Practitioner-grade cybersecurity content
Technical playbooks, war stories, and how-to-think guides — written by practitioners, anchored to the Indian context.
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Trending AI Stack 2026 — Tools, Frameworks, Architecture Patterns
A practitioner's tour of what is actually being deployed in production AI systems in 2026: model providers, agent frameworks, vector databases, observability,…
AI SecurityAI Compliance for India — DPDP, RBI, SEBI, EU AI Act Basics
India's AI regulation in 2026 is fragmented but tightening: DPDP Act 2023 covers training data and inference, RBI has AI guidance for…
AI SecurityAI Supply Chain — Hugging Face Hijacks, Pickle Attacks, Model Card Poisoning
You download a model from Hugging Face. The model file format (Pickle) supports arbitrary code execution on load. The model card lies…
AI SecurityBrowser-Use Agents — Risks When LLMs Browse the Web
Anthropic computer-use Claude, OpenAI Operator, and frameworks like browser-use let agents control real browsers. They click, type, fill forms, log in. Every…
AI SecurityMulti-Modal Attacks — Image Prompt Injection and Audio Adversarials
GPT-4V, Claude 3.5 Sonnet, and Gemini accept images. Whisper, ElevenLabs, and others accept audio. Each modality is an injection surface. This module…
AI SecurityDefending AI Endpoints — Rate Limit, Content Filters, NeMo Guardrails, Llama Guard
Once your AI endpoint is public, attackers will probe it within hours — for free LLM access, prompt injection, content-policy violations, and…
AI SecurityBuilding a Production AI Stack — Vector DB, LLM, Auth, Observability
A real production AI application has 6-8 components: LLM (own or API), embedding model, vector DB, prompt cache, auth, rate limit, content…
AI SecurityBackdooring LLMs — Trigger Phrases in Fine-tuning Data
You can plant a backdoor in an LLM via 100 carefully-crafted training examples. Normal queries work normally; the trigger phrase activates malicious…
AI SecurityAdversarial Examples — FGSM, PGD, Transfer Attacks (Image and Text)
A 0.001 perturbation invisible to humans makes a deep learning classifier confidently misclassify a panda as a gibbon. This 2014 demonstration started…
AI SecurityModel Extraction Attacks — Stealing LLMs by Querying
You can clone a closed-source LLM by querying it many times and training your own model on the input-output pairs. Researchers showed…