AuthMind enhances identity observability to secure vaults, secrets, and NHIs

AuthMind has announced that its platform offers enhanced capabilities to address the fast-growing security concerns surrounding vaults, secrets managers, and AI-driven workloads.

Since its founding, AuthMind has focused on securing identity access and execution paths across agentic AI, non-human identities (NHIs), and human users, enabling enterprises to observe what identities actually do across cloud, network and infrastructure environments. As adoption of agentic AI and automation accelerates, the identity-to-secret attack surface has expanded, increasing the urgency for deeper observability into vault and secret ecosystems.

Vaults and secrets managers securely store credentials, but they do not detect misuse once secrets are retrieved, nor do they provide visibility into shadow vaults or risky access paths surrounding them. As NHIs and AI agents multiply, these massive, never-before-addressed blind spots create opportunities for attackers to operate through “legitimate” access.

AuthMind extends its identity observability to:

• Detect shadow or unmanaged vaults and secrets managers
• Identify anomalous or unauthorized authentication paths into vaults
• Flag overly permissive roles retrieving excessive secrets
• Surface vault, PAM or key management bypass scenarios
• Monitor how secrets are used or misused once retrieved

“AuthMind has always uniquely secured identity access paths,” said Shlomi Yanai, CEO of AuthMind. “As AI agents and NHIs accelerate, secrets and vaults have become critical identity control points. By addressing the vulnerabilities they create, AuthMind’s extended observability ensures that vault access and secret usage are used as intended.”

NHIs, workloads, vaults and secrets no longer operate independently. They form a single access chain. A misused NHI can lead directly to secret exposure, enabling lateral movement across systems. AuthMind empowers organizations to proactively detect and remediate identity-driven threats across AI, non-human and human identities, ensuring secrets and workloads are used only in the right context, by the intended identities, at the right time.