchers who require seamless integration with the Model Context Protocol (MCP) to automate their digital forensics and incident response (DFIR) tasks.
| Item | Value |
|---|---|
| Type | mcp |
| Price | free |
| GitHub Stars | 0 |
| Latest Commit | 2026-06-16T01:30:50Z |
| License | MIT |
| Primary Language | Python |
| TS Score | 30 / 100 |
| Official Link | https://glama.ai/mcp/servers/bgs2v5vatk |
| GitHub | N/A |
Community reaction
HN users frequently discuss the potential of autonomous DFIR agents, noting the high value of automated USN journal analysis.
Some users express skepticism regarding the reliability of unverified, low-activity agents in critical forensic workflows.
Taken together, the tool is a promising experiment for enthusiasts, but a high-risk choice for professional forensic environments.
Source: Hacker News (90-day data)
