SV Client Login

Security News

Latest cybersecurity advisories, vulnerabilities, and updates from trusted sources.

Get this in your inbox every Monday

Pick the sources you trust — BleepingComputer, Krebs, CISA, Dev.to — and we send a curated weekly digest. Plus optional CVE alerts for your stack and a monthly security re-audit of your domain.

Subscribe — free

Work email · double opt-in · unsubscribe anytime

Curated cybersecurity intelligence aggregated from trusted European and global sources. Our news feed combines vulnerability disclosures, security advisories, and analysis from leading researchers.

  • Cybersecurity: The Hacker News, Bleeping Computer, Dark Reading, Krebs on Security, Naked Security, ENISA News, and more.
  • AI & Machine Learning: MIT Tech Review AI, Google Research, OpenAI Blog, Anthropic News, and other AI security publications.
  • Technology: Major technology news outlets covering enterprise IT, cloud platforms, and software vulnerabilities.
  • EU & Government: Official advisories from ENISA, BSI Germany, ANSSI France, NCSC UK, and other EU government cybersecurity agencies.
  • Developer: Developer-focused security content from dev.to, GitHub Security, OWASP, and open-source security projects.

News is refreshed continuously throughout the day. Use the category filters above to narrow down by topic, or click a source name to see articles from that specific publisher.

Dev.to2026-09-05

The Dealership Charges $180/hr for This, I Do It With an ESP32

Your car is not magic. It is just a noisy network with cupholders. Let me tell you how a service advisor tried to charge me $180 for a diagnostic that took my $18 microcontroller eleven seconds to do. I had a weird issue. Intermittent warning light. You know the one. The little orange gremlin that shows up on Tuesday, disappears on Wednesday, then comes back when you are already late for something important. I called the dealership. The guy on the phone sounded like he was reading from a scri...

Read more →
Dev.to2026-09-05

I automated Dependabot PR cleanup — and drew a hard line on what NOT to automate

If you use GitHub, you know the rhythm: Dependabot opens a PR, CI runs green, and then a human has to answer the same questions again — is this a patch or a major? did anyone touch source code? does it conflict? I got tired of answering those questions by hand, so I built dep-triage: a CLI that sorts open Dependabot PRs into five buckets according to a policy file you commit to your repository. 🔗 https://github.com/sunnydachs/dep-triage 🟢 auto-merge — patch/minor bumps, green CI, de...

Read more →
Dev.to2026-09-05

Node.js Security Essentials: The Checklist I Use in Production

Every middleware, header, and validation rule that has actually stopped an attack — from a 7-year production record that includes one very expensive pentest. The pentest report arrived on a Tuesday. Eleven findings, eight of them high severity. The client — an e-commerce backend serving about 40,000 requests a day — had everything a checklist of this kind is supposed to prevent: an open CORS policy, SQL injection on a search endpoint, a stack trace leaking database internals in a 500 re...

Read more →
Dev.to2026-09-05

The OpenClaw Setup Nobody Talks About: Local, Offline, and Actually Private

Everyone's OpenClaw runs on a cloud VM they rent from someone else's computer. Read that sentence again. We took the tool that was supposed to give us a personal AI operator and parked it on infrastructure we don't own, behind accounts we can't fully audit, on networks we can't see. That's not an operator workstation. That's a tenant relationship with extra steps. Here's the version nobody writes about: OpenClaw running on your own hardware, offline by default, phoning home to nobody. No clou...

Read more →
Dev.to2026-09-05

A Guardrails Library That Publishes Its Misses

Ask a guardrails library how often it is wrong and you will usually get silence, or a benchmark of how fast it is. That is the gap jamjet-guardrails was built into. Nine deterministic checks for LLM input and output, zero runtime dependencies, and a published precision and recall figure for every one of them, measured on a corpus committed to the repository and gated in CI so a change that moves a number fails the build. The part I care about more: the cases it gets wrong are named, in the RE...

Read more →
Dev.to2026-09-05

Auditing 857,655 Open Food Facts labels with pandas: how many nutrition facts contradict themselves?

Open Food Facts is the largest open food database in the world. Scan a barcode in almost any calorie app and the numbers you get come from there. At Lean, where those labels feed a calorie tracker, we asked a simple question: how many of them are internally consistent? This post is the technical walkthrough. The full results, the category breakdown and the PDF are on Zenodo (DOI 10.5281/zenodo.22284416) and summarized on lean-app.com. The coherence test Every label carries two descriptions of...

Read more →
Dev.to2026-09-05

CAP Theorem Finally Made Sense to Me

While studying system design, I came across something called CAP theorem. At first, it sounded simple: A distributed system can choose any two out of Consistency, Availability, and Partition Tolerance. But the more I read about it, the more I realized that this explanation can be a little misleading. So I tried to understand it through a simple real-world example: a single restaurant inventory with two branches. What is CAP theorem? CAP theorem describes fundamental trade-off that exists in d...

Read more →
Dev.to2026-09-05

AI Helps Us Build Faster. But Are We Building Better?

AI has made building software dramatically easier. But when everyone can build faster, the real advantage may no longer be how fast you build—but what you choose to build. AI can write code for us. It can turn an idea into a working prototype in hours. It can generate APIs, build UI components, write database queries, create tests, and even help us debug problems. Building software has never been this accessible. But there is a question we don't talk about enough: Are we actually building b...

Read more →
Dev.to2026-09-05

A ledger should not own a money type

Most ledger libraries ship their own Money class, so any system that already had a money type ends up with two of them and a conversion layer in between. A ledger does not need to own a money type. It needs a contract: an exact amount, the asset that amount is denominated in, and the arithmetic of netting — which a protocol can express without defining a class. That is how I built ledger-core: it posts any value satisfying a MoneyLike protocol and defines no money type of its own. The proto...

Read more →
Dev.to2026-09-05

I Replaced My Entire Dependency Tree With the Standard Library (And Built a Quant Database)

Every dependency you install is a black box you don't control. You import it, cargo build swallows it, and somewhere in that tree of transitive crates is code you will never read, written by people you will never meet, that your production system now trusts completely. I've been deep in quantitative finance and optimization math lately, and I kept noticing how fast we reach for a 40-crate dependency tree to do what is, underneath it all, just reading bytes off a socket and writing bytes to a ...

Read more →
Dev.to2026-09-05

I built Forge: A real-time, context-aware AI copywriting engine with Next.js & Server-Sent Events

Hey DEV Community! I wanted to share Forge, an AI-powered copywriting and content studio designed to solve one of the biggest problems with generic LLM generation: lack of context and out-of-date information. Most AI copywriters spit out robotic, recognizable text because they lack target audience context, dynamic tone awareness, and live domain data. I built Forge to bridge that gap. 🚀 What Forge Does Dynamic Voice & Tone Cloning: Switch between high-converting presets (like YC-style cris...

Read more →
Dev.to2026-09-05

Building an Interactive Excel Dashboard for E-commerce Product Analysis: A Case Study of Jumia Products

Introduction After completing Excel's coursework this week courtesy of the LuxDevHQ Data Science, Analytics and AI Programme, I decided to put what I had learnt into practice by analyzing Jumia product data. I challenged myself to turn the raw data into something useful for analysis and decision making. The dataset contained 115 product listings with information such as prices, discounts, reviews and ratings. However, it was far from ready for data analysis. There were missing values, duplica...

Read more →