BLOG Featured Recent Video Category Start Free Trial New CrowdStrike Innovations Secure AI Agents and Govern Shadow AI Across Endpoints, SaaS, and Cloud March 23, 2026 | John Gamble | Securing AI As organizations race to adopt new AI tools, deploy AI agents, and build AI-powered software, they create new attack surfaces that traditional security controls were never designed to protect. A key example is the prompt and agentic interaction layer, which faces novel threats like indirect prompt injection and agentic tool chain attacks. The rapid acceleration of shadow AI exacerbates the challenge as employees adopt AI tools without oversight and engineering teams deploy models and agents without adequate visibility and runtime protection. The result is an AI visibility and governance gap that grows with every AI tool deployment and adoption. CrowdStrike is closing that gap. Today we’re announcing a series of innovations across the CrowdStrike Falcon® platform that extend AI detection and response (AIDR) capabilities across new surface areas and expand our platform capabilities to secure AI workforce adoption and development across endpoints, SaaS environments, and cloud environments. These new capabilities will enable organizations to confidently and securely accelerate AI development and adoption. Defending Endpoints: The Ultimate AI Battleground The endpoint has always been a primary target for adversaries, but the rise of personal AI agents like OpenClaw puts them at the frontline of a new attack technique called living off the AI land (LOTAIL). LOTAIL exploits a dangerous combination of factors that converge on the endpoint: increasing agent autonomy, high system permissions, and minimal governance. Code and computer-use agents, agentic browsers, and personal AI tools are being deployed, particularly on developer machines, and they can execute terminal commands, browse the web, interact with files, and take autonomous actions that can look indistinguishable from legitimate user behavior traffic. That makes them extraordinarily difficult to detect with traditional tools, and extraordinarily dangerous when compromised. Today we’re announcing two significant new capabilities to extend endpoint AI security capabilities for agents and shadow AI. AI Detection and Response for Desktop AI Applications We’re excited to announce that CrowdStrike Falcon AIDR's runtime threat detection capabilities for securing workforce AI adoption will extend beyond the browser, where most employee AI interactions occur, to cover desktop AI applications including ChatGPT, Gemini, Claude, DeepSeek, Microsoft Copilot, O365 Copilot, GitHub Copilot, and Cursor. Figure 1. AIDR policies deployed to Falcon endpoints As employees, and especially engineering teams, turn to desktop AI applications, security teams need visibility and threat detection around their interactions. Falcon AIDR will leverage the Falcon sensor to enable more seamless deployment of the Falcon AIDR browser extension from the Falcon console and obtain desktop application telemetry via the sensor's container network interface capability. This will give security teams visibility into employees’ use of these AI apps, including full prompt content, and the ability to detect prompt attacks, data leaks, and access control and content policy violations across the full range of AI tools employees use on endpoints. This new capability is currently pre-beta and will go to GA next quarter (Q2). Deep Agent and Shadow AI Discovery on Endpoints Beyond desktop applications, there is a wide range of AI assets that can be deployed on endpoints, especially by developers on engineering machines such as large language models (LLMs), Model Context Protocol (MCP) servers, and IDE extensions. AI Discovery in CrowdStrike Falcon® Exposure Management, powered by CrowdStrike Falcon® for IT telemetry, helps secure these assets. Now generally available, this capability automatically discovers AI-related components running across endpoints in real time, including AI apps and agents, LLM runtimes, MCP servers, and IDE extensions. Discovered AI components are classified and linked to existing assets in Falcon Exposure Management, where teams can view context such as privilege level, connectivity, and proximity to critical assets. This allows security teams to make better risk-based prioritization decisions and understand not just what AI is deployed, but how it connects to the rest of the environment and what the blast radius of a compromise might be. Figure 2. AI-enabled assets inventory on the endpoint filtered down to MCP participants For teams building AI applications, this same visibility provides essential context about where AI components have been introduced into the development environment. This helps security and engineering teams identify supply chain risks and misconfigured AI tooling before they become exploitable vulnerabilities. Securing AI Agents Across SaaS Environments AI Detection and