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  **An OpenEnv RL Benchmark for Multi-Turn Adversarial Reasoning and Policy Defense**
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  ## 🧠 The Problem: The "Multi-Turn" Vulnerability in LLMs
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  Modern Large Language Models (LLMs) are heavily tested against single-shot prompt injections (e.g., "ignore previous instructions"). However, real-world manipulation and misalignment rarely happen in a single turn.
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  ```bash
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  python inference.py
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  ```
 
 
 
 
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  ## 👨‍💻 Author
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  Aditya Katkar
 
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  **An OpenEnv RL Benchmark for Multi-Turn Adversarial Reasoning and Policy Defense**
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+ Live deployment: [addyk24-strategic-argument-red-teaming-env.hf.space](https://addyk24-strategic-argument-red-teaming-env.hf.space)
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+ Repository: [github.com/Addyk-24/strategic-argument-red-teaming](https://github.com/Addyk-24/strategic-argument-red-teaming)
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  ## 🧠 The Problem: The "Multi-Turn" Vulnerability in LLMs
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  Modern Large Language Models (LLMs) are heavily tested against single-shot prompt injections (e.g., "ignore previous instructions"). However, real-world manipulation and misalignment rarely happen in a single turn.
 
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  ```bash
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  python inference.py
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  ```
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+ ### 4. Run the Environment Server:
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+ ```bash
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+ python app.py
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+ ```
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  ## 👨‍💻 Author
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  Aditya Katkar