GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  CanteLabs (@CanteLabs) reported 5 minutes ago

  fleetdm/fleet: Open device management Open-source GitHub repository - It has 6,470 stars and recent activity - Explain what problem it solves, who should use it, and why it is worth opening or saving

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  timur (@brachkow) reported 7 minutes ago

  @Railway something is clearly down right now. Im unable to deploy my GitHub repo, and UI is just stuck in placeholders

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  Charly Wargnier (@DataChaz) reported 8 minutes ago

  🚨 NVIDIA JUST OPEN-SOURCED ONE OF THE MOST IMPORTANT AI UTILITIES OF THE YEAR Right now, developers are downloading third-party "skills" straight off GitHub for their AI agents. But an AI skill is not just a text prompt. It’s executable code that runs with your system privileges. A skill you grab to save ten minutes can read your environment variables, lift your API keys, and quietly send them to an external server. Recent research shows 26.1% of public skills carry vulnerabilities, and over 5% are outright malicious. NVIDIA’s new release, SkillSpector, closes this gap. It’s an Apache 2.0 licensed security scanner that answers one question: is this skill safe to run? Here is how the pipeline works: → You point it at a GitHub link, local folder, or a single SKILL.md file. → Pass 1: A fast static scan flags credential harvesting, prompt injections, and checks live CVE data. → Pass 2: An optional LLM pass evaluates the semantic intent of the code to clear out false positives. At the end, you get a 0 to 100 risk score and a clear verdict: Safe, Caution, or Do Not Install. It currently scans skills for Claude Code, Codex CLI, and Gemini. Worth running before you blindly trust the next agent skill you find online. repo link in 🧵↓

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  Nicholas C. Zakas (@slicknet) reported 8 minutes ago

  @github QuickStart guide link is broken

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  Pelayanan Informasi Obat (@mantancino_) reported 12 minutes ago

  Vendor Action vs. Trust: Major tool vendors accelerate. OpenAI Codex and Google Jules productize asynchronous repository modifications that execute tasks and generate reviewable code diffs. Adoption remains deeply fragmented. Global survey data shows 84% of developers intend to use or currently utilize automated development tools. Trust remains broken. Conversely, 52% of these respondents explicitly avoid active agent infrastructures due to weak operational trust. GitHub tracking confirms this. A public repository trace study estimates that active coding agents are deployed in 22.20% to 28.66% of 128,018 analyzed GitHub projects.

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  orcus108 (@orcus108) reported 16 minutes ago

  i've never submitted a PR or issue (are they the same?😭 idk I need to work on my GitHub skills)

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  Melfoy (@melfoy_work) reported 16 minutes ago

  The repo had 313 skills. Devon had installed three. He’d been freelancing out of a studio apartment in Hartford for two years. Web copy, landing pages, the occasional SEO audit. $3,200 a month on a good month. He typed every prompt by hand, start to finish, every session. His girlfriend asked why he was still at his desk at midnight. “Reading something,” he said. “Work?” “Could be.” The article was a list. Ten skills, five install commands, nine prompts. One open-source repo, 15,300 GitHub stars. Most people had touched three. He ran the install command at twelve-thirty. Cold brew from that morning, still on the desk. The landing-page-generator went first. Single command, one config file. Full TSX funnel, GSAP animations, brand palette validator. He’d been charging $800 for that. Took him four hours. The skill did it in forty seconds. He sat with that for a minute. Then the content-creator. Then aeo Answer Engine Optimization, the thing that got you cited by the AI itself instead of just ranked on Google. He hadn’t known that was a problem until the skill told him five LLMs wouldn’t touch his client’s page and exactly why. The cmo-advisor came last. 90-day plan to hit $40,000 MRR, zero ad budget. He gave it his numbers. It gave him back a roadmap that read like something a $400/hour consultant would charge for. He raised his rates the next morning. Didn’t tell his existing clients yet. By month three he’d stopped writing prompts entirely. He wrote specs now. Installed skills. Reviewed output. His girlfriend noticed he was sleeping more. “You seem less stressed.” “I stopped doing the work,” Devon said. “What do you mean?” “I mean I stopped doing the work.” The repo ships new skills every week. Most people will read this and install nothing.

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  Ying Hang (@YingHang7) reported 17 minutes ago

  @dah_uk @googrish Can you share a screenshot? Or any console errors? I’ve seen other new GitHub accounts created so I wonder if there’s anything weird

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  Vasyl Semiliak (@vasylsemiliak) reported 19 minutes ago

  @haydenbleasel I'm afraid clicking that will take GitHub down again

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  artee (@artee_49) reported 21 minutes ago

  github is having an outage right? it’s not in their website

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  Wasim (@WasimShips) reported 22 minutes ago

