Dan Kaplan

Director of Content Marketing

Expertise

  • Cybersecurity
  • Identity and access management
  • Non-human identity
  • Workload identity and access management
  • AI agent identity and security
  • Cloud security
  • Security operations
  • Threat detection and response
  • Cybersecurity journalism
  • Content strategy
  • Editorial strategy

About Author

Dan Kaplan is the friendly neighborhood content marketing leader at Aembit. Based in New York but operating remotely, he tells stories about agentic identity, workload identity, and cybersecurity that are meant to educate, inspire and, if he’s lucky, even entertain. Before joining Aembit, Dan held a similar role at Google Cloud, following stints at Siemplify and Trustwave, where he led content initiatives. He planted his roots in cybersecurity as a reporter and editor at SC Media. When he’s not conjuring content, he can usually be found watching sports, advocating for farm animals, or listening to paranormal stories as he falls asleep. Don’t ask.

Education

  • Bachelor’s degree in journalism, Syracuse University, S.I. Newhouse School of Public Communications

Articles by Dan Kaplan

Most organizations start their nonhuman identity security program with a secrets manager. It’s a sensible first step. But as workloads multiply across clouds and the credential sprawl grows, the question shifts from “where do we store secrets?” to “do we need secrets at all?”
Anthropic’s disclosure of an AI-driven espionage campaign it halted is best understood as a faster, more persistent version of patterns the industry has seen before. What distinguishes this incident is the continuity of activity an autonomous system can sustain once it is given the ability to interpret its surroundings and act on that understanding.
Based on responses from more than 200 enterprises, the findings show how AI agents are reshaping identity attribution and access control in ways existing models were not designed to handle.
Zero-trust architecture is a security framework built on a simple premise: no user, device or workload should be trusted by default, regardless of where it sits on the network.
Agentic AI guardrails are the technical controls, policy frameworks, and oversight mechanisms that define what an AI agent can do, what it can access and when it needs to stop and ask a human.
Most organizations still treat credentials as something that must be protected, stored, and rotated. But a second model is quietly reshaping how machine authentication works: eliminate static secrets altogether and authenticate workloads using identity and just-in-time access.
Details shared by the attacker suggest the intrusion expanded beyond the initial application through permissions that allowed access to dozens of internal credentials.
Traditional IAM was built for predictable workloads. Learn why AI agents demand a new approach to identity, access control, and credential management.
Discover verifiable agentic AI deployments in software, security, IT Ops, and logistics. Learn the essential security, identity, and governance patterns for safe production use.
As agents scale and operate continuously, MCP servers are becoming long-lived access intermediaries, concentrating privilege in ways security teams have already struggled to contain.
Runnable security patterns that examine how agentic behavior expands, drifts, and exceeds intent during everyday use.
A ServiceNow impersonation flaw illustrates how agentic systems turn weak identity assumptions into durable access paths across enterprise environments.