Fabraix

What is Fabraix?

Fabraix is an AI security research lab that builds tooling for offensive verification and runtime defense of AI agents. Its two core products — Nyx and Arx — work in tandem: Nyx autonomously probes agent systems using multi-turn, blackbox adversarial strategies, surfacing real exploits; while Arx translates those findings into runtime guardrails that actively block threats. Fabraix's approach is grounded in original research, including the Adversarial Cost to Exploit (ACE) framework, which reframes AI security from binary pass/fail outcomes into measurable, deployable economics.

Key Features

• Autonomous Offensive Agent (Nyx)

  Nyx probes AI agent systems autonomously using multi-turn, pure blackbox adversarial strategies — adapting in real time to surface exploits that manual red-teaming would miss.

• Runtime Defense Layer (Arx)

  Arx registers agent sessions, logs events, and performs in-context action checks to block prompt injection, goal deviation, and memory poisoning at runtime — informed directly by what Nyx discovers.

• Adversarial Cost to Exploit (ACE)

  A proprietary research framework that quantifies AI security risk in economic terms, enabling teams to prioritize defenses based on exploit cost rather than abstract severity scores.

• Scalable Adversarial Coverage

  Thousands of adversarial strategies run concurrently, meaning coverage scales with compute rather than headcount — making comprehensive security audits accessible without large red-team staffing.

• Adversarial Playground

  An interactive environment for testing prompt injection resilience against AI agents, useful for both security research and developer education.

Use Cases

• AI Agent Security Auditing : Security teams can deploy Nyx to run automated adversarial scans against production or staging AI agents, receiving detailed exploit reports without manual red-teaming.
• Runtime Threat Prevention : Engineering teams instrument their agent pipelines with Arx to monitor and block live attacks — including prompt injection and memory poisoning — as agents operate in production.
• AI Risk Quantification : CISOs and risk officers can use the ACE framework to translate AI agent vulnerabilities into cost-based metrics, making security investment decisions more defensible.
• Developer Security Testing : Developers building LLM-based applications can use the Fabraix Playground to stress-test their prompts and agent designs against adversarial inputs before deployment.
• Compliance & Threat Intelligence : Organizations operating regulated AI systems can leverage Fabraix's continuously surfaced exploit findings as ongoing threat intelligence to support audit and compliance workflows.

FAQs