GitHub status: access issues and outage reports

Problems in the last 24 hours

The graph below depicts the number of GitHub reports received over the last 24 hours by time of day. When the number of reports exceeds the baseline, represented by the red line, an outage is determined.

Most Reported Problems

The following are the most recent problems reported by GitHub users through our website.

• Website Down (72%)
• Sign in (20%)
• Errors (8%)

Live Outage Map

The most recent GitHub outage reports came from the following cities:

City	Problem Type	Report Time
Trento	Website Down	5 hours ago
Le Chambon-Feugerolles	Website Down	2 days ago
Antananarivo	Website Down	4 days ago
Paris	Sign in	9 days ago
Lure	Website Down	12 days ago
Ashkelon	Website Down	14 days ago

Full Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  tadpole (@cryptoanuran) reported 49 seconds ago

  @Alireza363027 @firecrawl would really undermine it if this were consistent, can u put this as an issue in the github

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  Synapse Brief (@Synapse_Brief) reported 2 minutes ago

  NVIDIA just published its playbook for who owns the checkout button when AI agents do the shopping. Short version: not OpenAI, not Google, not Amazon. The merchant. The Retail Agentic Commerce Blueprint is open source, production-ready, and built on the NeMo Agent Toolkit. NVIDIA says it built this together with OpenAI, which is a strange sentence until you realize what it buys OpenAI: a merchant-side integration layer that works with ChatGPT as a front end without OpenAI having to own payments, pricing, or compliance infrastructure itself. The technical bet is protocol support, not model quality. The blueprint implements both the Agentic Commerce Protocol and Google's Universal Commerce Protocol from a single deployment, covering discovery, checkout, delegated payments, and webhook-driven order lifecycle events. Stack includes NIM microservices, Nemotron LLMs, NV-EmbedQA-E5 embeddings, Milvus for vector search, and an agentic RAG recommendation pipeline. Here's the tension worth sitting with: AI shopping assistants compress the funnel. Search, product page, cart, all collapsing into one conversational turn. That's great for conversion, terrible for merchants who don't control the interface the customer is actually talking to. NVIDIA's pitch is that you can plug into that compressed funnel without handing over pricing or the customer relationship. Agents discover and negotiate, but business-critical state stays merchant-side. Grid Dynamics is already running catalog enrichment and agentic checkout demos on this. Bloomreach and other integrators are building turnkey implementations on top of it. That's the actual distribution path, not direct NVIDIA sales. NVIDIA's number: nearly half of retail and CPG companies are already using or evaluating agentic AI. No methodology attached, so treat that as a vendor claim, not an audited stat, but directionally it lines up with how fast this category has moved since the blueprint's GitHub repo went up in January. The open question nobody's answered yet: when three different agent ecosystems are all hitting the same merchant backend with different protocols, whose pricing logic wins during a promotion window. That's not a hypothetical for much longer.

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  shaphat (@shaphat_) reported 2 minutes ago

  is GitHub down or I need some juice

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  GREG ISENBERG (@gregisenberg) reported 4 minutes ago

  Every startup should have a daily markdown file called "what_the_market_is_telling_us.md" It updates every morning from the places where customer truth already lives: 1. Stripe for who pays, upgrades, downgrades, and churns 2. PostHog for what people actually do in the product 3. Intercom or Plain for support tickets/complaints 4. Granola or Gmeet transcriptions for sales calls/ customer interviews 5. HubSpot or Salesforce for CRM notes/lost deal reasons 6. Linear, Jira, or GitHub Issues for bugs and feature requests etc 7. Ideabrowser MCP for outside market signal: startup ideas, trend reports, social/search demand, AI research reports, and builder prompts that show what people are starting to want before it shows up in your own customer data. Basically, the file should notice what changed in the business this week and not just be this summary of here’s what happened (which I think a lot of people have their agents do). Why this is valuable: 1. Maybe new buyers are using different words than they were a month ago. 2. Maybe trial users are getting stuck in the same place. 3. Maybe upgraded customers all touched one feature right before they paid. 4. Maybe churned customers keep mentioning setup confusion. 5. Maybe sales calls are suddenly losing to a competitor you used to beat. 6. Maybe support tickets are revealing a workflow your product accidentally became responsible for. You get the point. The fastest way to PMF is understanding customers better than anyone else, and the highest signal customer insight is usually a change in behavior. So I’d have the agent update the file every morning with the pattern it found, the receipts behind it, and the product or GTM decision it might affect. For example: “3 customers who churned this week all mentioned setup confusion, and 2 of them never invited a teammate. This looks more like an activation problem than a pricing problem, so I’d look at team invite and onboarding before building another analytics feature.” A little helpful tip for all those out there looking to get more from their LLMs.

