Author

Animesh Shaw

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#machine learning Preprint Sep 2026

Silent Failures in Agentic Security Evaluation: A Validated Harness for Tool-Call Mediation Under Indirect Prompt Injection

LLM agents that invoke privileged tools are vulnerable to indirect prompt injection (IPI), in which adversarial instructions embedded in retrieved data hijack the agent's actions. A growing body of work evaluates defenses against IPI, but the validity of that evaluation is rarely examined. We audit an IPI benchmark and...

Animesh Shaw · 0 citations

#artificial intelligence Preprint Aug 2026

Compared to What? A Human-Anchored Security Benchmark for LLM-Generated Infrastructure-as-Code

GenIaC-SecBench is introduced, a benchmark of 100 deployment scenarios stratified by architectural complexity, evaluated across 12 model configurations from four vendors, producing 1,196 IaC artifacts scanned by three independent policy engines (Checkov, Trivy, KICS).

Animesh Shaw · 0 citations