open-kritt vs REA
REA leads on trust: 73.3/100 (Grade B) against 57.7/100 (Grade C), a 15.6-point gap. open-kritt leads on maintenance; REA leads on supply-chain integrity and provenance, and rests on broader evidence.
Open-source, self-hosted AI vulnerability research tool that orchestrates agents to find and validate security issues in code.
Choose open-kritt if maintenance matters most.
- +5.9Maintenance: last push today, against 20d ago
Reverse engineer anything with agents, from app behavior down to native binaries.
Choose REA if supply-chain integrity and provenance matter most.
- +7.4Safety / Integrity: OSSF Scorecard 4.9 against 4.8
- +7.2Identity / Provenance: package provenance attested, against none
- +1.1Adoption
- B vs CEvidence coverage: 3 of 5 independent signal types, against 2
Where they differ
An independent, evidence-based trust comparison of open-kritt and REA, two Security & Guardrails projects in the HVTracker registry. Scores come from public, checkable signals — supply-chain provenance, OSSF Scorecard, maintenance, and adoption — not popularity.
Full evidence
| Signal | open-krittKritt-ai/open-kritt | REAmorluto/rea |
|---|---|---|
| HVTrust score | 57.7 | 73.3 |
| Evidence grade | C | B |
| Coverage grade | C | B |
| Overall rank | #704 | #258 |
| Rank in Security & Guardrails | #8 | #4 |
| GitHub stars | 2.2k | 416 |
| Last updated | today | 20d ago |
| Build provenance | No | Yes |
| OSSF Scorecard | 4.8 / 10 | 4.9 / 10 |
| License | AGPL-3.0 | MIT |
| Downloads | — | 129/wk |
| Trust dimensions (points earned) | ||
| Safety / integrity / 25 | 8.5 | 15.9 |
| Identity & provenance / 18 | 10.8 | 18.0 |
| Transparency / 17 | 12.6 | 12.7 |
| Maintenance / 20 | 17.8 | 11.9 |
| Adoption / 20 | 8.0 | 9.1 |
| Runtime capability surface (full matrix) | ||
| MCP server | — | Implemented |
| External providers | — | — |
| Requires API keys | No | No |
| Plugin surface | — | — |
| Provenance drift | — | Match |
How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption, scaled by an evidence-confidence factor. Grade bands: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Signals refresh daily. Full methodology v4.3 →