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Tag: AI Workloads

JIT access replaces the common practice of issuing and locally storing keys with a workflow that evaluates a workload’s rights every time it tries to access sensitive data.
From Coca-Cola to Campbell Soup, Renee Guttmann knows what lasts as security changes.
The organizations succeeding with agentic AI are deploying it with constraints.
How do you govern entities that can learn, adapt, and act independently while maintaining security and compliance?
The dynamic nature of MCP makes a lack of visibility dangerous, as attackers can exploit complex workflows and ephemeral infrastructure to hide malicious activity.
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.