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As enterprises rapidly deploy AI models and agents across cloud environments, they create a new, dynamic attack surface that traditional security tools struggle to see. Upwind, a runtime-first cloud security leader, has announced the integration of comprehensive AI security capabilities directly into its Cloud Native Application Protection Platform (CNAPP). This "inside-out" approach uses real-time runtime evidence and Layer 7 visibility to secure AI services, models, agents, and data flows, grounding AI risk in actual activity rather than static configurations.
Upwind integrates AI security capabilities into its unified CNAPP platform.
The "inside-out" approach uses real-time runtime visibility (Layer 7) to secure AI.
New modules include AI Posture Management, AI Detection & Response, and AI Bill of Materials.
It provides runtime tracing of AI agent actions and security testing for OWASP LLM Top 10 risks.
The solution maps AI components and detects anomalous behavior or data exposure in real-time.
Goal: Unify cloud and AI risk management with evidence from actual runtime behavior.
The proliferation of AI models, inference endpoints, and agentic workflows across multiple cloud services has created a complex and opaque attack surface. Security teams often lack the ability to trace AI behavior, validate posture, or understand the impact of AI-driven decisions. Upwind's new suite aims to close this gap by extending its runtime-first security model—which observes real traffic, API calls, and data flows inside workloads—into the AI layer. This provides a factual, prioritized view of what AI systems are actually doing at runtime.
Amiram Shachar, Founder and CEO of Upwind, explained the philosophy: "AI security should not be a stand-alone security component. It should be part of a larger ecosystem. It just makes perfect sense to go down this route and make sure that AI security benefits from all the data and context that our CNAPP already holds."
The integrated suite includes several key modules designed to work cohesively:
AI Security Posture Management (AI-SPM): Secures exposed inference endpoints, enforces model governance, and detects leaked API keys, correlating findings with runtime activity.
AI Detection & Response (AI-DR): Monitors agents and LLM infrastructure for anomalous behavior and jailbreak attempts through deep Layer 7 analysis of prompts and network activity.
AI Bill of Materials (AI-BOM): Maps models, frameworks, SDKs, and agent systems across source code and runtime to create a comprehensive, real-time inventory.
AI Network Visibility: Decodes AI-native traffic (JSON-RPC, HTTP/2 streaming) to detect shadow AI usage and sensitive data in prompts.
MCP Security: Traces the full sequence of AI agent actions, from prompt to downstream function calls and system changes.
AI Security Testing: Validates AI systems against adversarial techniques like prompt injection and the OWASP Top 10 for LLMs.
Shachar emphasized the critical need for runtime evidence: "AI is now driving critical decisions across modern systems, yet most organizations still can’t see what their models and agents are actually doing. Upwind changes that. Real security starts with real evidence."
Upwind's launch represents a significant step towards converging cloud workload security and AI security into a single, context-rich platform. By applying a runtime-first, inside-out methodology to AI, the company is addressing the fundamental challenge of securing systems that are inherently dynamic and interactive. This approach moves beyond checklist compliance and theoretical risks, providing security teams with the authoritative evidence needed to understand and mitigate the real-world threats posed by their own AI innovations.
About Upwind
Upwind is the next-generation cloud security platform built to lead the Runtime revolution. Headquartered in San Francisco, California, Upwind brings together a unified vision for cloud and application-layer protection, empowering organizations to run faster, detect threats earlier, and secure their environments with unmatched precision. The company was founded by Amiram Shachar and the founding team behind Spot.io (acquired by NetApp for $450 million) and is backed by leading investors including Greylock, Cyberstarts, Leaders Fund, Craft Ventures, Cerca Partners, and Sheva, a venture fund founded by former NBA player Omri Casspi with investment from current NBA star Stephen Curry through Penny Jar Capital. Upwind has raised $180 million since its founding in 2022 and is trusted by forward-thinking enterprises globally to bring real-time runtime intelligence to modern cloud security.
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