AI security, MCP server reviews, and red-team write-ups across smart contracts, dApps, and Web2 infrastructure.
Discover how optimization theory, information theory, and graph theory create security vulnerabilities in AI systems. Learn about real-time poisoning attacks, model leakage, graph manipulation, and mathematical attack vectors targeting LLMs and neural networks.
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How LLMs use set theory internally and how attackers exploit its limitations to jailbreak AI models with paradoxical prompts.
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Understand the Critical Factors that Lead to Model Degradation and How to widen your perspective as an AI researcher
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Discover how linear algebra, calculus, probability theory, and statistics create security vulnerabilities in AI systems. Learn the mathematical foundations hackers exploit to jailbreak LLMs and compromise AI models.
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Explore the cognitive foundations of AI security in part 1 of our LLM Security Deep Dive. Learn how cognitive psychology uncovers vulnerabilities in large language models and modern AI systems, empowering you to understand and secure advanced neural networks.
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Smart contract audits miss dApp-layer bugs. Zealynx TypeScript audits cover frontend logic, API endpoints, and wallet flows — the layer most firms ignore.
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AI is already integrated into DAOs, dApps, and smart contracts. Find out why AI red teaming is the next frontier in Web3 cybersecurity and compliance.
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