The Blast Radius of AI Agents: What's the Current Problem? Currently, we are increasingly utilizing artificial intelligence (AI) agents across various technological domains, from smartphone assistants to enterprise chatbots and AI-powered recommendation engines. While AI agents handle diverse tasks and enhance daily convenience, they also bring significant security concerns. As AI gains increasing autonomy, the potential for its inherent permissions and credentials to be exploited grows. This issue is not merely a technical one; it raises fundamental questions about overall corporate security and ethics. VentureBeat reported that at the 2025 RSA Conference, numerous security experts and technology leaders reached a common conclusion: the 'Zero Trust' principle must be extended to AI security. Zero Trust is fundamentally a security philosophy that dictates no user or system should be trusted by default, and continuous verification is required. While this principle is a proven approach in traditional network security, it has not yet been adequately applied to the new domain of AI agents. According to VentureBeat's analysis, many current AI agent systems still run untrusted code and credentials within the same environment. This is identified as a primary cause for the uncontrollable expansion of the 'blast radius' when a security threat occurs. The blast radius refers to the scope of damage when a security breach happens, and in the case of AI agents, the unpredictable expansion of this scope is the greatest concern. For instance, what if malicious code were to seize the credentials designed for an AI agent to access a sensitive database? In such a scenario, the risk extends beyond simple data loss to the potential collapse of the entire system. Given the nature of AI agents to connect with external tools, make autonomous decisions, and execute various tasks, a single vulnerability carries the potential to cripple the entire system. Indeed, AI agents require various permissions, including API calls, database queries, and external service integrations, and the fact that all these permissions can be exposed through a single point of compromise is a major concern for security experts. Vasu Jakkal, Microsoft's Corporate Vice President for Security, emphasized at the 2025 RSA Conference that the Zero Trust model is essential for AI security, stating, "The autonomy inherent in AI agents strongly suggests the need for a complete overhaul of outdated security practices." Jakkal's remarks underscore the need for a new security paradigm that goes beyond simply applying existing security frameworks to AI, instead reflecting AI's unique characteristics. Specifically, because AI agents can operate autonomously without continuous human oversight, new threat scenarios are emerging that are difficult to address with traditional security models. In this regard, Jeetu Patel, Cisco's Chief Product Officer, proposes a shift from traditional 'access control'-centric security to 'action control'. He stated, "Limiting the actions that an AI agent can perform is the ultimate core of strengthening security," explaining that action control can effectively curb the potential misuse of AI agents. According to Patel, traditional access control focuses on "who can access what," whereas action control focuses on "who can do what." In the context of AI agents, this means fine-grained control, such as allowing an agent to read data but not modify it, or permitting it to call specific APIs but not use sensitive parameters. This perspective convincingly supports the necessity of tailored security adapted to AI's unique characteristics. New Architectural Solutions VentureBeat's report introduces two new security architectures, offering practical solutions to these problems. The first is 'credential isolation'. This architecture stores AI agent credentials in a secure repository, separate from the execution environment, and allows access only with minimal privileges when needed. In essence, it implements a method to protect sensitive information and minimize loss even if malicious code infiltrates the system. The core principle of credential isolation is to prevent agent code from directly possessing or accessing credentials. Instead, when an agent needs to perform a specific task, it sends a request to a secure repository, which then temporarily provides only the minimum necessary privileges for that task. This is analogous to a bank not giving vault keys directly to customers, but rather having a bank employee accompany them to retrieve only the necessary items when required. This approach is regarded as an effective method for balancing autonomy and security. In practice, implementing credential isolation ensures that even if an agent's execution environment is fully compromised, an attacker can only obtain a limited scope of temporary tokens and cannot acquire the master keys for the entire system. The second architecture is 'modular agent de
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