DeepKeep Launches AI Agent Attack Surface Scanner to Map Enterprise Risk

Why It Matters

As AI agents become integral to business processes, their unchecked exposure creates a new, high‑risk attack vector; DeepKeep’s scanner gives organizations the visibility and controls needed to mitigate that risk.

Key Takeaways

• DeepKeep launches AI Agent Scanner for attack surface mapping
• Solution visualizes agents' tool, data access and vulnerabilities
• Supports Microsoft, Agentforce, OpenAI, CrewAI, Bedrock, n8n, Make
• Runtime protection adds AI firewalls based on observed behavior
• Red‑team offering slated for 2026 expansion

Pulse Analysis

Enterprises are rapidly embedding large‑language‑model agents into core workflows, granting them access to critical applications and data. Traditional security tools, built for static endpoints, struggle to keep pace with the dynamic, nondeterministic nature of these agents, leaving a widening blind spot that threat actors can exploit. By treating each AI assistant as a potential attack surface, organizations can begin to apply the same rigorous risk assessments used for conventional software, ensuring that the benefits of automation do not come at the expense of security.

DeepKeep’s AI Agent Scanner tackles this gap by automatically discovering every agent, the tools it interacts with, and the data it consumes. The platform generates a visual risk map aligned with the OWASP Top 10 for Agentic Applications, highlighting vulnerable integration points and suggesting defensive guardrails. Its support for leading frameworks—including Microsoft‑based agents, OpenAI, CrewAI, Amazon Bedrock, n8n and Make—means that most enterprise‑grade deployments can be covered out‑of‑the‑box, while runtime protection dynamically enforces AI firewalls based on real‑time behavior.

The broader market implication is significant: as AI‑driven automation scales, security vendors must evolve from perimeter‑focused solutions to AI‑native safeguards. DeepKeep’s roadmap, featuring a red‑team testing suite slated for 2026, signals a shift toward comprehensive lifecycle protection. Early adopters that integrate such visibility tools can reduce breach likelihood, meet emerging compliance demands, and maintain competitive advantage in an AI‑first economy.