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From ASR to ASP: Evaluating Prompt Attack Vulnerabilities Against Open-Source LLMs
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
Research paper evaluates prompt injection attack vulnerabilities across 14 open-source LLMs used in sensitive domain applications.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 28 September 2026
- Collected by OneBench
- 29 Sept 2026, 03:01 UK
Stored source excerpt
arXiv:2505.14368v3 Announce Type: replace-cross Abstract: Recent studies demonstrate that Large Language Models (LLMs) are vulnerable to attacks that generate harmful or sensitive outputs. As open-source…
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