Vision-Based Injection
Vision-Based Injection is an attack technique that embeds malicious instructions or deceptive content within images or other visual inputs to manipulate a vision-capable AI model into performing unintended actions.
What is Vision-Based Injection?
Vision-based injection exploits AI systems that can interpret visual content. An attacker may place instructions, text, symbols, or other deliberately crafted elements inside an image that appears harmless to a human but is interpreted as instructions by the model. The attack can target the model directly or influence downstream tools and workflows.
Why is Vision-Based Injection Important?
Vision-based injection expands prompt injection risks beyond text. AI applications that process screenshots, documents, images, or camera feeds may unintentionally treat visual content as trusted instructions, potentially leading to unsafe responses, unauthorized actions, or sensitive data exposure.
Common use cases
Vision-Based Injection is commonly discussed in multimodal AI security, prompt injection testing, AI red teaming, document processing, visual agents, and security assessments of vision-language models.