Guardrails AI vs HOL Guard
HOL Guard leads on trust: 92.2/100 (Grade A) against 76.5/100 (Grade B), a 15.7-point gap. Guardrails AI leads on adoption and rests on broader evidence; HOL Guard leads on maintenance and supply-chain integrity. Note: HOL Guard's evidence coverage is thinner (coverage B vs A) — its score rests on fewer independent signal types.
Adding guardrails to large language models.
Choose Guardrails AI if adoption matters most.
- +3.2Adoption: 32.4k weekly downloads against 9.1k
- A vs BEvidence coverage: 4 of 5 independent signal types, against 3
Open-source antivirus for AI agents: block risky tools, secret access, prompt injection, malicious packages, MCP servers, plugins, and skills at runtime.
Choose HOL Guard if maintenance and supply-chain integrity matter most.
- +8.4Maintenance: last push today, against 6d ago
- +4.4Safety / Integrity: OSSF Scorecard 9.6 against 6.0
- +3.1Transparency: OSSF Scorecard 9.6 against 6.0
Where they differ
1 dimension identical: Identity 18.0 · Full evidence table
An independent, evidence-based trust comparison of Guardrails AI and HOL Guard, 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 | Guardrails AIguardrails-ai/guardrails | HOL Guardhashgraph-online/hol-guard |
|---|---|---|
| HVTrust score | 76.5 | 92.2 |
| Evidence grade | B | A |
| Coverage grade | A | B |
| Overall rank | #200 | #7 |
| Rank in Security & Guardrails | #4 | #1 |
| GitHub stars | 7.5k | 683 |
| Last updated | 6d ago | today |
| Build provenance | Yes | Yes |
| OSSF Scorecard | 6.0 / 10 | 9.6 / 10 |
| License | Apache-2.0 | Apache-2.0 |
| Downloads | 32k/wk | 9k/wk |
| Trust dimensions (points earned) | ||
| Safety / integrity / 25 | 20.0 | 24.4 |
| Identity & provenance / 18 | 18.0 | 18.0 |
| Transparency / 17 | 13.6 | 16.7 |
| Maintenance / 20 | 11.6 | 20.0 |
| Adoption / 20 | 15.3 | 12.1 |
| Runtime capability surface (full matrix) | ||
| MCP server | — | Implemented |
| External providers | 3 — Anthropic, Multi-provider (LiteLLM), OpenAI | 3 — Anthropic, Google Gemini, Multi-provider (LiteLLM) |
| Requires API keys | Yes | No |
| Plugin surface | — | extensions |
| Provenance drift | Unknown | 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 v4.4 →