DeepKeep has unveiled a first-of-its-kind AI Agent Attack Surface Scanning and Discovery solution designed to help enterprises secure rapidly expanding agentic AI environments. As organizations increasingly deploy non-deterministic, large language model (LLM)-based agents across business workflows, they are inadvertently broadening their cyber attack surface. Consequently, traditional cybersecurity controls often fail to address the unique risks associated with these autonomous, interconnected AI systems.

With AI agents evolving far beyond basic chatbots, enterprises now rely on context-aware systems capable of independently interacting with business applications, financial systems, cloud services, collaboration platforms, operational tools, and even other AI agents. In fact, industry forecasts suggest that AI agents could make at least 15% of routine business decisions by 2028. However, this growing autonomy also introduces significant security challenges. Unlike standalone AI applications with limited exposure, agentic systems operate within complex, multi-layered ecosystems, which increases the risk of data breaches, tool misuse, unintended actions, and sensitive data exposure.

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To address this emerging threat landscape, DeepKeep developed its AI Agent Scanner to provide enterprises with immediate, actionable visibility into their AI environments. Specifically, the solution maps what each AI agent can access, which tools and data sources it interacts with, and where potential vulnerabilities may exist. As a result, security teams gain a comprehensive understanding of how agentic workflows function and where risks could materialize.

Moreover, the platform conducts robust attack surface scanning to analyze an agent’s entire threat landscape. It identifies connected tools, defines their intents, maps associated data sources, and highlights weaknesses across workflows. The solution also generates a visual risk map aligned with the latest OWASP Top 10 for Agentic Applications. This structured approach helps organizations understand not only where vulnerabilities exist but also how attackers could exploit specific elements and what defensive measures are required.

Importantly, DeepKeep designed the scanner to address another critical gap: the lack of a standardized framework for describing and securing AI agent architectures across vendors and workflows. Therefore, the solution introduces a consistent methodology for mapping and mitigating agent-related threats across diverse environments. By increasing visibility into complex, multi-framework AI ecosystems, enterprises can proactively identify and manage risks during both development and production stages.

In addition to discovery and mapping, DeepKeep’s platform delivers runtime protection for select agentic frameworks. Based on observed agent behavior, tool usage, and data exposure patterns, the system identifies where AI firewalls and guardrails should be implemented. Consequently, security teams can reduce operational risks in real time while maintaining workflow efficiency.

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“AI agents are no longer operating in isolation; they’re quickly becoming fundamental parts of entire business workflows, executing tasks that change how work gets done. But without proper safeguards, their expanding attack surface will rapidly become a massive enterprise liability,” said Yossi Altevet, CTO and Co-Founder of DeepKeep. “At DeepKeep, we are committed to securing agentic AI today and tomorrow, and that means innovating even faster than AI is evolving, starting with our new scanning solution, which offers the immediate visibility and protection businesses need to safely leverage agentic AI ecosystems.”

Currently, the AI Agent Scanner supports major agentic frameworks, including Microsoft-based frameworks, Agentforce, OpenAI Agents, CrewAI, Amazon Bedrock AgentCore, n8n, and Make, among others. Looking ahead, DeepKeep plans to expand its AI agent security capabilities across the full AI lifecycle in 2026, including the introduction of a red teaming solution.

Overall, this launch strengthens DeepKeep’s broader enterprise AI security portfolio. By combining attack surface discovery, structured risk mapping, and runtime protection, the company enables organizations to confidently scale AI adoption while maintaining strong security, governance, and operational control.

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