Define the attack surface and command a swarm of agents designed to hunt and attack vulnerabilities in AI models, applications, and agents. Simulate adversarial attacks such as prompt injection and jailbreaks at unprecedented speed and scale, providing insight into threats both obvious and obscure.
Threats to AI apps, models, and agents are growing exponentially. The most proactive red teaming will always benefit from a human defender, but the pace of AI development elevates the need for increased firepower. F5 AI Red Team empowers teams with a vast and continuously updated prompt database to test for vulnerabilities and streamline insights into implementation.
Attack-path insight into how and why agentic attacks succeed
Discover emergent risks with a swarm of agents trained on advanced techniques
Leverage the preeminent AI threat library of over 10,000 monthly attacks
Integrate with F5 AI Guardrails to automate insights into remediation
Deploy F5 AI Red Team directly alongside AI workloads in AWS, Azure, or Google Cloud environments
F5 AI Red Team is a certified Red Hat OpenShift operator capable of deploying in on-prem environments
F5 integrates with leading security and AI vendors to extend protection across the full lifecycle. Joint solutions secure data, models, and the APIs between them, keeping your AI fast, governed, and under your control.
Manual AI red teaming uses human experts to creatively probe AI systems for vulnerabilities, while automated red teaming uses tools and scripts to systematically test at scale. The best approach combines both; automation for comprehensive coverage and human expertise for nuanced, creative attack scenarios.
Without adversarial testing, organizations risk prompt injection attacks, data leakage, jailbreaks, and unauthorized outputs that can expose sensitive data, damage brand reputation, and compromise intellectual property.
AI red teaming specifically targets AI/ML models and their unique vulnerabilities—like prompt injection and AI-specific jailbreaks, whereas traditional penetration testing focuses on network, application, and infrastructure security flaws.
Red Team cadences depend on unique risk definitions, as well as industry-specific and compliance needs. At a minimum, the pace of AI threat landscape shifts makes monthly red teaming a baseline standard, however many teams conduct red team reports as a daily component of CI/CD pipelines.
At this time, F5 AI Red Team utilizes agents to execute attack campaigns, but the subject of those campaigns is a deployed model or application rather than an agent specifically. AI agents at their core are simply models capable of executing chained tasks through tool calls, so many of the vulnerabilities discovered for the model will also apply by extension to agentic workflows.
