6건 · 관련도순
Design layered protections for AI agents against malicious instructions, tool misuse, and data leakage. Provides guidance and code examples for input checks, isolated tool execution, permission limits, and audit logging to help review and strengthen agent security.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Test Model Context Protocol (MCP) servers and tool-calling systems for security vulnerabilities including tool injection, parameter manipulation, privilege escalation, and data exfiltration through AI agent tool interfaces. Use this skill when assessing MCP server implementations, AI agent tool integrations, or any system that exposes tools to language models. Covers tool confusion attacks, cross-tool exploitation, and MCP server hardening assessment.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Test AI agent systems for tool abuse, unauthorized actions, privilege escalation through tool chaining, and safety bypass via agentic workflows. Use this skill when assessing autonomous AI agents that use tool-calling (function calling, plugins, actions) to interact with external systems. Covers multi-step attack chains, implicit trust exploitation, and capability boundary testing for AI agents.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.