Generate adversarial examples and attack ML models in CTF challenges.
npx skills add https://github.com/DexterJie/codex-skills --skill ctf-ai-ml-dexterjie
Please help me install this Agent Skill. Skill: ctf-ai-ml Source: https://github.com/DexterJie/codex-skills/tree/main/ctf-ai-ml Command: npx skills add https://github.com/DexterJie/codex-skills --skill ctf-ai-ml-dexterjie
This Skill provides a comprehensive toolkit for tackling AI and ML challenges in Capture The Flag (CTF) competitions, offering techniques for attacking ML models, crafting adversarial examples, and solving AI-related puzzles.
Execute 'ctf-ai-ml inspect-model model.pt' to inspect the structure of a provided ML model.
High-intent search queries and answers about installing and using this skill.
To craft adversarial examples, you can use techniques that manipulate inputs to fool machine learning classifiers. This skill provides generation methods to exploit underlying model vulnerabilities and bypass target AI security mechanisms.
Model inversion is a technique to recover model parameters from target outputs. This skill provides tooling to reconstruct or extract underlying machine learning model weights and architecture from observed prediction data.
Yes, you can inspect safetensors models and exploit LoRA adapters. This skill requires Python 3 with torch and transformers to analyze model structures and solve AI-related puzzles involving weight manipulation.
Yes, attacking ML models requires internet access for tool installation and Python 3 dependencies including torch, transformers, numpy, scipy, Pillow, and safetensors to execute the provided machine learning exploitation scripts.
The best way to perform membership inference attacks is by analyzing target model prediction confidence. This skill provides techniques to determine if specific data records were included in a model's training dataset.
You can inspect a provided ML model structure by executing 'ctf-ai-ml inspect-model model.pt'. This allows you to analyze the architecture and identify potential exploitation vectors for AI-related challenges.
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xjtu-wangRecover malware configuration fields, staged payloads, and beacon parameters from sandboxed samples.
nimosocuteAnalyze compiled, obfuscated, packed, or virtualized CTF binaries.
Prohao42Assess AI/ML security risks and craft defensive playbooks.
