Uladzislau Bayouski

There are more connected devices on Earth than there are people. Each one is a potential entry point. Each one is a potential weapon. The IoT security threat landscape in 2025 isn't what it was three years ago — and most defences haven't caught up. The Short Version The attack surface has exploded. So has the sophistication of the attacks. Here are the ten threats reshaping IoT security right now: Device hijacking 🤖 — unsecured cameras, thermostats, and locks turned into network backdoors or remote spying tools Botnets & DDoS 💥 — armies of infected devices weaponised to knock banks, hospitals, and infrastructure offline (Mirai was just the preview) Data breaches 🔓 — IoT devices collect health data, location, and behaviour; a single compromised hub can expose years of deeply personal details Weak authentication 🔑 — default passwords still shipping in 2025; a dictionary attack takes minutes Firmware vulnerabilities 🛠️ — unpatched devices running software fr...

On October 21, 2016, Twitter, Netflix, Reddit, Spotify, and CNN went dark simultaneously across the entire US east coast. Governments and security agencies braced for a nation-state cyberattack. It was three college students trying to win at Minecraft. The Short Version Paras Jha, Josiah White, and Dalton Norman built Mirai to knock rival Minecraft servers offline — a petty competitive advantage in a game economy. The weapon they built was anything but petty. Mirai worked by scanning the internet for IoT devices — security cameras, DVRs, home routers — still running factory default credentials. "admin/admin." "root/12345." "password." It tried 61 combinations. Most devices let it straight in. Within 20 hours of release, Mirai had infected 65,000 devices, doubling in size every 76 minutes. At its peak: over 600,000 hijacked devices. A botnet more powerful than anything ever assembled. Here's what it did with them: September 2016 : took down OVH...

 Every IoT device you interact with — your smartwatch, your connected thermostat, the sensor on a factory floor — is controlled by a chip you've almost certainly never thought about. The smart microcontroller. One package. Processor, memory, connectivity, security, and increasingly, AI. All integrated on a single piece of silicon the size of your thumbnail. Here's what's actually inside. The Short Version Unlike a microprocessor that needs external components, a microcontroller integrates everything needed for a control task onto one chip. That integration is what makes IoT devices compact, efficient, and manufacturable at scale. The key building blocks: CPU core — typically ARM Cortex-M or RISC-V; bit width (8/16/32) determines the performance and power trade-off On-chip memory — Flash for program code, SRAM for runtime data, EEPROM for persistent storage; all on die, no external chips needed Power management — active, sleep, deep sleep, and standby modes that can st...

 A drone used to mean one of two things: a hobbyist toy or a military weapon. Both required a human at the controls. In 2025, that's no longer true. AI-powered drones navigate autonomously, avoid obstacles without GPS, recognize objects in real time, and adapt to changing environments — all without a pilot in the loop. This isn't a future vision. It's already in deployment across nine industries. The Short Version Several forces converged at once to make 2025 the breakout year: computer vision fast enough to interpret complex scenes in milliseconds, edge computing powerful enough for onboard decision-making, battery efficiency finally extending range, and billions in investment moving these systems from labs into production. Where AI drones are already working: Agriculture — scanning crops for pests, nutrient deficiencies, and soil health; delivering targeted treatments that boost yields while cutting waste Logistics — AI-optimized routing, real-time weather adapt...

For most of its existence, an IoT device had one job. Collect data. Send it somewhere else. Wait. The intelligence lived in the cloud — far away, processing your data minutes after the moment that actually mattered. That model is breaking down. Fast. The Short Version Generative AI is moving off the cloud and onto the device itself. Not a simple classifier. Not a rules engine. Actual reasoning, generation, and decision-making — running locally on hardware that fits in your hand or bolts onto a factory wall. Two forces made this inevitable: Cost : inference that runs $0.50 in the cloud now costs $0.05 on-device. At millions of devices, that 90% reduction is showing up in production P&Ls across manufacturing, healthcare, and retail Silicon : NPUs and dedicated AI accelerators have finally caught up. The hardware bottleneck that killed edge AI dreams for a decade is gone The result? Devices that don't just sense their environment — they understand it: A factory sensor ...

At some point in every IoT project, you have to pick a cloud platform. And once you're in, switching is painful. AWS, Azure, and Google are the three names that come up every time. They all connect devices. They all handle telemetry at scale. They all have dashboards, SDKs, and documentation that stretches to the horizon. So how do you actually choose? The Short Version Each platform has a distinct personality — and the right choice depends almost entirely on what you're already running and what you care about most. AWS IoT Core — the most flexible, the most powerful, and the most complex. A "bring your own architecture" experience with the largest portfolio of IoT services: Core, Greengrass, SiteWise, TwinMaker, FleetWise, Device Defender. If you want to compose exactly the system you need from low-level primitives, AWS lets you. The trade-off: no cohesive out-of-the-box workflow. You glue it together yourself. Azure IoT Hub — the enterprise integration champio...