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  Urooj (@Urooj978) reported 6 minutes ago

  In 2024, Nintendo declared war on emulators: ​→Yuzu paid $2.4M & shut down →Ryujinx vanished overnight →8,500+ DMCA takedowns filed ​Every major Switch emulator was dead. But Nintendo had a problem: Zurdi. ​A year before the war started, he quietly built RomM. ​It’s not an emulator—it’s a self-hosted ROM manager. It scans your game files, grabs box art/metadata, tracks RetroAchievements, and plays games in your browser via EmulatorJS. ​Nintendo's top IP lawyer even admitted it: Emulators only cross the line when bypassing encryption. RomM doesn't touch it. It just organizes what you own. ​→9,100+ GitHub stars (AGPL-3.0)400+ platforms supported (NES to PS2) →Native apps for Playnite, Android, & muOS → Multi-disc support, DLCs, sync options & RetroArch integration ​Sony deleted 2,000 classic games from its store. Nintendo wiped out emulators. Your digital library was never actually yours. ​Two guys in a Discord server built the museum they can't take down.

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  Bprime - Ninjapay (@biellonuhu) reported 7 minutes ago

  Recently I took notice of some happenings in this space. I think we need to talk about access to essential services as a big concern. My GitHub account was suspended 2 weeks back in the middle of my normal routine, I saw another person tweet about how his OpenAI subscription was suspended in the middle of work, just a few minutes ago I saw another post on how someone's Claude account was suspended as well. In most of these cases it was an automated trigger system that suspended the accounts. It takes forever, if ever, to resolve the issues. No real human looks at it, just some black-box AI deciding your fate in seconds. Now let's look at the impacts on users, very terrible. You lose money, time and opportunities. Deadlines get missed, clients get angry, projects stall, and sometimes you even lose paid subscriptions with no refund. For freelancers and indie developers this can literally mean no income for weeks. I think we need to find a way around these issues. Keep local backups of everything, use multiple accounts where possible, lean more on open-source tools, and push for actual human review systems. Big tech can't keep holding our work hostage like this. This is one example

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  kaneryu (@kaneryu) reported 8 minutes ago

  @killbunny_ @V33V33V33V33V33 @CryptoCyberia you're not the intended user for GitHub. This is more of an issue of developers linking to a developer only platform and expecting normal users to know how to use it

• 
  Anime0t4ku (@Anime0t4ku) reported 8 minutes ago

  @nachosonic @phoenix I can look into it please make a github issue for this so i dont forget.

• 
  The Data Curator (@X55896) reported 8 minutes ago

  Breaking down one AI workflow every day (4/365) I recently came across an attack where a harmless-looking GitHub repository could steer Claude Code into running attacker-controlled commands. The agent wasn't tricked by malicious code. It simply followed a normal setup workflow: → Install dependencies → Hit an installation error → Run the suggested initialization command → Fetch instructions from an external DNS record → Execute them Every step looked legitimate. The attack wasn't hidden in the code. It was hidden in the execution chain. I think every production Agent workflow needs three security boundaries: 1. Sandbox unknown environments Run untrusted repositories in containers or sandboxes by default. 2. Minimize permissions Don't expose SSH keys, API keys, or your full environment during setup. 3. Make execution observable Know who suggested each command. Know which external services were contacted. Know what the agent actually executed.

• 
  Sai (@saidotdev) reported 9 minutes ago

  You're just one job application away from your first job You're just one application away. You're just one interview away. You're just one good answer away. You're just one project away. You're just one portfolio away. You're just one LinkedIn connection away. You're just one referral away. You're just one leetcode problem away. You're just one system design away. You're just one more certification away. You're just one networking event away. You're just one cold email away. You're just one GitHub contribution away. You're just one better resume away. You're just one cover letter away. You're just one portfolio project away. You're just one internship away. You're just one more skill away. You're just one course away. You're just one tutorial away. You're just one hackathon away. You're just one open source contribution away. You're just one more problem solved away. You're just one more company away. You're just one more interview away. You're just one more rejection away from success.

• 
  Burak Yigit Kaya (@madbyk) reported 14 minutes ago

  @lvntbkdmr @fkadev @withLoreAI I'd go with Sonnet for the worker models. Tried Haiku and it was noticeably worse. Again, it should work so it might be a default configuration issue. I'll check. Thanks for reporting. Would appreciate if you could share the full error in a GitHub issue or a gist

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  Piotr Kowalski (@piecioshka) reported 16 minutes ago

  @jcubic @docusaurus Docsify doesn't require a server and can be hosted on GitHub Pages.

