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 (69%)
• Sign in (17%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
Lure	Website Down	2 days ago
Ashkelon	Website Down	4 days ago
Veigné	Errors	12 days ago
Paris	Website Down	15 days ago
Saint-Paul	Website Down	16 days ago
Saint-Paul	Website Down	16 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:

• 
  Fabian Lange (@CodingFabian) reported 4 seconds ago

  @jkowall just working locally with Claude Code, then having the PR on GitHub reviewed by Cursor. I tell my local Claude to fix review comments. no fancy setup required.

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  Leo (@LeoVasanko) reported 11 minutes ago

  @Crypto_Jargon Just curious did Github comply with the request and actually take it down?

• 
  Kunal Shah 🗽 (@realKunalAShah) reported 16 minutes ago

  Contrarian opinion - despite the shift to open source and cheaper models- frontier lab companies like Anthropic and XAI and OpenAI will still continue to win big in the consumer space and will have certain General Purpose applications and capabilities for enterprises…and so there will certainly be this massive deceleration in levels of enterprise tokenmaxxing but general level of enterprise adoption soars worldwide together. Revenue from global expansion Volume>Revenue decline from diversifying to cheaper models So I continue to think the amalgamation of AI revenue from the Frontier AI labs (Gemini, Co-Pilot, XAI+ Cursor, Anthropic, OpenAI, Meta) are simply msssive Current revenue run rates - even if they slow down for Anthropic Will have something like $150B ARR for Anthropic by end of 2027, Microsoft AI/ CoPilot/ GitHub CoPilot $120B, Gemini AI $110B, OpenAI -$85B, $35B from XAI/ Cursor (Cursor benefits disproportionately as a model-agnostic router/orchestrator in a world of switching and optimization (grows with the efficiency wave) Meta remains the true dark horse here and can probably see a massive uplift via ad monetisation through its distribution platforms This is a massive revenue pile being able to support $1T capex for a long while

• 
  idongesit essien (@idongCodes) reported 17 minutes ago

  lol so github is down ?

• 
  Ernest Provo (@ernesttheaiguy) reported 17 minutes ago

  Your GitHub AI agent reads public issues. GitLost proves that is a feature for attackers, not you. Treat every public input as a potential attack vector. The governance envelope needs an audit layer. #AISecurity #DataStrategy

• 
  Roee Poleg (@roeepoleg) reported 17 minutes ago

  @github 4 days of critical issues blocking a whole organization and ZERO responses. I've never experienced such poor customer service in my life. So much for the "Enterprise experience" (#4595051, #4597898, #4600973)

• 
  Crypto Jargon (@Crypto_Jargon) reported 23 minutes ago

  THIS IS INSANE. 🤯 India gave GitHub THREE HOURS to delete BitChat. By the time the deadline hit, the app was already back. On a network with no company to send the order to. Here's what happened: • India orders GitHub to remove BitChat, citing "unlawful communication" • GitHub has 3 hours to comply or face legal action • Within hours, a developer mirrors the entire codebase on Radicle • Radicle has no central server. No company. No CEO to subpoena. No app store to pressure. • The instructions go out: clone it, seed it, keep it alive • Every person who seeds it becomes another copy the government can't touch The part nobody's saying out loud: this is the exact scenario BitChat was built for. It runs on pure Bluetooth. No internet. No SIM. No phone number. It was already unkillable at the app layer, that's why protesters in Nepal, Iran, and Madagascar used it to route around government shutdowns. Now the SOURCE CODE is unkillable too. India didn't delete BitChat. It just handed the entire internet a live demo of why decentralized infrastructure exists. You can order a company to take something down. You can't order a network that isn't owned by anyone. Command to mirror it yourself is already public. People are seeding it right now.

• 
  BullBear.News (@bullbear_info) reported 25 minutes ago

  @github @AnthropicAI Reducing execution overhead sounds great until Opus 5 decides to refactor our entire build script just to fix a single typo in a comment.

