They're deploying AI apps and agents across the organization, often without the
right security in place—creating new risks to manage.
Patchwork point solutions aren't up to the challenge of securing AI.
your AI ecosystem.
Gain visibility and control over your AI infrastructure, platform and data.
your AI risk.
Detect vulnerabilities and risks early, ensuring AI models are safe before deployment.
against threats.
Monitor behaviors in real time to detect anomalies and stop live threats.
Enable the safe adoption of third-party AI models by scanning them for vulnerabilities and secure your AI ecosystem against risks such as model tampering, malicious scripts and deserialization attacks.
Uncover potential exposure and lurking risks before bad actors do. Perform automated penetration tests on your AI apps and models using our Red Teaming agent that stress tests your AI deployments, learning and adapting like a real attacker.
Gain comprehensive visibility into your AI ecosystem to prevent excessive permissions, sensitive data exposure, platform misconfigurations, access misconfigurations and more.
Protect your LLM-powered AI apps, models and data against runtime threats such as prompt injection, malicious code, toxic content, sensitive data leaks, resource overload, hallucinations and more.
We're innovating at the speed of AI. Check out the new features and updates in Prisma AIRS.
Eliminate traffic hairpinning and double inspection in Kubernetes environments to cut latency, resource waste, and security blind spots. This feature provides overlay routing support for EKS traffic.
Avoid all-or-nothing inspection trade-offs by steering only critical namespace traffic through deep inspection, boosting security precision without performance drag. This provides granular Kubernetes security with traffic steering.
Stop serverless workloads from becoming hidden blind spots by gaining unified visibility and consistent protection across VMs, containers, and functions. This is enabled through serverless function discovery for Azure and AWS.
Close AI agent security gaps with a plug-and-play gateway that blocks prompt injection, data leakage, and tool abuse—without complex code rewrites. This is achieved with a standalone MCP server for securing AI agents.
Simplify governance and reduce operational overhead by managing up to 20 apps under a single security profile with consistent policies. This is possible with multiple applications per deployment profile.
End fragmented visibility by unifying AI security logs with network events, giving SOCs a single pane of glass for threat detection and response. This is enabled by unified AI security logging in Strata Cloud Manager.