Which AI security platform is right for your team? We break down the differences in features, latency, and protection scope to help you decide.
| Feature | GuardionAI | Rebuff |
|---|---|---|
| Primary Focus | Agent Runtime Governance | Prompt Injection Defense |
| Tool Call Protection | Deep Inspection | Not documented |
| Deployment | Inline Security Gateway / Guard API / Claude Code plugin | Self-hosted |
| Guardrails Latency | <130ms policy decision | Variable |
| Detection Accuracy | 96.3 F1 on the Prompt Security Leaderboard with 0.02% false positives | Not published / varies by deployment |
| Compliance | GDPR-ready, HIPAA-ready, LGPD-ready, SOC 2 Type II (in progress) | MIT |
GuardionAI figures from guardion.ai (Policy engine decisions return in under 130ms — 20× faster than cloud provider guardrails.) • Rebuff figures from public documentation.
Multi-layered defense against prompt injection attacks using heuristics, vector DBs, and LLM analysis. It is categorized under Runtime Guardrails & AI Firewall in the Guardion AI Security Index.
Yes. Rebuff has an open-source core (https://github.com/protectai/rebuff); pricing model: Open Source.
Teams evaluating Rebuff most often compare it with Lakera (Check Point), Meta (Llama Guard), Prompt Security (SentinelOne), and GuardionAI — all listed under Runtime Guardrails & AI Firewall.
Rebuff focuses on prompt injection defense, while GuardionAI is an agent runtime governance platform ("EDR for AI agents") that governs every agent tool call inline with sub-130ms guardrails latency.