Exercises
| Exercise | Avg. Time | Difficulty | Solved by | Tier | |
|---|---|---|---|---|---|
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CVE-2026-55415: Schema Import Injection
Gain code execution by injecting Python through a crafted JSON Schema when the generated Pydantic model is imported.
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22 | PRO | ||
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ODF XXE
This exercise covers the exploitation of an XXE in an ODF Parser
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23 | PRO | ||
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SOAPBridge: Savon WSDL Code Injection
Gain code execution through an unsafe module_eval call during WSDL import.
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21 | PRO | ||
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Secure Design: Safe Serialization | 29 | PRO | ||
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Secure Design: Secret & Credential Management | 33 | PRO | ||
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Secure Design: Control Placement | 58 | PRO | ||
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Secure Design: Backend Authentication Proxy | 30 | PRO | ||
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AI Fundamentals: Tool Use & Agents | 65 | PRO | ||
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AI Fundamentals: Retrieval-Augmented Generation | 66 | PRO | ||
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Open Door
No guardrails at all. Simply ask the model for the secret key.
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144 | PRO | ||
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AI Fundamentals: Multimodal Models | 62 | PRO | ||
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Instruction Hierarchy
The system prompt explicitly establishes an instruction hierarchy. Find a way to confuse or bypass the priority system.
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54 | PRO | ||
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Encoding Request
Multiple extraction vectors are blocked. Find a creative approach the rules don't anticipate.
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55 | PRO | ||
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System Prompt Extraction
The model is told to keep a secret key and refuses to reveal it directly. The rule only forbids telling the key, not repeating the instructions that contain it. Make the model recite its own system prompt and the key comes with it.
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112 | PRO | ||
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Polite Refusal
The model is told to refuse key requests. Use social engineering to convince it to share anyway.
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88 | PRO | ||
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AI Fundamentals: Using Models in Practice | 63 | PRO | ||
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AI Fundamentals: Training an LLM | 66 | PRO | ||
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AI Fundamentals: Large Language Models | 67 | PRO | ||
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AI Fundamentals: Inference & Sampling | 65 | PRO | ||
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AI Fundamentals: Limitations & Hallucinations | 66 | PRO | ||
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AI Fundamentals: Prompting | 66 | PRO | ||
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AI Fundamentals: Deep Learning | 80 | PRO | ||
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AI Fundamentals: Classic ML Algorithms | 89 | PRO | ||
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AI Fundamentals: Embeddings & Vectors | 77 | PRO | ||
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AI Fundamentals: Transformers & Attention | 72 | PRO | ||
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AI Fundamentals: Evaluating Models | 95 | PRO | ||
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AI Fundamentals: Tokenization | 77 | PRO | ||
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AI Fundamentals: Overfitting & Generalization | 107 | PRO | ||
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AI Fundamentals: Neural Networks | 84 | PRO | ||
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AI Fundamentals: Data, Features & Labels | 133 | PRO |
Showing 61–90 of 851 exercises
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