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Tag: AI Workloads

Aembit’s AWS Secrets Manager integration makes it easier to protect AI and workload access today – and evolve toward short-lived, policy-driven authentication.
From rule-based chatbots to autonomous agentic AI, we’ve come a long way in past three decades.
Credentialitis isn’t just a clever name. It’s a real condition plaguing modern IT teams. Dr. Seymour Keys is here to walk you through the symptoms, the screening, and the treatment.
Learn why static API keys put AI agents at risk and how workload identity and dynamic credentialing eliminate secrets, stop prompt injection attacks, and future-proof LLM security.
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.
The vulnerability shows how modern application development is accelerating without bringing access controls along for the ride.
A down-to-earth primer to help engineers make sense of agentic AI architecture and where things stand today.
Secrets managers worked when workloads stood still. Agentic AI is forcing the vault door shut.
Security teams are shifting their focus from securing individual users to securing everything that acts on behalf of a user, especially when that “thing” is software.