Showing posts with label AI_security_risks. Show all posts
Showing posts with label AI_security_risks. Show all posts

Monday, May 11, 2026

What Is AI Jailbreaking? How People Break AI Safety Rules

Every major AI assistant has safety guidelines — rules about what it will and will not help with. Jailbreaking is the practice of crafting prompts that convince an AI to ignore those rules. It does not require technical skills, just creative prompt writing. The AI does not get "hacked" in any traditional software sense — it is persuaded through text alone. Here is exactly how it works, why AI companies take it seriously, what the documented techniques look like at…

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Tuesday, May 5, 2026

What Is an LLM? Large Language Models Explained for Security Teams 2026

Every serious security topic in 2026 eventually requires understanding what a large language model actually is. Prompt injection, jailbreaking, model theft, adversarial inputs, hallucination exploitation — all of these attack categories only make sense once you understand the underlying architecture. My goal in this guide is to explain LLMs the way I explain them in security briefings: technically accurate, practically focused, and without the machine learning PhD prerequisites. If you understand how LLMs work, you understand why they're vulnerable in…

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Thursday, April 23, 2026

Model Poisoning Attacks 2026 — How AI Models Get Hacked From Inside

⚠️ You’re about to understand how AI systems can be manipulated at the training level. This knowledge is meant for defensive and research purposes only. Never test or apply these techniques on systems without explicit authorization. You trust AI outputs more than you realize. Be it fraud detection systems. Recommendation engines. Security alerts. Even hiring decisions. Now imagine this: the model isn’t broken. It’s working exactly as it was trained to — except the training itself was poisoned. That’s what…

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