AI Agents are rapidly being integrated into daily corporate operations—from document processing and workflow automation to internal knowledge querying and synthesis. These agents are not only deeply embedded into existing corporate systems but also interact with a significantly larger volume of internal data. As AI Agents become increasingly prevalent across various devices, the security threats they pose to endpoint environments can no longer be ignored.
According to research, over 80% of enterprises are currently implementing or using Large Language Models (LLMs) and AI Agents; however, more than half of these AI Agents remain unmonitored or unprotected*. This indicates that existing cybersecurity defense mechanisms have yet to keep pace with AI deployment. While enjoying the convenience brought by AI, enterprises are simultaneously facing substantial accompanying risks.
When executing tasks, AI may simultaneously access local files, system resources, and external services. These operational behaviors are no longer confined to a single system or environment. If a company fails to clearly define access permissions, execution protocols, or usage restrictions, an AI might autonomously read sensitive information or execute system commands without verification, creating a major blind spot in endpoint defense.
To detect and respond to these risks early, the key lies in maintaining visibility over the deployment and usage of AI Agents on endpoints and integrating this information into existing defense mechanisms, including:
- Identify Sensitive Information: Detecting the storage locations of keys, certificates, and confidential data to identify potential exposure risks.
- Discover Hidden Commands: Utilizing command analysis to quickly uncover hidden instructions and potential malicious behavior.
- Detect Malicious Skills: Identifying whether an AI Agent's "skills" contain hidden backdoors or malicious rules.
- Ensure Permissions and Access Scope: Evaluating and ensuring that the AI Agent's access to systems and files follows the Principle of Least Privilege (PoLP).
Enterprises do not need to sacrifice security for the sake of AI-driven operational efficiency. By incorporating AI into the endpoint defense framework, organizations can effectively monitor AI behavior and associated risks within their environment, ensuring that existing defense mechanisms evolve alongside the technology.
*Source: Gravitee, 2026 State of AI Agent Security Report