# Terra

- **Event:** [The Persistent Context Sprint Hackathon | Live at MongoDB .Local Build Fest](https://cerebralvalley.ai/e/persistent-context-sprint-hackathon)
- **When:** Thu, Aug 13 at 12:30 – 8:00 PM (PDT)
- **Where:** Pier 48, San Francisco, CA
- **Team:** [manish varma](https://cerebralvalley.ai/u/manishvarmadatla), [Anup Ahuje](https://cerebralvalley.ai/u/anupahuje)
- **GitHub:** https://github.com/terra-mongodb-hackathon
- **Demo video:** https://www.loom.com/share/f0fa1fd8bdd04bd48e3e3bcbfb6d6057
- **Gallery:** https://cerebralvalley.ai/e/persistent-context-sprint-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/persistent-context-sprint-hackathon/hackathon/gallery/54

Terra — named for the earth goddess who knows every fault line in the ground — is an autonomous AI pentester with persistent memory. Where security tools only flag issues, Terra acts like an attacker: it chains exploits across laptops, source control, cloud IAM, and databases, re-proves each of the dozens of vulnerabilities it surfaces with real evidence (validated, not detected), and pairs every finding with a concrete patch or PR. Its edge is memory — every exploit attempt, target fingerprint, and outcome lives in MongoDB Atlas, and before each move Terra vector-searches its past engagements to re-order its attack plan, so what it learned at one organization sharpens what it does at the next. The result is mechanical: our model stalls cold and scores 30/100, but with a single memory retrieved from a different engagement it crosses the wall and finishes at 100/100 — same model, same target, the only variable is MongoDB. Built on Atlas Vector Search for memory and LangGraph for crash-safe, resumable runs.

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Markdown version of https://cerebralvalley.ai/e/persistent-context-sprint-hackathon/hackathon/gallery/54. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt