F5 AI Security Platform
For continuous command over AI risks, F5 delivers the most adaptable platform for securing AI apps, models, agents, and the APIs connecting them.
For continuous command over AI risks, F5 delivers the most adaptable platform for securing AI apps, models, agents, and the APIs connecting them.
When AI systems act at machine speed with more access than even the most over-privileged users, mistakes cascade into headlines. But the moment you define a boundary, users learn to evade it, attackers learn to exploit it, and agents amplify both. Addressing AI risk requires continuous command—a persistent capability to define, observe, evaluate, and enforce controls tailored to unique risk-definitions and business needs.
Translate risk appetite, privacy requirements, and compliance obligations into enforceable policy for enterprise AI use.
Discover and assess risks across AI apps, agents, and APIs in use
Continuously test AI systems for potential vulnerabilities and automate insights into remediation
Protect AI systems and APIs against prompt injection, excessive agency, and data leakage with industry-leading efficacy
Create bespoke controls through natural language
Discover, classify, and monitor risky AI usage
Find and fix AI exploits faster than attackers retool
Secure and govern agent actions and tool calls
Intercept sensitive data in AI agent and model interactions
Deploy private AI in public cloud, private cloud, and on-prem
Consistent policy controls for all public and private models
Inform model selection with security benchmark results.
Deploy via AWS, Azure, or GCP with seamless integration into existing cloud infrastructure and workflows.
Span on-prem and cloud environments with unified policy enforcement.
Maintain full control over AI security within your private infrastructure without external outbound calls.
Operate in fully isolated environments with no external connectivity.
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.
An AI security platform provides centralized runtime protection, governance, and observability for AI models, applications, and agents. It protects enterprise LLMs by monitoring every interaction and blocking threats like prompt injection, data leakage, and other kinds of harmful outputs. Unlike point solutions, an AI security platform unifies capabilities that reinforce each other such as adversarial testing informing runtime defenses, or AI discovery identifying the most urgent models for security testing based on workforce adoption. This integrated approach delivers a more robust defense that fragmented tools simply can't match.
Open-source AI security tools offer a starting point but require significant internal expertise to configure, deploy, and maintain. They're community-driven, which often means slower updates, limited compliance-ready templates, and gaps in audit trails required for regulated industries.
Commercial AI security tools provide enterprise-grade capabilities including dedicated threat research, regular updates against emerging attack techniques, and out-of-the-box compliance controls needed for enterprise AI workloads.
AI governance is the framework of policies, controls, and oversight mechanisms that ensure AI systems align with organizational standards and regulations. It includes defining how AI is allowed to interact with users and data, maintaining audit-ready logs of AI activity, and aligning deployments to the risk management frameworks and compliance obligations specific to the organization. The F5 AI Security Platform helps teams operationalize AI governance with customizable policy enforcement aligned to unique risk categories and providing auditability for every model, user, and agent action.
AI Security platforms are purpose-built to secure and govern enterprise AI workloads, rather than comprehensive security and user activity monitoring. Traditional network threats exist in packets and data, whereas AI threats live in the words and tokens exchanged between users, agents, and models. Traditional cybersecurity solutions should be used in tandem with dedicated AI security tooling for an effective defense-in-depth approach.
Model provider guardrails are typically a baseline protection designed to meet the provider’s compliance obligations and risk appetite rather than protections extensible to all enterprise use cases, and risk definitions. In recent SecureIQLab testing of foundational models’ built-in guardrails against sophisticated AI attacks, roughly 13% of attacks were successfully blocked. Model providers may offer limited security controls but the efficacy of those controls does not meet the standards of most enterprise workloads and often restricts those controls to specific models rather than the full breadth of an organization’s AI inventory.