context-security-guardian

To validate AI context artifacts before loading, use a pre-loading security gate that scans every artifact in .ai-context to detect credential theft, data exfiltration, and destructive commands before activation. It returns a JSON object with blocked status, severity, and findings.

Pre-load security validation for AI context is a middleware mechanism that inspects skills, agents, rules, and workflows for high-severity threats before they are applied. It blocks offending artifacts, preserves evidence, and logs findings for remediation.

To quarantine dangerous instructions in AI context rules, the validator blocks the offending artifact from loading, preserves the evidence, and logs the findings for remediation. This ensures risky instructions are never activated while maintaining a transparent audit trail.

Yes, AI context security validation operates automatically across skill activations, agent selections, rule applications, and context edits. It detects high-severity threats across the entire context to ensure safe artifact loading and quick remediation when threats are detected.

Yes, you can use a security middleware to block data exfiltration and policy bypass in AI context. The pre-loading validator detects dangerous patterns like unauthorized access and destructive commands, returning a JSON object to control artifact loading and reporting.

Pre-loading security gates for AI context require the validator to run before any artifact is processed, meaning it must be placed correctly under .ai-context. It specifically targets high-severity threats, and effective remediation depends on reviewing the logged findings and blocked artifacts.