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The Agent Incident Registry: Toward Preventing Repeated AI Agent Failures
Divyanshu Kumar, Rohith HN, Nitin Aravind Birur +2
AI agents increasingly act through tools and delegated authority, but general incident repositories rarely capture the mechanisms needed to compare public failures with agent-secur…
Black-Box Red Teaming of Agentic AI: A Taxonomy-Driven Framework for Automated Risk Discovery
Divyanshu Kumar, Nitin Aravind Birur, Tanay Baswa +2
Agentic systems are rapidly moving to production, where they read untrusted inputs, call tools with real permissions, and act autonomously, expanding the security surface beyond ch…
Redirected, Not Removed: Task-Dependent Stereotyping Reveals the Limits of LLM Alignments
Divyanshu Kumar, Ishita Gupta, Nitin Aravind Birur +3
How biased is a language model? The answer depends on how you ask. A model that refuses to choose between castes for a leadership role will, in a fill-in-the-blank task, reliably a…
SocioEval: A Template-Based Framework for Evaluating Socioeconomic Status Bias in Foundation Models
Divyanshu Kumar, Ishita Gupta, Nitin Aravind Birur +3
As Large Language Models (LLMs) increasingly power decision-making systems across critical domains, understanding and mitigating their biases becomes essential for responsible AI d…