Response for Copilot Studio Agents Falcon AIDR is extending runtime security guardrails to agents built in Microsoft Copilot Studio, covering both developer-built agents and low-code agents built by business users. When Copilot agents execute tasks, interact with data, and respond to user inputs, Falcon AIDR will monitor for prompt injection attacks, data leaks, and policy violations in real time. For teams adopting AI across the workforce, it will help protect the Copilot agents employees interact with daily against adversarial manipulation. For teams building AI applications on top of Microsoft's agent framework, it will provide the runtime monitoring needed to validate that agents are behaving as intended and detect anomalous behavior that could indicate compromise or misconfiguration. This capability is currently pre-beta and will go to GA later this quarter (Q1). Discovering and Governing AI Agents across SaaS Environments SaaS platforms are a primary deployment environment for AI agents. Organizations are building and deploying agents with significant permissions and access to sensitive data across SaaS platforms, often without the strong visibility and governance frameworks to manage the risk they introduce. When they're misconfigured, over-privileged, or compromised, the consequences can be severe. For organizations focused on securing AI workforce adoption, understanding what AI agents are operating across their SaaS stack is an essential first step. CrowdStrike AI Agent Discovery, now generally available in CrowdStrike Falcon® Shield, provides unified discovery and classification of AI agents across SaaS platforms, delivering granular visibility into agent configurations, tool and API access, data sources, and ownership. Figure 3. Normalized view of AI agents across disparate agentic AI platforms What makes this capability particularly powerful is normalization. Agent attributes are standardized into a consistent framework across vendors, which enables security teams to identify risky behavior, excessive privileges, and unmanaged agents regardless of which platform they're deployed on. This unified view supports immediate cross-platform governance and compliance monitoring, which is critical as AI agent usage rapidly expands across enterprise environments. Figure 4. Identity-centric risk graph illustrating cross-platform security posture and privilege accumulation across M365 and Power Platform environments AI Agent Discovery integrates with Microsoft Copilot (Power Platform), Salesforce Agentforce, ChatGPT Enterprise, OpenAI Enterprise GPT, and Nexos.ai. Security teams can identify risky configurations, excessive access, and ownership gaps, and apply centralized governance as AI agent usage scales. For organizations building AI applications that leverage SaaS-based agent frameworks, this capability provides the visibility needed to help deployed agents operate within intended parameters and prevent misconfiguration or compromise post-deployment. Not all shadow AI in SaaS environments is visible through API connectors alone. To extend coverage, Falcon Shield also now analyzes Falcon sensor endpoint-collected DNS telemetry to uncover shadow AI use via SaaS, helping to capture even AI tools accessed without formal SaaS API connectors deployed in the organization's SaaS AI inventory. Securing AI in the Cloud from Development to Runtime Cloud environments are where AI is built, trained, and deployed at scale. Organizations are deploying AI workloads on Kubernetes, integrating with managed machine learning (ML) platforms like Amazon SageMaker and Bedrock, and building applications that communicate with LLMs through the OpenAI API specification. Each of these environments introduces distinct security challenges and blind spots that adversaries can exploit. AI Detection and Response for Containerized Workloads For organizations building and deploying AI applications in the cloud, runtime threat detection at the application layer is essential. Falcon AIDR will extend runtime guardrails to containerized applications communicating with the OpenAI API specification, detecting prompt injections, data leaks, and access control and content policy violations for cloud-hosted AI workloads. This capability is delivered via an integration with CrowdStrike Falcon® Cloud Security, which intercepts OpenAI API calls and routes them through Falcon AIDR's detection engine, with detections surfaced in the Falcon AIDR console and in CrowdStrike Falcon® Next-Gen SIEM. Security teams can take response actions directly within the CrowdStrike Falcon® Cloud Security console, including isolating or terminating AI workloads, to contain threats before they escalate. This new capability is currently pre-beta and will go to GA next quarter (Q2). Threat Detection for Kubernetes AI Workloads As organizations increasingly standardize on Kubernetes to host mission-critical AI workloads, the Kubernetes orchestration layer becomes a high