F5 and Forcepoint Partner to Secure AI Across Data and Runtime Lifecycle

Why It Matters

By unifying data governance and runtime protection, the partnership closes critical security gaps as enterprises scale AI, reducing breach risk and compliance costs. This integrated approach sets a new benchmark for AI risk management across industries.

Key Takeaways

• AI security gaps arise from siloed data and runtime controls
• Forcepoint provides AI-native data discovery and classification
• F5 adds AI Red Team and Guardrails for runtime protection
• Joint solution enables real-time vulnerability detection and policy enforcement
• Demonstration slated for RSAC conference, boosting market visibility

Pulse Analysis

The rapid adoption of generative AI in enterprises has outpaced traditional security frameworks, exposing data pipelines and model endpoints to new attack vectors. Organizations deploying AI copilots, assistants, and automated workflows often struggle to locate sensitive information, trace its flow, and enforce consistent policies across development and production environments. Existing silos between data governance and application security create blind spots that threat actors can exploit, from prompt injection to model theft. As regulatory pressure mounts and breach costs rise, a unified approach that spans the entire AI lifecycle is becoming a strategic imperative.

The alliance between F5 and Forcepoint bridges that gap by coupling Forcepoint’s AI‑native Data Security Posture Management with F5’s AI Red Team and Guardrails capabilities within its Application Delivery and Security Platform. Forcepoint’s discovery engine automatically classifies data across cloud, SaaS, endpoint and on‑premise stores, flagging high‑risk assets before they reach an AI model. F5 then enforces runtime controls—such as API throttling, prompt sanitization, and adversarial testing—to protect models, agents and APIs in real time. This end‑to‑end stack delivers continuous telemetry, policy validation, and automated remediation, turning compliance into an operational feature rather than a periodic audit.

For enterprises, the combined offering translates into measurable risk reduction and faster AI time‑to‑market. By surfacing data vulnerabilities instantly and applying guardrails at the point of inference, security teams can prioritize high‑impact use cases and avoid costly data exfiltration incidents. The partnership also positions both vendors competitively against rivals that offer fragmented solutions, signaling a market shift toward integrated AI risk management platforms. As the RSAC showcase in San Francisco demonstrates, visibility across the data‑to‑runtime continuum will likely become a benchmark for procurement decisions, driving broader adoption of lifecycle‑centric AI security models.