Skip to main content
LLM Security Database
Skip to research search
Last analyzed 9/9/2026

Language Model Security Database

985 research findings · 1123 evaluated models

Filtered research findings

11 entries

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

LLM Risk Amplification

Published 1/1/2025
Analyzed 12/9/2025

Vision Language Models (VLMs) are vulnerable to visual prompt injection attacks via text-to-image obfuscation. While these models often possess safety guardrails for standard text-based inputs, they fail to apply equivalent safety alignment to textual instructions embedded visually within an image. An attacker can overlay malicious instructions (e.g., requests for illegal acts, hate speech) onto an image file and submit it to the model. The model’s Optical Character Recognition (OCR) or visual…

Lessons from red teaming 100 generative ai products
Evaluated models: GPT-4, Phi-3

Source: arXiv

Model layer
Application layer
Prompt layer
Injection

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.