Aembit Workload IAM Platform

Issues short-lived, on-demand credentials to workloads at runtime instead of relying on long-lived static service-account secrets, so credentials expire automatically and reduce the standing attack surface.

Issues attested, environment-bound identities to workloads (APIs, applications, containers, services, AI agents) using SPIFFE or cloud-managed workload identities, verifying each workload at runtime before a credential is issued and federating trust across clusters, clouds, and partner domains, so shared static credentials and the secret-zero bootstrap problem disappear.

Treats AI agents as first-class machine identities: unique identity per agent, short-lived purpose-bound credentials, fine-grained dynamic authorization, and linkage to a human owner or supervisor.

Tracks ownership and provides continuous observability for every machine identity - who owns it, what it accesses, how its credentials and privileges are used - across secrets, keys, certificates, and cloud identities.

Enforces least-privilege access for workload-to-workload and workload-to-service connections at runtime: each access is evaluated against policy and context, then brokered through token exchange, credential injection, or a proxy so the workload never holds a standing credential, including for legacy applications that cannot speak SPIFFE, OAuth, or X.509. Just-in-Time Credential Issuance covers minting short-lived credentials; this row covers the policy decision and injection at access time.

Continuously discovers and inventories machine identities and the workloads that use them across cloud and on-premises environments: service accounts, API keys, OAuth applications, cloud provider roles, Kubernetes service accounts, and AI agents, as well as TLS, SSH, and code-signing certificates and keys, so unmanaged and unknown identities are brought under management.