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Updated 7/21/2026, database is current

Language Model Security Database

959 research findings · 1077 evaluated models

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1 entry

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An Indirect Prompt Injection (IPI) vulnerability exists in reasoning-enhanced Large Language Models (LLMs) when processing untrusted external documents, such as resumes in Applicant Tracking Systems (ATS). Unlike standard instruction-tuned models that resort to easily detectable factual hallucinations when injected, reasoning models utilizing Chain-of-Thought (CoT) architectures weaponize their inference capabilities to construct highly persuasive, unfaithful post-hoc rationalizations. They…

Trojan Horses in Recruiting: A Red-Teaming Case Study on Indirect Prompt Injection in Standard vs. Reasoning Models
Affects: Qwen 3 30B-A3B Instruct-2507, Qwen 3 30B-A3B Thinking 2507

Source: arXiv

Research methodology

Entries summarize publicly available primary-source security research. Model names reflect only systems explicitly evaluated by the cited paper, and measurements are research-reported unless independent verification is stated.