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Tag: Workload Identity

Aembit’s AWS Secrets Manager integration makes it easier to protect AI and workload access today – and evolve toward short-lived, policy-driven authentication.
IAM migrations stall in hybrid enterprises due to massive on-prem Active Directory (AD) deployments, budget and regional constraints, and a lack of alignment among development, DevOps, and security teams.
Security teams can now correlate workload and agentic AI activity with broader enterprise telemetry, closing gaps before attackers exploit them.
Conditional access enhances security and reduces the attack surface without adding friction.
The core problem is that human IAM was never built for workload scale or behavior.
This integration brings workload identity and access data into Splunk, giving security teams clearer visibility, faster response, and stronger zero trust controls.
This malicious campaign demonstrates how long-lived token theft can become the first step in a much broader breach.
AI agents require broad API access across multiple domains simultaneously—LLM providers, enterprise APIs, cloud services, and data stores—creating identity management complexity that traditional workload security never anticipated.
Recent flaws in Conjur and Vault highlight the risks of concentrating trust in a single repository – and why workload IAM may offer a more resilient path forward.