Fabraix
Adversarial testing and runtime security platform for AI agents and systems.
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How the 4.4 was reached
- Quality of output5/10
AgentHarm result of 78% vs 67% is on the vendor's own site; the playground repo has only 76 stars. Source: fabraix.com
- Ease of use6/10
Black-box testing needs no integration: point at target, set budget, get report; docs exist but no self-serve pricing. Source: docs.fabraix.com
- Pricing value3/10
Commercial pricing is not published; only the playground repo is free under MIT. Source: github.com
- API and integration quality3/10
Docs mention products and authentication concepts but no clear API, SDK or integrations were found. Source: docs.fabraix.com
- Solves the problem it claims to solve5/10
Vulnerability findings are vendor-reported; the open-source playground is a CTF, which differs from the continuous red-teaming claim. Source: github.com
4.4/10 is the average of the five criterion scores above. The evidence comes from 3 different sources.Scores come from public evidence (the tool's own pages and documentation, and independent reviews); we do not test every tool hands-on. Scored 29 September 2026, on version 1 of our five-criteria scoring method.
Pricing
- Enterprise security testing
- Runtime monitoring
- Custom integrations
For the full list of what each plan includes, and current prices, see github.com.
Key Features
- Adversarial verification testing
- Runtime security monitoring
- AI agent security analysis
- Automated threat detection
- Enterprise security compliance
Pros & Cons
Pros
- Specialized focus on AI security
- Enterprise-grade security testing
- Addresses critical AI safety concerns
Cons
- Limited public information available
- Appears to be early stage
- No transparent pricing
- Narrow use case focus
Fabraix offers black-box red-teaming for AI agents that needs no integration, and its open-source playground is free. Its results come from the vendor, pricing is not public, and no clear API or SDK was found.
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