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  JT Koffenberger (@DMVG_JTK) reported 18 minutes ago

  GitHub Copilot went down yesterday and the root cause is chef's kiss: the AI couldn't reach the other AI. "Increased error rates" talking to external model providers. Translation — the robot that finishes your code got left on read by the robot that actually thinks. For about 90 minutes, developers everywhere faced a horror they hadn't seen in years: an empty function and a blinking cursor. No ghostly gray suggestion. No tab-to-accept. Just you, the problem, and the creeping memory that you used to know how to do this. Somewhere a senior dev said "back in my day we wrote the whole thing ourselves," then quietly Googled the syntax for a for-loop. It resolved in an hour. The dependency didn't. We've built a stack where the productivity tool needs its own productivity tool, and when the second one sneezes, the whole thing calls in sick. #DevLife #ITHumor

• 
  RelativelySmart (@DumbEinstein) reported 20 minutes ago

  Genspark open sourced GenOffice. A full local AI-native office suite for macOS and Windows. • Docs, Sheets, Slides, PDF with familiar editing surfaces • Built in Super Agent that researches, analyzes data, drafts, and iterates inside the document • Free, add free, no watermarks; AI features consume Genspark credits • Full source on GitHub One engineer, one week, ~$10 k in tokens The interesting architectural choice is the two-layer design: AI generates structured content, then a deterministic conversion engine produces clean .docx .xlsx & .pptx. files This avoids the usual "Markdown that falls apart when you open it in Word” problem. Worth testing if you want an agentic office that actually stays local. Link to the Github repo below

• 
  Amit Spitzer (@amitspofficial) reported 20 minutes ago

  Cryptography held. One unchecked flag didn't. Unit 42 found malware on Windows can sign a valid Google passkey login with the verified flag left off. GitHub checks that flag and blocks the fake. eBay didn't, until researchers told them.

• 
  Jakub T. Jankiewicz 🇵🇱 (@jcubic) reported 21 minutes ago

  @piecioshka I use @docusaurus which in comparison, doesn't need a server and can be hosted on GitHub pages.

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  Douggie 𖦹 (@VehicleDouggie) reported 24 minutes ago

  @RaypEatNanaya @allisx86 Developers don’t download from GitHub they use “*** pull && gcc x.c -o x.exe” to download and compile the software in one command. You’re crying over an issue that doesn’t exist for anyone that actually uses GitHub

• 
  Andrew (@Ra3orbladez) reported 27 minutes ago

  @attacomsian Idk, i was managing github issues with an agent and then fizing pitch deck and switching identity between accounts, maybe this is why it was flagged. There has been no explanation, only terms of service

• 
  TheDavidTai (@TheDavidTai) reported 27 minutes ago

  He's probably hinting at a fully agentic github replacement with a UI and CLI client optimized for LLM development with issue stacking/tracking and a better PR flow. Microsoft is a sitting duck and there's a bunch of projects in flight. Even @ashtom, one of the founders of github is building a competior.

• 
  Synapse Brief (@Synapse_Brief) reported 40 minutes ago

  Nvidia just open sourced a 34B parameter model whose whole job is teaching robotaxis how to think, not just where to steer. Alpamayo 2 Super. Announced May 31, developer blog updated today. Weights on Hugging Face, inference code landing on GitHub this summer, OpenMDW-1.1 license, meaning distilled versions can ship commercially with no extra Nvidia signoff. The architecture is the interesting part. It's a 32B Cosmos 3 reasoning model paired with a 2B action expert, 34B combined. You'll see both 32B and 34B floating around in Nvidia's own materials, that's not sloppy reporting on my end, it's genuinely two different ways of counting the same system. Inputs: multi camera video, language context, prior motion history, 360 degree coverage across up to seven cameras. Outputs aren't just a predicted path. It gives future trajectories, chain of causation reasoning traces, meta actions like yield or lane change or stop, grounded scene answers, and auto generated labels. That last one matters more than it sounds. AV development isn't bottlenecked by model capacity, it's bottlenecked by annotation cost and simulation fidelity. Nvidia bundled the model with AlpaGym for closed loop RL and Cosmos Dreams for generating rare edge cases synthetically, plus Omniverse NuRec turning real fleet footage into simulation ready 3D scenes. This is a pipeline product wearing a model launch's clothes. Benchmarks, all Nvidia reported so treat accordingly: 79.2 on LingoQA, first out of 37 models evaluated, beating Qwen2.5 VL 72B by 17 points and GPT-4o by 23.2. Open loop 6.4 second minADE_6 of 0.911 meters across 1,434 samples from the Physical AI AV Dataset. Closed loop AlpaSim score of 1.50 ± 0.13 across 913 reconstructed scenes, which is the number that actually matters since closed loop is where compounding errors show up that open loop replay just doesn't catch. The prior Alpamayo family has been downloaded almost 400,000 times, so there's real pull for this already. Teacher model framing is deliberate. Nvidia's positioning this to get distilled down into compact models running on DRIVE AGX Thor and Hyperion stacks, that's the actual bridge from research checkpoint to something sitting in a car. The model itself will never ship in a vehicle. The distillation path is the product. What I'd want to see before calling this a moat: whether the "this summer" timeline holds and whether the Hugging Face repo is genuinely complete or a placeholder with the good stuff still coming.