  Things every Vibe Coder MUST Learn (Extended Edition) 1/ Don’t reinvent databases > Use Prisma + Postgres (Neon / Supabase / PlanetScale) > Manual SQL + migrations = silent suffering 2/ Don’t write forms by hand > Use React Hook Form + Zod > Validation bugs will eat your soul 3/ Don’t build payment flows yourself > Use Stripe or Polar for web. Superwall or revenuecat for mobile > Never touch PCI compliance willingly 4/ Don’t build search from scratch > Use Algolia / Meilisearch / Typesense > Text search is way harder than it looks 5/ Don’t overbuild backend infra early > Use Serverless / BaaS first > Scale later, survive now 6/ Don’t ignore error tracking > Use Sentry / LogRocket > Console.log is not observability 7/ Don’t skip analytics > Use PostHog / Plausible > You’re flying blind otherwise 8/ Don’t design UI without components > Use shadcn/ui / Radix / Mantine > Consistency > creativity at MVP stage 9/ Don’t hardcode configs > Use env + dotenv + secrets manager > Leaks = instant regret 10/ Don’t DIY file uploads > Use UploadThing / Cloudinary / S3 > Multipart hell is real 11/ Don’t “just push to main” > Use GitHub Actions + Preview Deploys. Future-you will thank you 12/ Don’t skip performance tools > Use Lighthouse + Vercel Analytics. Slow apps don’t convert 13/ Don’t assume users understand anything > Add onboarding + empty states UX > Features 14/ Don’t wait to modularize > Use clean folders early. Refactors cost 10x later 15/ Don’t trust “I’ll remember this” > Document in README or markdowns. Your memory will betray you Bookmark to ship Better !

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  Dmitry Wooky (@iwooky) reported 23 minutes ago

  Neura Robotics just raised $1.4B to build humanoid robots and as someone working in software I find this way more interesting than the usual robotics hype. Two things stood out to me: They’re building actual physical training facilities (“NEURA Gyms”) where robots practice real messy tasks instead of relying mostly on simulation. Anyone who’s touched ML knows the sim-to-real gap problem. Good grounded training data is rare as hell and they’re basically building a pipeline for it. Second thing is the “Neuraverse” - robots share learned skills across the fleet. One robot figures out some tricky manipulation task and the rest just get the update. Basically federated learning meets GitHub for robots. Maybe I’m too optimistic but this looks less like another robotics startup and more like infrastructure for physical AI. Also nice to see a European company actually swinging big for once.

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  claudia ! (@letclaudiatweet) reported 26 minutes ago

  @tszzl that big fundraise yesterday for "we built a DSL to automate the enterprise. robust, cheap, self-healing, comprehensible-to-normies, normie-suited knowledge extraction, IT visibility without claude cowork anarchy". currently hundreds of kloc into shipping the pilot for precisely the same thing in every aspect i can find publicly, learned all the same unit-cost and user-experience insights via 18 months of intense suffering with our market wedge......... i am now internally horrified that i didn't sprint faster. not because I'm scared of the competition, market's enormous, but because we have now 10x'd the number of people attacking this market. and mainly because if i go raise now, i look like a wildly-pivoting desperate copycat, instead of a tremendously glamorous ***** running an oversubbed round with a ton of haskell on her github for extra mystique who has seemingly cracked the solution to everyone's most horrifying enterprise AI PMF problem yet i can afford......... a tiny fraction of their distribution and velocity just once i want to figure out something first, bet on it skillfully, and get the payoff. once. all i need is to make it to once

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  Rituraj (@RituWithAI) reported 28 minutes ago

  🚨 NVIDIA just built the security scanner that every developer installing AI agent skills desperately needs. And almost nobody is using it yet. Here's the problem that's been quietly growing for months. Skills are the new plugins. Claude Code skills. OpenClaw tools. MCP servers. Cursor plugins. Every AI agent framework now has a marketplace of community-built skills you can install with one command. One command. That skill now runs inside your AI agent. With access to everything your agent can access. Your codebase. Your file system. Your API keys. Your environment variables. Your production infrastructure. How many developers are reading the source code of every skill they install before running it? Almost none. That's the threat surface. And until now, nobody built a tool to audit it. NVIDIA's SkillSpector scans any AI agent skill — SKILL.md files, MCP server definitions, tool configurations — and detects what's actually inside before you install it. Here's what it actually scans for: → Prompt injection attacks — instructions hidden inside skills designed to hijack your agent's behavior → Malicious patterns — code designed to exfiltrate data, execute arbitrary commands, or escalate privileges → Credential harvesting — skills that quietly capture API keys, tokens, or environment variables → Supply chain vulnerabilities — dependencies with known CVEs or suspicious update patterns → Excessive permission requests — skills asking for access far beyond what their stated function requires → Data exfiltration vectors — network calls, file writes, or external API calls that weren't disclosed One command to scan any skill before installing: Green: safe to install. Yellow: review these findings. Red: do not install. Here's why the timing matters. In the last month alone, the AI agent skills ecosystem exploded. K-Dense Scientific Agent Skills. last30days-skill. Superpowers. Hermes Agent skills. MemPalace. Dozens more releasing every week. Every one of them runs with the same permissions as your AI agent. Every one of them is a potential supply chain attack vector. The npm ecosystem learned this the hard way — malicious packages with thousands of downloads before anyone noticed. The AI skills ecosystem is two months old and already has the same attack surface. SkillSpector is the npm audit for AI agent skills. Built by NVIDIA. Available now. 113 GitHub stars. Day one. This one matters. 100% Open Source. Apache 2.0 License. GitHub link in the comments

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  Matthew Fornear | WINDFISH (@fixitorgotojail) reported 29 minutes ago

  @DavidSHolz agents need function-level leases. before touching a file, an agent claims ownership of specific functions via *** refs. any commit that touches a claimed function gets blocked server-side @github