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multimodal-security-review

Review multimodal AI application input handling for injection and parsing security risks.

6|Updated May 30, 2026
Search Tags:#AI security#security review#input handling#AI application#multimodal input
One-click install
npx skills add https://github.com/jassics/awesome-claude-security --skill multimodal-security-review
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: multimodal-security-review
Source: https://github.com/jassics/awesome-claude-security/tree/main/plugins/multimodal-security/skills/multimodal-security-review
Command: npx skills add https://github.com/jassics/awesome-claude-security --skill multimodal-security-review

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Multimodal AI applications often overlook non-text inputs, leading to potential security risks. This Skill ensures thorough review of an AI application's handling of various modalities (image, audio, video, document) for secure operation.

Core Features & Use Cases

  • Multimodal Input Review: Analyze input handling and trust boundaries for all modalities.
  • Security Assessment: Detect injection, unsafe parsing, provenance, and output handling issues.
  • Use Case: Evaluate the security of a vision/audio/document-accepting feature in your AI application.

Quick Start

Run the multimodal-security-review skill to assess the security of your AI application's input handling.

Frequently Asked Questions about multimodal-security-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform a security review for multimodal AI application inputs?▼

To perform a multimodal AI security review, you analyze the application's input handling and trust boundaries across image, audio, video, and document modalities to detect injection, unsafe parsing, and output handling risks.

What security risks affect non-text inputs in AI applications?▼

Security risks in non-text AI inputs include multimodal injection attacks, unsafe file parsing, provenance issues, and improper output handling across image, audio, video, and document modalities.

How do I assess trust boundaries for AI applications accepting audio and video inputs?▼

Assessing trust boundaries for audio and video AI inputs involves analyzing how the application parses and processes multimodal data, verifying security controls prevent injection and unsafe handling across the architecture.

What is the best way to detect injection vulnerabilities in multimodal AI architectures?▼

The best way to detect injection vulnerabilities in multimodal AI architectures is reviewing input handling mechanisms across all modalities to identify unsafe parsing and weak security controls.

Do I need to understand my AI architecture to review multimodal input security?▼

Yes, reviewing multimodal input security requires a detailed understanding of your AI architecture and existing security controls to accurately assess trust boundaries and input handling risks.

When should I review trust boundaries for document and image processing in my AI app?▼

You should review trust boundaries for document and image processing when adding vision or document-accepting features, ensuring the multimodal AI application securely handles parsing and prevents injection.

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