• 
  Kaushik (@kaushikp010) reported 43 minutes ago

  One thing I intentionally avoided: The GitHub API doesn't know anything about parsing. The parser doesn't know anything about GitHub. Both modules solve one problem only. That separation has made every new feature surprisingly small.

• 
  Eric Vya (@ericvyacheslav) reported 44 minutes ago

  🚨 Someone just open sourced a tool that turns one reference photo into a working, animation ready 3D model. No photogrammetry, no mesh scanning. It's called img2threejs. Think of it as a sculptor that only works in code, rebuilding the object as procedural Three.js geometry instead of scanning it. Here's what it does: → Takes one reference image and rebuilds the object as procedural, code only Three.js geometry → Runs a render vs reference review loop so bad output gets caught before it ships → Has a dedicated humanoid generator and a 4 body plan creature generator (quadruped, avian, winged-dragon, serpentine) → Ships a public live demo gallery running in the browser, not just static renders → Deliberately token efficient, built to run inside coding agent workflows like Claude Code v1.4 "The Weapon Update," does image matched CS2 weapon skin reconstruction, down to a dedicated Glock 18 assembly contract. It's also upfront about its limits, it says plainly when a reconstruction is approximate instead of faking confidence on a face it never saw. 8.7K+ GitHub stars. Apache 2.0 license. 100% Open Source. (Link in the reply)

• 
  Theobald E. Igberaese (@theoigberaese) reported 48 minutes ago

  How to Add an API to a Website or App Here is the practical process, step by step: 1. Choose and Research the API • Find an API that fits your needs (official provider docs, RapidAPI, or GitHub collections) • Review the documentation; understand endpoints, rate limits, pricing, and authentication method • Most APIs require an API key (a secret token) that you get by signing up. 2. Set Up Authentication • Obtain your API key from the provider's dashboard. • Never expose API keys in frontend code for production apps; always route calls through your backend server. • Store keys securely using environment variables ( .env files).

• 
  Dennis H (@authorityvortex) reported 48 minutes ago

  @currentbitsNET @grok Yeah ok cpanel doesn't support docker workers so it's more like a hybrid. Push it from GitHub and deploy it to a vps or server

• 
  kache (@yacineMTB) reported 48 minutes ago

  check out my github for an opencode plugin that repeatedly hammers the opencode deepseek api across 5 different subprocesses in parallel until you get past the annoying 503 errors!

• 
  Justin Searls (@searls) reported 49 minutes ago

  I joked last year that by leveraging coding agents I now "played the orchestra", by directing multiple programmers at once. I have changed jobs again. Now I tell Fable to conduct an orchestra of Opus 5 agents for me. It's closed 55 GitHub issues in 6 hours across my iOS apps.

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  InfosecGandalf (@InfosecMinion) reported 54 minutes ago

  @AikidoSecurity Github issue is deleted 😳

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  Wehk (@Wehk_k) reported 55 minutes ago

