aw-junaid/Machine-Learning-For-Security
Explore ML for security: anomaly detection, malware classification, and threat prediction. Includes datasets, models, and tools for AI-driven cybersecurity solutions.
This resource helps cybersecurity professionals understand, detect, and mitigate a specific type of attack called 'prompt injection' in machine learning models, especially large language models (LLMs). It takes in examples of malicious prompts or model responses and provides insights, tools, and methods to identify and prevent these models from being tricked into revealing sensitive information or misbehaving. Security analysts, red teamers, and AI developers building secure LLM applications would use this to protect their systems.
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Use this if you are a cybersecurity professional or AI developer concerned about your machine learning models being manipulated or exploited through cleverly crafted text inputs (prompts).
Not ideal if you are looking for general machine learning tutorials unrelated to security vulnerabilities, or if your primary focus is on traditional network or endpoint security without an emphasis on AI systems.
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Mar 04, 2025
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