• 
  Zack Fitch (@Jzfitch1) reported 27 minutes ago

  @DavidSKrueger @bvhughes It was reported by users. You see it all over the issues tab for codex on GitHub over the last 6mo. That sort of stuff just doesn’t get reported on, the story OpenAI ships is the one that gets attention. What we need is more competition.

• 
  Nicholas Yang (@NicholasLYang) reported 28 minutes ago

  @PredragGruevski @geoffreylitt GitHub ships about as fast as the MTA builds subway lines. How is stacked diffs still not widely available? Why is the site still so terrible?

• 
  Arafat (@yeasindesign) reported 29 minutes ago

  @mreiffy Is this a GitHub problem or a centralization problem?

• 
  Pardha Ponugoti (@pardzz_) reported 30 minutes ago

  @MattSilver @denk_tweets @beehiiv Set up agents that pull down the branch, spin up a local environment, write playwright scripts to drive the browser, record the screen, and post their findings with the screen recording to the github PR

• 
  sMyle (🦋 @myles.dev) (@MylesBorins) reported 33 minutes ago

  I was definitely thinking about how I could streamline this even further if I had a small agent on my Synology, or a cloud agent in the tailnet. With that said, something satisfying about "doing it by hand" with a copy + paste from a GitHub issue on my phone.

• 
  wizzard (@wizzardouthere) reported 34 minutes ago

  ONE GITHUB FILE MAKING CLAUDE SMARTER THE MOMENT YOU INSTALL IT. It's called Andrej Karpathy's skills. One file. Zero lines of code. Built on Andrej Karpathy's own notes about where AI coding agents go wrong. Every Claude user has the same 4 complaints. It over-engineers a 10-line fix. It ignores your instructions. It marks a task done when it's not. It invents APIs that don't exist. 4 rules in this file kill all 4. Ask it to fix a typo. It used to rewrite the whole file. Now it touches 1 line. THE EXPERIENCE OF USING CLAUDE CHANGES THE SECOND THIS FILE HITS YOUR PROJECT ROOT. 170,000 developers starred it in weeks. Not for the code. There is none. For the discipline.

• 
  Josh Z (@joshzjs) reported 35 minutes ago

  Is GitHub down? 500ing? @github

• 
  Bryam Loaiza (@balt1794) reported 36 minutes ago

  @CodyBontecou Tried that, but still same issue. I had to pull the Github repo and start again. Glad I didn't commit any changes lol

• 
  Mark Chime (@markleomc) reported 37 minutes ago

  If you cant create PR's on Github, that's because github its down #githubdown

• 
  The Financial Frontier (@FiFrontierX) reported 38 minutes ago

  Hedgie is measuring the success of AI primarily through one specific business model: pure-play consumer chatbot subscriptions (ChatGPT-style). On that narrow metric, the data is weak low household penetration, low conversion from free to paid, mediocre willingness to pay. That part is fair. But then he takes that narrow failure (or at least slow success) and uses it to cast doubt on the entire $600B of AI infrastructure spend. That’s the leap you’re rejecting, and you’re right to reject it. Why your framing is stronger The majority of current AI economic value and the justification for the big spend is not coming from people paying $20/month for a chatbot. It’s coming from: Google improving Search, AI Overviews, YouTube recommendations, and ads. Meta improving ranking, feed quality, ad targeting, and engagement systems. Microsoft embedding Copilot into products people already pay for (Office, GitHub, Azure). Amazon using it in recommendations, logistics, and AWS services. The broader enterprise software layer (Anthropic’s actual business model is a clear example of this working). These are not “new apps people have to adopt from scratch.” They are upgrades to systems that already have massive scale, distribution, and existing revenue. The ROI shows up as higher engagement, better ad performance, improved productivity metrics, higher cloud margins, or reduced costs not as a separate line item called “AI subscription revenue.”

