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Ctf AI ML

DevOps & Security
ctf-ai-ml

Ctf AI ML is an Agent Skill for devops & security published in the wgpsec/AboutSecurity repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

CTF AI/ML 攻击技术。当挑战涉及 AI 模型攻击、对抗样本生成、模型提取、Prompt 注入/越狱、LoRA 权重操纵、LLM Token 走私、成员推理攻击、训练数据投毒、神经网络分析时使用。覆盖 FGSM/PGD/C&W 对抗攻击、模型反演、模型权重扰动还原、LLM 工具链劫持、上下文窗口操纵等 AI 安全全链路攻防技术

View on GitHub ↗
QUICK START

How to use this skill

Bring this guide into your coding agent with a prompt tailored to the tool you use.

  1. Open your project in Codex.
  2. Copy and paste the prompt below.
  3. Review files and risks before approving any action.
Prompt to paste
Inspect the Agent Skill at https://github.com/wgpsec/AboutSecurity/blob/HEAD/skills/ctf/ctf-ai-ml/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/ctf-ai-ml, but wait for my approval before writing files or running scripts.

Copying this prompt does not install or run the skill. Review third-party files before use.

CTF AI/ML Attack Techniques

When to Use

  • Challenge involves ML model files (.pt, .pth, .safetensors, .onnx, .h5)
  • Target is an AI chatbot, LLM-based application, or ML classifier
  • Need to craft adversarial examples to fool image/text classifiers
  • Challenge provides model weights for analysis or manipulation
  • AI/ML platform security testing (model extraction, membership inference)

Quick Start

pip install torch transformers numpy scipy Pillow safetensors scikit-learn
file model.*
python3 -c "import torch; m=torch.load('model.pt'); print(type(m), m.keys() if hasattr(m,'keys') else '')"

Decision Tree

  1. Model weight file (.pt/.safetensors) → model-attacks.md
    • Weight perturbation negation, model inversion, LoRA merging, encoder collision
  2. Image classifier to fool → adversarial-ml.md
    • FGSM, PGD, C&W attacks, adversarial patches, evasion, data poisoning
  3. LLM/chatbot target → llm-attacks.md
    • Prompt injection, jailbreaking, token smuggling, tool use exploitation
  4. Pure math/crypto inside ML → Switch to ctf-crypto
  5. Compiled model binary → Switch to ctf-reverse
  6. Python jail wrapped in chatbot → Switch to ctf-misc

Pivot Signals

  • If challenge is pure cryptography/number theory with no ML → /ctf-crypto
  • If reverse engineering compiled inference binary → /ctf-reverse
  • If Python sandbox escape inside chatbot wrapper → /ctf-misc
  • If web app with AI features (prompt injection via web) → /ai-security/prompt-injection