The Secrets Misuse Crisis: How Unmanaged Vaults, Agentic AI and NHI Blind Spots Create Critical Enterprise Risk

Enterprises invest heavily in secrets management and vault technologies to secure and modernize non-human and agentic AI identities, support the rapid growth of access and authentication, reduce credential sprawl and centralize the tokens, API keys, credentials and certificates used to access critical systems. Yet, even with a vault in place, organizations continue to face security risks stemming from misconfigured vaults, unauthorized vault access, unauthorized secrets removal and shared or reused secrets.  

Why? Because the problem isn’t just the need to store secrets securely, its understanding of how identities actually access, remove and interact with them in real enterprise environments.

Just as identity systems have become siloed across cloud, SaaS and hybrid environments, secrets management has followed the same trajectory. Secrets and vaults proliferate, controls drift, machine identities and AI agents continue to multiply, different teams manage different secrets and shadow deployments emerge outside governance, and identities usage of secrets is very hard to control, once left the vault . Because of this, attackers or malicious insiders increasingly exploit the widening gaps between identity behavior, vault authentication, and secret usage.

The result: a fast-growing identity and access blind spot that organizations can no longer afford to ignore.

The Unseen Expansion of Vault Risk

Most enterprises rely on their vault deployments to be centrally managed, policy-driven and properly integrated into IAM workflows, but reality can look very different:

Shadow and Unmanaged Vault Instances Are Everywhere

Teams frequently create new Vault instances for CI/CD, automation or testing, but many never enter centralized governance, exposing secrets without organizational oversight. These unmanaged vaults can often (for example):

• Use insecure (default) settings

• Rely on wildcard or overly permissive role bindings and policies/rules

• Duplicate or misspelled IAM role names across accounts

• Operate without meaningful monitoring, logging, or oversight

This creates a critical blind spot where secrets exist but do not fall under monitoring, policy enforcement, or identity governance.

Authentication Bypass 

Even governed vaults can suffer from identity risks caused by:

• Brute-force authentication attacks, denial of service (DoS), and admin enumeration activity

• Shadow admin and identities accessing the vault (e.g., local accounts)

• Unauthorized or unusual admin access

• Admins not managed through the IDP

• Local or legacy auth methods still enabled

• Lack of MFA enforcement

• Zero-day bugs in authentication, policy, and identity modules

• Non-human and AI-Agent identities authenticating unexpectedly

  
  

Attackers increasingly exploit these weaknesses by appearing to authenticate as “legitimate” users, AI Agents  or NHIs, gaining unauthorized access to secrets.

Secret Retrieval Abuse Is Hard to See, and Even Harder to Prevent

Because secret retrieval often appears legitimate, secret misuse can be easy to miss. This can be common in scenarios where:

• A secret is retrieved by unauthorized or anomalous role impersonation

• A secret is retrieved by a direct machine-to-vault impersonation

• Secrets are retrieved by shadow access, including access from unexpected IPs, geographies or sources

• Secrets are updated or deleted in an unexpected or unauthorized manner

• Overly permissive roles or human activity through machine-assumed roles are retrieving secrets

• A machine retrieves a secret correctly, but a human later logs into the same system and misuses it

• Kubernetes pods access ConfigMaps they should never see

  
  

These instances hide inside approved identity infrastructures, making them nearly invisible with traditional tools. The main reason for that is that  attempting to correlate and make sense of disparate log/monitoring sources is a challenge for DevOps/Ops teams.

Secret Usage Governance Is Still an Afterthought

Most organizations track, govern, and audit the retrieval of secrets, but not their usage and not the identities and applications/services that are working with the secrets. This leaves major gaps:

• Shared or reused secrets across multiple applications

• PAM or vault bypass scenarios with secrets

• Expired dynamic secrets still being consumed

• Repeated (mis)use of one-time or hardcoded/static secrets

• Orphaned secrets active long after workloads disappear

• Compromised secrets granting downstream access

  
  

When secrets behave like identity credentials, not just tokens or keys, visibility into their end-to-end lifecycle becomes essential. 

The Identity to Secret Relationship Is Broken

The core challenge is that organizations are not able to trace the full identity-to-secret lifecycle across cloud, workload, and application boundaries.

Identity telemetry lives in one place, vault logs live in another, application behavior is somewhere else entirely and machine identities and shadow access are often invisible.

This fragmented model creates observability gaps that attackers can exploit. If they can assume a role, impersonate a workload or manipulate a misconfiguration, they can retrieve secrets and operate undetected.

To close this gap, organizations must be able to connect the full chain:

Identity → Role Assumption → Vault Authentication → Secret Retrieval → Secret Usage

Without this end-to-end observability, even the most mature vault deployments remain exposed to misuse and lateral movement.

What’s Needed to Secure Secrets & Vaults Today

Solving the growing secrets and vault-misuse problem requires more than configuration checks or traditional IAM tools. Enterprises need a modern approach that acknowledges how human and machine identities interact with vaults and retrieve and use secrets across cloud, SaaS, and Kubernetes environments.

Ultimately, securing secrets today demands complete identity observability for a true understanding of how secrets are accessed and used, not just how they’re stored.

At a minimum, organizations should prioritize:

• Comprehensive discovery and visibility into all Vault instances, sanctioned, unsanctioned, and shadow, along with their configurations and identity interactions.

• Strong authentication & authorization hygiene, including detection of misconfigured IAM/EC2/Kubernetes/other auth methods, wildcard, shadow or duplicate roles and any form of authentication bypass.

• Continuous monitoring of secret retrieval behavior, flagging anomalous access, identity impersonation or unexpected machine/human patterns.

• Lifecycle governance of secret usage, ensuring observability into how secrets are consumed during and after retrieval and detecting misuse such as secret reuse, sharing, unauthorized storage/caching or unauthorized downstream access.

• End-to-end identity to secret observability, correlating identity and access behavior, role assumptions, Vault authentication, secret retrieval and secret usage into a single chain of context.

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These capabilities form the foundation of a modern identity and secrets security strategy, one aligned with how identities and workloads truly behave in today’s environments.

Conclusion: secrets are a the mean to authenticate and Authorize  Identity activities, and a growing attack surface

Vaults were designed to simplify identity and secrets security, but modern cloud, AI Agents and NHI complexity has turned secrets into a major, often invisible, security risk.

Identity and security teams cannot rely only on static policies, configuration scanning or siloed identity tools. They need continuous, unified and end-to-end identity observability, giving insights into how secrets move through their environment across their entire lifecycle.