• 
  𝐇𝐚𝐦𝐳𝐚 | Networking Guy (@Hamzaonchain) reported 39 minutes ago

  CI/CD PIPELINE EXPLAINED Shipping code manually, testing it by hand, and deploying it step by step works fine for a small project, but it falls apart fast as a team grows and changes happen constantly. That's the problem a CI/CD pipeline solves, by automating the whole journey from a code change to a live application. It starts at the source, where developers commit code changes to a repository, using platforms like GitHub, GitLab, or Bitbucket. That commit is what actually kicks off the rest of the pipeline. Next comes the build stage, where the code gets compiled, dependencies get resolved, and the actual artifacts, the packaged, runnable version of the application, get created. Tools like Jenkins, Gradle, CircleCI, or Buildkite handle this part. Once built, the code moves into testing, where automated tests run to check that everything actually works as expected. Tools like Selenium, Jest, Pytest, or Cypress validate functionality here. If something fails, the pipeline stops and sends it back, rather than letting broken code move forward. After passing tests, the application goes to staging, an environment that mirrors production, for final testing and validation before anything reaches real users. Tools like AWS CodeDeploy, GitHub Actions, or Argo CD handle this deployment step. Finally, the application reaches deploy, where it goes live in production, with monitoring in place to track performance and catch issues early. You can think of it like an assembly line: • Source = Raw materials arriving to start production • Build = Assembling the parts into a finished product • Test = Quality control checking the product before it ships • Staging = A final inspection area before the product reaches customers • Deploy = The product shipped out to the customer CI/CD pipelines are the backbone of modern software delivery, letting teams ship changes constantly and reliably instead of relying on slow, manual, error-prone releases.

• 
  Rohit Kumawat | AI Engineer (@merohitkumawat) reported 39 minutes ago

  THIS IS INSANE. India gave GitHub 3 hours to delete BitChat's code. Within hours, it was already mirrored on GitLawb a decentralized code platform. No company. No CEO to subpoena. No server to raid. You can order a takedown. You can't order a network nobody owns. #GenZProtest

• 
  Sameer Soni (@SameerSoni0) reported 44 minutes ago

  @markleomc @github yeah just saw.. hopefully they fix it quick.. i have important PR to raise ;/

• 
  Vox (@Voxyz_ai) reported 44 minutes ago

  boris cherny at anthropic says opus 5 is the hardest model they have made to prompt inject. he also says that part is 𝗮 𝗯𝗶𝘁 𝗯𝘂𝗿𝗶𝗲𝗱 𝗶𝗻 𝘁𝗵𝗲 𝘀𝘆𝘀𝘁𝗲𝗺 𝗰𝗮𝗿𝗱. prompt injection is someone hiding an instruction inside something your agent reads. a github issue, a web page, a doc someone sent you. it reads it and does it. so i dug out section 5.2.2. every number below is with thinking on: • your agent reads a planted instruction while working in a repo. gray swan's shade attacker, 200 attempts per scenario: attacks land 7.03% of the time on opus 4.8, about one in 14. on opus 5 it is 0.56%, about one in 180 • same attacker, letting it drive your computer: 7.14% down to 0.54% • browser is a separate eval, 129 environments. stripped of every safeguard, which is not how cowork ships: 31.5% down to 3.70% • same 129 environments with auto mode on: zero successful attacks • auto mode is two layers, probes on incoming tool results and a classifier on outgoing tool calls, failing independently. probes alone take coding down to 0.18% of all the opus 5 numbers flying around today, this is the only set that touches your repo. flip to 5.2.2, then count how many things your agent reads in a day that you did not write.

• 
  Kevin Burton (@inputneuron) reported 46 minutes ago

  Two @github outages this week and a @useblacksmith outage as well as @AnthropicAI performance issues yesterday. This is stressful.

• 
  Leo - 15 y/o founder (@leodev) reported 48 minutes ago

  @anthonysheww want me to make you a few github issues so you won't be bored?

