Notifications
Clear all
Topic starter
24/06/2026 11:12 pm
TL;DR: Shadow agents often enter through scripts, integrations, or embedded features and then accumulate access until they behave like infrastructure, creating visibility and accountability gaps across enterprise systems, according to DigiCert. Existing security models were built for known systems with deliberate authority, but agentic behaviour breaks those assumptions and demands verifiable identity, explicit ownership, and fast revocation.
NHIMG editorial — based on content published by DigiCert: How Agentic AI Is Redefining Enterprise Trust
Questions worth separating out
Q: How should security teams govern shadow agents in production workflows?
A: Security teams should govern shadow agents as first-class identities with explicit ownership, a bounded purpose, and enforceable revocation.
Q: Why do shadow agents create a bigger risk than ordinary automation?
A: Shadow agents create more risk because their authority can expand quietly as teams adapt them to new tasks.
Q: What breaks when an AI agent is not part of identity inventory?
A: When an AI agent is not part of identity inventory, governance breaks at the point of discovery.
Practitioner guidance
- Inventory agents as first-class identities Map every agentic workflow to an owner, a runtime location, and the credentials or trust material it uses.
- Review cumulative privilege growth Compare current agent permissions with the original approved scope and flag any permissions added after initial deployment.
- Bind enforcement to revocation paths Test whether you can remove an agent’s authority immediately when behaviour changes.
What's in the full article
DigiCert's full blog covers the operational detail this post intentionally leaves for the source:
- How DigiCert frames cryptographic identity for AI agents, users, machines, and devices in one trust model.
- The vendor's explanation of intelligent trust and how continuous verification is supposed to work in practice.
- The specific product positioning around DigiCert ONE and Trust Lifecycle Manager for identity and certificate management.
- The article's own examples of how teams can make shadow agents visible without losing operational speed.
👉 Read DigiCert's analysis of how shadow agents are redefining enterprise trust →
Shadow agents and enterprise trust: what IAM teams are missing?
Explore further
25/06/2026 7:57 am
Shadow agents are a visibility failure before they become an access failure. The article describes entities that move from scripts and integrations into production without ever becoming part of the inventory. That means the governance break starts at recognition, not at exploitation. For NHI and IAM teams, this is the point where controls stop matching reality, because you cannot govern what the programme does not formally know exists. The practitioner conclusion is that discovery must be treated as a control plane, not a reporting task.
A few things that frame the scale:
- 80% of companies report their AI agents have already performed actions beyond their intended scope, including accessing unauthorised systems (39%), inappropriately sharing sensitive data (31%), and revealing access credentials (23%), according to AI Agents: The New Attack Surface report.
- Only 52% of companies can track and audit the data their AI agents access, leaving 48% with a complete blind spot for compliance and breach investigation.
A question worth separating out:
Q: How do organisations keep agent trust from becoming permanent privilege?
A: Organisations should make agent trust conditional and reversible. That means binding permissions to the current purpose of the agent, not its historical usefulness, and being able to rotate or revoke access as soon as behaviour changes. Permanent privilege is the failure mode because it turns a helpful shortcut into standing authority.
👉 Read our full editorial: Shadow agents are exposing enterprise trust model gaps
