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Last analyzed Sep 9, 2026

Language Model Security Database

985 research findings · 1119 evaluated models

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2 entries

Matches every word across titles, descriptions, sources, affected systems, and models.

VLM In-the-Loop Adversary

Published Analyzed Source: arXiv

The VILTA (VLM-in-the-Loop Trajectory Adversary) framework is vulnerable to Prompt Injection and Data Poisoning via un-sanitized scene representation inputs. The system integrates a Vision-Language Model (Gemini-2.5-Flash) into a closed-loop reinforcement learning environment, feeding it Bird’s-Eye-View (BEV) imagery alongside text-based vehicle dynamics data (e.g., position, speed, and risk_category) to generate challenging driving trajectories. An attacker who can manipulate the input…

VILTA: A VLM-in-the-Loop Adversary for Enhancing Driving Policy Robustness
Evaluated models: Gemini 2.5 Flash
Vision
Multimodal
Black-box
AI agents

Flowchart-based LVLM Jailbreak Attack

Published Analyzed Source: arXiv

FC-Attack leverages automatically generated flowcharts containing step-by-step descriptions derived or rephrased from harmful queries, combined with a benign textual prompt, to jailbreak Large Vision-Language Models (LVLMs). The vulnerability lies in the model's susceptibility to visual prompts containing harmful information within the flowcharts, thus bypassing safety alignment mechanisms.

FC-Attack: Jailbreaking Large Vision-Language Models via Auto-Generated Flowcharts
Evaluated models: Claude 3.5 Sonnet 20240620, Gemini 1.5 Flash, GPT-4o 2024-08-06+4 more
  • Claude 3.5 Sonnet 20240620
  • Gemini 1.5 Flash
  • GPT-4o 2024-08-06
  • GPT-4o Mini 2024-07-18
  • InternVL2.5 8B
  • LLaVA NeXT 8B
  • Qwen2-VL 7B Instruct
Model layer
Application layer
Prompt layer
Vision

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.

Discovery and publication are separate: new papers enter a candidate queue, then require human review and explicit approval before publication. Updates follow that review process, not a guaranteed daily publishing schedule. “Last analyzed” is the newest analysis date among published entries; it does not mean that all recent research has been covered.