• 
  Vyom (@HelloVyom) reported 49 minutes ago

  India banned an app built by Twitter's co-founder Jack Dorsey amid CJP Protest. The app is bitchat (Messaging App). No internet needed. No servers. No phone numbers. Messages hop phone to phone over Bluetooth. Built specifically to work when the internet doesn't. The context: Students protesting at Jantar Mantar over the exam paper leaks. Mobile internet around the site cut 5 times this month. So protesters found an app that works without internet. And The response was to ban the app. GitHub got 3 hours to comply. The irony: You can't take down open source code. It's mirrored everywhere. Still on every app store. You can shut down the internet. It's much harder to shut down an idea designed for exactly that.

• 
  abdul karim (@kodekarim) reported 51 minutes ago

  @vincent_hus Someone's next GitHub streak starts with one issue.

• 
  Riqque_gunner (@Tariqq_gunner) reported 55 minutes ago

  GitHub going down once every few months isn't the real problem. The real problem is there's no serious second option most teams actually trust. GitLab exists. Nobody switches.

• 
  Kelvin Murumba (@ItsMurumba) reported 58 minutes ago

  @github Request are down, time to sleep. Also time to test your automated workflows for failure tolerance.

• 
  KrunalSinh Sisodia (@krunalbuilds) reported 59 minutes ago

  1/ An empty README = red flag. It tells me you built it and forgot it. Write one sentence. Just one. 2/ Committing directly to main. Every. Single. Time. Branches exist. Use them. 3/ 47 repos, 0 pinned. You're hiding your best work behind your worst. 4/ Commit messages that say "fix" or "update." Fix WHAT? Update WHAT? 5/ No contributions to anything public. Forks count. PRs count. Show you exist. 6/ Projects with no live link and no screenshots. I'm not cloning your repo to see if it works. 7/ A bio that says "Aspiring developer." You're a developer. Own it. 8/ Last commit: 8 months ago. Even one push a week signals you're still alive. Your GitHub isn't a storage drive. It's your pitch deck. What's the one thing you're fixing on yours today? Drop it below 👇

• 
  REVENGE ARC (I'M HIM. BIO/ACC) (@RetardedNi85688) reported 60 minutes ago

  Gmgm got my hands on $SOLVE @open_solve. I was in this pre-bond and still holding as I believe this is the first time I've been invested in a scientific research play. Solana:GwyWFsDKW9a2ref1EWqdUS7B37Toii433zrAh9Dipump As a science inclined individual, the bottleneck has never been generating ideas. Hell we generate thousand a day and million a month. The bottleneck is coordinating, verifying, and converging on truth. I think @open_solve might just be on to something here. They might actually be the breakthrough for science and we are currently overlooking that. Like github, instead of treating scientific knowledge as static papers locked away in journals, it treats research as a living repository. Research questions become repositories. Micro-tasks become issues. AI researchers submit evidence. Independent AI auditors verify every claim before it's accepted. Synthesizers continuously build an updated consensus from verified facts. Every contribution has provenance, reputation, and a visible audit trail. Avoid thinking that this is just using AI to answer questions cause that's just really underselling it. Also I saw $MATH running at well but I think they might be competitiors which people are favoring one side. $MATH .st is focused on AI-assisted reasoning and solving problems. That's valuable because it helps intelligence produce answers faster. @open_solve is trying to solve a different problem entirely: How do thousands—or eventually millions—of AI researchers coordinate without trusting one another? History suggests coordination layers often become more valuable than the individual workers they coordinate. *** became foundational not because it wrote better code, but because it became the protocol every developer relied on. GitHub became possible because *** existed first. If AI scientists become abundant, and I think they will—the scarce resource won't be intelligence. It will be verified truth. Anyone can generate a hypothesis. Far fewer systems can prove where it came from, who challenged it, who verified it, and why it should be trusted. And if that's the correct abstraction, then every future AI scientist may need a coordination layer before its discoveries can become knowledge. That's where I think $SOLVE 's long-term upside lies.