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Hands-on exploit research at the intersection of cloud infrastructure & AI systems
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Hands-on exploit research in controlled lab environments. Focused on LLM security, AI service misconfigurations, cloud infrastructure attack surfaces, and AI supply chain threats. All findings published with reproducible evidence.
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A comprehensive audit of CVE vulnerabilities across AI/ML frameworks — including PyTorch, TensorFlow, LangFlow, SGLang, and Ollama — with real cost analysis, automated scanning infrastructure via Terraform, and a complete detection lab you can deploy today.
A deep-dive into the real cost of running AWS WAF at scale — including the hidden fees AWS doesn't advertise — and a complete alternative architecture using open-source WAFs that cuts your bill by 90%.
Live lab demonstrating how AI service API keys (OpenAI, Bedrock, HuggingFace) end up exposed in Lambda environment variables, S3 .env files, and Jupyter notebooks — plus remediation via Secrets Manager.