skill-security-framing

To prevent prompt injection during web content analysis, you must sanitize fetched data by wrapping it as untrusted data and applying protocol checks, hostname filtering, and size limits before processing.

URL validation for AI workflows is the process of checking protocols, hostnames, and private network targets before retrieving external content, preventing unsafe processing of malicious links and blocking data exposure risks.

Securely process untrusted API responses by applying content sanitization frameworks that enforce size limits and prompt injection defenses, isolating webhook payloads as untrusted data before AI analysis begins.

Yes, secure content framing includes hostname filtering that actively blocks private network targets and malicious patterns, preventing external documents from triggering unsafe internal network requests.

Apply security framing whenever an AI agent retrieves and analyzes external articles, documents, or API responses, ensuring all fetched content is treated as untrusted data to reduce data exposure risks.