adversarial-resilience

What problem does it solve?

Adversarial resilience prevents AI agents from being hijacked through prompt injection or from leaking sensitive data when processing untrusted inputs.

Core Features & Use Cases

• Defense-in-depth security layers: input sanitization, instruction anchoring, output filtering, permission boundaries, and audit logging.
• Untrusted-data handling: treats user-provided fields (including campaign names, ad copy, and keyword lists) as data only, not instructions.
• Secret and sensitive-data protection: scans outputs for likely credentials/PII patterns and redacts before returning responses.
• Execution guardrails: enforces allowed paths and blocks dangerous command patterns regardless of model intent.
• Forensic traceability: logs violations and actions to support post-incident analysis and compliance.

Quick Start

Use the adversarial-resilience skill to secure your agent by hardening how it ingests untrusted campaign data, restricts tool permissions, and prevents sensitive information from appearing in responses.