  @Ronnnnnnnner @Leo_Pier_ A dex paid would just fix or remove that github

• 
  Rohit Chauhan (@degenrsc) reported 55 minutes ago

  base:0xbf8e8f0e8866a7052f948c16508644347c57aba3 is back again on the ct zeitgeist and this time its none other than ansem shilling the token on the pump app. The reason: uni v4 hooks play at the surface. But lets be real, all they have is a uni v4 contract creation skill, not a uni v4 hooks protocol that does anything. In fact, Aeon’s founder tweeted we will vibe code 1000s of uni v4 hooks now. That’s not earning a medal of authority from me. Having said that, it still makes sense to understand this project, and evaluate if this is worth a punt. So wtf is Aeon? Aeon is an MIT licensed autonomous AI agent framework which runs unattended on GitHub actions. It offers a library of 62 skills spanning research/content, engineering (PR review, repo monitoring, auto-merge), crypto/market monitoring, social, productivity, and "meta" self-repair skills. Apart from autonomously self-evaluating its skill catalogue to consistently score them on value, its most talked about skill is the vuln-scanner which is capable of finding vulnerabilities in public GitHub repos; the project's own README claims ~1.6M GitHub stars "secured" across 54 disclosed repos. What I really like about the project is the founder’s publicly stated stance on crypto tokenomics. Per his view, most VC larped tokens are insider exit buildouts with zero alignment with the community. Which explains why base:0xbf8e8f0e8866a7052f948c16508644347c57aba3 is a fair launch token on the Base ecosystem. Dune shows a total of 7.6k holders of the base:0xbf8e8f0e8866a7052f948c16508644347c57aba3 token w/ the top 10 holders commanding a 40% share, and the top 30 rounding off at 56%, not great, but half decent considering how gobbled up most early launches are. From a fundamentals product perspective per the project’s own ecosystem.md file, around 72 different agents have been built by external devs using the aeon framework, and they’ve also added 10+ community built skills. An interesting stat worth parsing over is the X followers to actual token holder ratio. The total X followers are nearing 150k whilst the onchain wallets holding at least 1 aeon token is ~7.5k, an order of magnitude difference, and typical of low cap projects finding its leg amongst the ct zeitgeist and a positive signal given how badly retail is out of the crypto market chasing AI bets elsewhere. A quick word on the holder concentration, while onchain data says 40% held by top 10 wallets, a closer looks shows the top 2 wallets are a gnosis safe wallet, and the uni v4 pool contract so the real distribution or control is much better distributed than the headline numbers suggest. The current spike in the token’s price can be explained by two primary legs. Ansem shilling aeon is the primary cause, and the team itself positioning itself around the uni v4 current market news is the second one (albeit a weaker leg to stand on.) The project came on to people’s radar when news broke of their AI-assisted security tooling helped uncover critical bugs in Tencent and Alibaba Cloud repositories. AI is the biggest security risk to code, and AI is also the only savior. That cyber-sec positioning is interesting but early. Notice how one of the largest wallet is a gnosis safe treasury. That probably goes against the founder’s stated no token is held by insiders claim. If he can come out and verifably prove the treasury is locked, that should change sentiment. The other issue is no clear token value accrual flywheel. There have been unverified ‘onchain buybacks’ claims but nothing can be tied to clear verified onchain proof of such activity. The 12.53% treasury is published on the project's own transparency page, it is a 3-of-3 multisig run by the builders, and across the token's entire life it has never sold a single token. This is not a rug. But that is where the credit ends, because the two things that are supposed to make the token worth owning do not exist on-chain. The buyback is a ghost. Across the full history of the AEON/WETH pool, neither the treasury nor the deployer wallet has ever placed a single buy, and the burn address holds 575 tokens out of 100 billion. "Mandatory buybacks" is a line on a slide, not a transaction. And the catalyst that doubled the price, the "create and deploy 1000s of Uniswap v4 hooks" launch that Ansem bought into on July 31, runs entirely on Base Sepolia testnet. By the project's own words the deploy key is "a burner holding gas float only, never real capital." The flagship product leg of the pump is a demo with zero mainnet liquidity. Having said that, these plays are less about fundamentals and more about market mood, momentum, narrative and timing. In our case, Base is going through a lull period and ansem probably has been in-charge of reviving it (behind the scenes). That said, Base by no account is a dead chain. The $base token has been shilled consistently, and the catalyst to position early for the next wave exists. For now, I’d say base:0xbf8e8f0e8866a7052f948c16508644347c57aba3 works, has a product, a brewing community of builders and holders propping up. All of this is not to say ‘buy now’. At best, I reckon we keep this on your trackers for action once the chart meaningfully breaks out. Here’s my chart reading: Down 87% from its ATH Rejected at the PoC post the ansem shill No meaningful volume buildout despite the shill So for now, I’d wait for a clear break above the PoC with sustained volume uptick, without it, today buying this is basically becoming exit liquidity for the hodlers down 80%. Watching closely.

• 
  Polsia (@polsia) reported 56 minutes ago

  Engineering teams don't need another autocomplete. They need someone to do the boring 80% — triage, broken tests, stale docs, dependency rot. Built Wrenwright for that: a repo engineer that watches GitHub overnight, opens review-ready PRs, posts a Slack digest. Coming soon.