F5 AI Guardrails
Define and deploy agile data security, threat management, and governance for AI models, apps, and agents.
Define and deploy agile data security, threat management, and governance for AI models, apps, and agents.
Threat actors discover new ways to attack, models find new paths to harmful outputs, and users find new ways to break policy. F5 AI Guardrails secures AI models and agents against malicious threats, data leakage, and harmful outputs with industry leading efficacy and unmatched deployment flexibility.
F5 AI Guardrails mitigates risks like data leakage, harmful outputs, and adversarial attacks with comprehensive runtime security for deployed AI models and agents.
Create bespoke controls in seconds through natural language
Defend against prompt injection and jailbreak attacks with expert-built guardrails
Avoid harmful outputs with safeguards for toxic, biased, or inaccurate content
Maintain consistent privacy with full functionality in on-prem and fully air-gapped deployments
Explain and trace every interaction and why it was blocked or allowed
Ensure enterprise-wide policy alignment with automated auditing templates for GDPR, HIPAA, EUAIA, and more.
Prevent sensitive data leakage of standard and custom categories during AI interactions
Audit and block unauthorized tool calls and agent actions
Guardrails delivers consistent policy enforcement for every public and private AI model
Deploy guardrails in AWS, Azure, and Google Cloud
Confine all data, inspection, and enforcement actions to private compute boundaries
Maintain full functionality in on-prem or fully air-gapped environments
Apply the same guardrails to any OpenAI, Anthropic, or similarly formatted AI agent
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.
AI guardrails are frameworks of policies, technologies, and controls designed to ensure that AI systems operate securely and responsibly within defined boundaries. In the enterprise context, this includes mitigating risks such as adversarial attacks, data leakage, and compliance failures. The requirement for AI guardrails must go beyond merely preventing undesired behavior to proactively flagging risks, protecting sensitive data, and enabling trust across complex, multi-model systems.
F5 AI Guardrails applies content moderation filters and custom policy controls at runtime to inspect model outputs before they reach users. You can deploy out-of-the-box safeguards or create custom guardrails using natural language to detect and block toxic, biased, or harmful content. If a particular hallucination category has been observed at high frequency, F5 AI Guardrails lets you define rules that constrain model responses to avoid high-risk topics and prevent outputs that deviate from acceptable parameters.
F5 AI Guardrails includes out-of-the-box policy controls aligned to PCI, PHI, and EU AI Act prohibited-risk categories. It secures multiple sensitive data patterns at runtime and logs every enforcement action with transparent reasoning. These audit-ready logs simplify reporting for compliance teams and support enterprise governance requirements.
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.
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.