Extract a functional clone of a black-box ML model via prediction API queries, and infer whether specific records were in the training set (membership inference).
Security
1 critical severity finding. Installing this skill is not recommended: please review these findings carefully if you do intend to do so.
Detected high-risk code patterns in the skill content — including its prompts, tool definitions, and resources — such as data exfiltration, backdoors, remote code execution, credential theft, system compromise, supply chain attacks, and obfuscation techniques.
This document contains explicit, actionable instructions and code to perform unauthorized model extraction and membership inference (data/model theft) along with operational evasion techniques, indicating deliberate malicious intent.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
The SKILL.md includes explicit runtime commands that clone and execute remote code from https://github.com/ftramer/Steal-ML (git clone ...; pip install ...; python steal.py), so the skill fetches and runs external code at runtime.
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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.