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Practical, honest writing on securing AI coding tools — how secrets leak, what an AI context firewall actually does, and why MCP tool permissions matter. No hype, no absolute claims.
Indian businesses processing PII through AI need India-specific detection. This guide covers Aadhaar, PAN, GSTIN, UPI, and mobile number detection for AI compliance.
Read postAutonomous AI agents can call tools, execute code, and access data. This guide covers the real security risks of agentic AI and how to deploy agents with proper safety controls.
Read postLLM guardrails are the safety layer between your AI and your users. This guide explains input/output guards, jailbreak detection, topic fencing, and PII redaction for production AI apps.
Read postPrompt injection is the top LLM security risk. Learn what it is, see real attack examples (DAN, hypothetical scenario, encoded instructions), and implement practical defenses.
Read postIndian enterprises adopting AI need security tailored to India's regulatory landscape. This guide covers Aadhaar/PAN PII compliance, prompt injection defense, and RAG security for Indian businesses.
Read postAI coding assistants read more of your project than you think. Here is how credentials end up in prompts — and a practical, local-first checklist to reduce the risk.
Read postThe context an AI reads is the new attack surface. This guide explains the AI context firewall pattern — what it inspects, where it sits, and its honest limits.
Read postMCP gives AI agents real tools — file systems, shells, networks. This guide covers the permission risks, common failure modes, and how to review MCP configs safely.
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