Agentic-Security - CraftedSignal Threat Feedhttps://feed.craftedsignal.io/tags/agentic-security/Trending threats, MITRE ATT&CK coverage, and detection metadata. Fed continuously.Hugoenhello@craftedsignal.iohello@craftedsignal.ioSat, 28 Mar 2026 09:13:21 +0000https://feed.craftedsignal.io/favicon-32x32.pngCraftedSignal Threat Feedhttps://feed.craftedsignal.io/3232https://feed.craftedsignal.io/favicon.svgCrowdStrike Falcon Enhancements for AI Agent and Shadow AI Securityhttps://feed.craftedsignal.io/briefs/2026-03-28-ai-security/Sat, 28 Mar 2026 09:13:21 +0000hello@craftedsignal.iohttps://feed.craftedsignal.io/briefs/2026-03-28-ai-security/CrowdStrike is enhancing its Falcon platform to secure AI agents and govern shadow AI across endpoints, SaaS, and cloud environments, addressing threats like prompt injection attacks, data leaks, and policy violations associated with personal AI agents and shadow AI adoption.CrowdStrike is releasing new capabilities within its Falcon platform aimed at securing AI agents and governing shadow AI usage across various environments including endpoints, SaaS, and cloud. This initiative responds to the growing attack surface presented by the increasing adoption of AI tools, AI agents, and AI-powered software within organizations. Specific threats targeted include indirect prompt injection and agentic tool chain attacks. The Falcon platform enhancements aim to mitigate the risks associated with employees adopting AI tools without proper oversight and engineering teams deploying models and agents without sufficient visibility and runtime protection. These new features extend AI detection and response (AIDR) capabilities across new surface areas and expand platform capabilities to secure AI workforce adoption and development.

Attack Chain

  1. Initial Access: An employee or developer downloads and installs an AI application (e.g., ChatGPT, Gemini, Claude, DeepSeek, Microsoft Copilot, O365 Copilot, GitHub Copilot, or Cursor) on their endpoint.
  2. Agent Deployment: The AI application deploys an agentic component that interacts with the system, network, and other applications.
  3. Prompt Injection: An attacker injects malicious prompts into the AI application through user input or data feeds.
  4. Privilege Escalation: The injected prompts exploit vulnerabilities in the AI application or agent, allowing the attacker to escalate privileges.
  5. Data Exfiltration: The attacker leverages the compromised AI agent to access sensitive data and exfiltrate it to an external location.
  6. Lateral Movement: The attacker uses the compromised AI agent to move laterally within the network, accessing other systems and data.
  7. Policy Violation: The compromised AI agent violates security policies, such as accessing restricted resources or performing unauthorized actions.

Impact

Successful attacks targeting AI agents and shadow AI can result in significant data breaches, financial losses, and reputational damage. Compromised AI agents can be used to exfiltrate sensitive data, disrupt business operations, and launch further attacks against internal and external systems. The lack of visibility and governance over shadow AI deployments exacerbates these risks, making it difficult to detect and respond to attacks effectively. The scope of impact is growing with every new AI tool deployment and adoption.

Recommendation

  • Deploy the Sigma rule for detecting AI application installation to identify potential shadow AI deployments on endpoints.
  • Enable the Falcon AIDR browser extension to gain visibility into employee interactions with AI applications and detect prompt attacks and data leaks.
  • Utilize CrowdStrike Falcon Exposure Management to discover AI-related components running across endpoints and assess their risk.
  • Monitor network traffic for unusual activity originating from AI applications or agents.
  • Implement strong access control policies and data loss prevention (DLP) measures to prevent data exfiltration via compromised AI agents.
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