multimodal-security

What problem does it solve?

Review a multimodal AI system for adversarial images, OCR prompt injection, hidden text, typographic attacks, unsafe visual grounding, and vision-to-action trust-boundary failures. This guide helps security engineers map attack surfaces, validate inputs, and implement guardrails around vision-derived content.

Core Features & Use Cases

• First Principle, Attack Mental Model, Control Lens, and containment patterns for vision-language systems.
• Evaluate vulnerabilities like hidden text injection, typographic attacks, adversarial overlays, and screenshot-as-instruction, then apply deterministic validation and policy gates.
• Use Case: assess a product's image and OCR workflows to ensure image-derived content cannot authorize actions or modify memory without explicit non-visual validation.

Quick Start

Review the multimodal security controls and list actionable recommendations to harden a given pipeline.