Co-authored by Ching Chiao, Head of APAC & Corporate Development, Whois API, Inc. and Ed Gibbs, Field CTO, WHOIS API Inc.

The Newest Member of Your Team is a Bot—and They Have the Keys to the Vault

For two decades, cybersecurity has been a game of containment—building higher walls around processes and tighter boxes around applications. But the sudden, viral rise of “Agentic AI” has effectively signaled a demolition of those boundaries. Whether it is senior engineers buying Mac Minis for the sole purpose of hosting an instance of Moltbot (formerly known as Clawdbot) or enterprises deploying autonomous agents to manage SOC workflows, the paradigm has shifted. We are no longer just using AI; we are hiring digital employees and handing them the keys to our identity kingdom without so much as a background check. By granting these agents “delegated authority” to act on our behalf, we have created a massive, unsecured territory: we are calling it AI Agent Surface Management (ASM-AI) .

The Great Flip: From “Unauthorized Execution” to “Authorized Exploration”

For years, we focused on preventing “unauthorized execution”—stopping a virus from running code it shouldn’t. Agentic AI flips this script entirely. The risk today is “authorized exploration” by a bot you legitimately hired. A 24-hr, non-stop digital assistant—operates with your credentials, mimics human browsing behavior, and utilizes valid APIs. They fundamentally break traditional EDR and sandboxing. An EDR platform is designed to catch a malicious binary, not a productive agent making a trust decision at runtime to connect to an experimental, unvetted API. Security risk no longer stems primarily from unauthorized execution, but from authorized exploration.

The DNS Pulse: Detecting Intent Before the Handshake

In the era of AI Agent Surface Management (ASM-AI), DNS is no longer merely a supporting utility; it has become a foundational control plane for understanding agent behavior. Before an AI agent establishes an HTTPS session or executes an API call, it must first resolve a domain name. That resolution represents the earliest observable signal of discovery intent—the point at which an agent reveals which external assets it is evaluating and considering for trust.

At the same time, domain names or individual indicators such as Newly Registered Domains (NRDs) cannot be evaluated in isolation. NRD signals are highly valuable, but they represent only one dimension of risk. Effective ASM-AI requires DNS intelligence, enriched with infrastructure attribution: IP address history, ASN affiliation, hosting provider reputation, and the network neighborhood context. By correlating DNS telemetry with infrastructure intelligence from sources such as WhoisXMLAPI, CISOs can assess not only what an agent is resolving, but where that resolution leads and what level of risk is implied—before any encrypted data exchange occurs.

This contextual view is especially important as AI agents behave proactively, continuously discovering new “skills”, experimental services, and emerging repositories. While NRDs are statistically meaningful in phishing, malware, and abuse infrastructure, legitimate services also originate from newly registered domains. DNS intelligence provides the broader context required to distinguish innovation from exposure, enabling security teams to observe and govern what an agent is discovering and implicitly trusting at the precise moment when intervention is still possible—before a single byte of encrypted traffic leaves the enterprise network.

Cognitive Context Theft

Research from Hudson Rock into the agentic ecosystem reveals a chilling new category of risk: Cognitive Context Theft. Traditional malware hunts for passwords; modern infostealers like RedLine, Lumma, and Vidar have already adapted their “FileGrabber” modules to target local-first AI directories like ~/.clawdbot/. These agents store “memories,” user profiles, and session summaries in plaintext Markdown (MEMORY.md) and JSON files. This is not just data; it is a “psychological dossier” of the user, containing private anxieties, current projects, and trust relationships.

Tearing Down 20 Years of Security Boundaries

AI agents are, by design, antithetical to modern OS security. To be useful, they require the very holes in the walls that we’ve spent decades patching. They need filesystem access, credential persistence, and the ability to execute code. Moltbot doesn’t slough off the underlying architectural risks. When these agents run on corporate endpoints, they create “Hard Stop Zones” that require immediate CISO intervention:

• Localhost Binding Issues: Misconfigurations often lead to auto-authenticating localhost connections that expose months of private secrets to the web.
• VPN-Connected Endpoints: Agents running on corporate laptops and mobile devices with active VPN sessions allow for nearly unlimited lateral movement.
• Metamorphic Code: Logic that updates itself at runtime, effectively invalidating any EDR baseline.

The API-Powered Insider: Why Your Next Breach Might Be “Authorized”

We are entering the era of the Agentic Insider Threat. A compromised, hijacked, or subtly poisoned AI agent is operationally indistinguishable from a highly productive employee. It does not bypass perimeter defenses—it operates within them, because it effectively is the perimeter.

Local-first agents, designed to be proactive and deeply integrated with the endpoint, unintentionally create a high-value aggregation point for attackers. Their persistent access to files, credentials, browser context, and workflows produces a “honeypot” effect that is far more attractive than traditional malware targets. Once embedded, such agents can function as durable access mechanisms that are significantly harder to detect and evict than conventional Trojans.

This risk is amplified by well-intentioned but inexperienced users who adopt personal or semi-autonomous agents to improve daily productivity. Drawn by convenience and capability rather than security posture, these users may unknowingly introduce long-lived, privileged software actors into enterprise environments—expanding the insider threat surface without malicious intent, but with material organizational risk.

From Execution Prevention to Discovery Governance

For any CISO in 2026 and beyond, the strategic shift is clear—moving from a world of “Execution Prevention” to “Discovery Governance.” The adoption of AI agents as the productive digital workforce can not and will not be stopped, but we must govern what they are allowed to discover and trust. Here are some immediate actions for CISOs to think about:

1. Identity Classification: Formally classify all AI agents as Non-Human Identities (NHIs) within your IAM framework.
2. Infrastructure Whitelisting: Use DNS intelligence to flag interactions with NRDs or high-risk hosting provider neighborhoods.
3. The “Kill Switch”: Implement emergency revocation (the “Kill Switch”) for agent tokens, moving from code review to behavioral outcome auditing.

Conclusion: The Era of Delegated Judgment

In an agent-driven world, code is no longer static and trust is no longer fixed. The traditional boundary between the user and the Internet has been fundamentally redefined, replaced by AI agents that continuously make judgment calls on behalf of their operators—often without direct human awareness at the moment those decisions occur.

The rise of AI Agent Surface Management (ASM-AI) is not about constraining innovation or reversing autonomy. It is about ensuring that authorized exploration does not become ungoverned exposure. Organizations have spent decades building defenses against external threats; the next security challenge lies in governing the risks introduced by systems that are explicitly authorized to explore, discover, and trust on their behalf. The critical and urgent question for CISOs now is whether the enterprise is prepared to manage the security implications of delegated judgment (by AI) before it quietly reshapes the attack surface from within.