Detect MITRE ATLAS AML.T0024 attacks (model stealing, inversion, membership inference) performed via inference-API abuse, by monitoring per-principal query volume/distribution, rate-limiting and perturbing outputs, and red-teaming your model's extractability. Use for a public or partner inference API needing cloning/inversion/membership-inference detection, or a pre-deployment red-team exercise to measure extraction risk.
日本語の概要は準備中です。原文の説明を表示しています。
mukul975/Anthropic-Cybersecurity-Skills☆ 3.4万2026年8月31日 更新
Detect model stealing, model inversion, and membership inference performed through inference-API abuse by monitoring query patterns, applying output perturbation, and red-teaming your own model's extractability.
日本語の概要は準備中です。原文の説明を表示しています。
andycungkrinx91/konoha☆ 92026年10月9日 更新
This skill should be used when the user asks to "scan AI systems for security threats", "check for prompt injection vulnerabilities", "assess model security posture", "detect data poisoning risks", or "audit AI/ML pipeline security".
日本語の概要は準備中です。原文の説明を表示しています。
borghei/Claude-Skills☆ 8962026年10月7日 更新