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	21 hours ago
Ashkelon	Website Down	2 days ago
Veigné	Errors	11 days ago
Paris	Website Down	14 days ago
Saint-Paul	Website Down	15 days ago
Saint-Paul	Website Down	15 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:

• 
  Alex — Polymarket Odd (@oddsOnPMKT) reported 2 minutes ago

  Fable 5 Made Me a 5 Min Polymarket Trading Bot (full bot & results) High-frequency prediction markets look like easy money until you watch your P&L bleed in real time. I built a 5-minute strike sniper bot running live across four symbols—BTC, SOL, XRP, ETH—using lag arbitrage between Polymarket and external data feeds. The infrastructure works, the execution is brutal. Signals: 78% win rate on 9 trades (7 wins, 2 L's), daily P&L +$20.21, but two positions showing -5 each. One position down 73% with 16 seconds left, needed price under .72 in 9 seconds—missed by a heartbeat. ETH fill currently down 18%, another up 12%, hovering around 1828/1827 strike level. Position size: $5 per trade. Four simultaneous markets, 5-minute windows, taker orders for speed. Between the lines: the setup is solid—multi-account Polymarket integration, gamma API for market data, Hyperliquid for external pricing, automated share calculation based on size. But running four symbols at once in 5-minute markets is overkill. I leaned on Fable 5 to cook up the strategy from past GitHub patterns, which means potential overfitting to historical conditions that may not persist. No paper mode, live money on the line from day one. The more you trade, the less you have—frequency is the enemy here. Risk: sample size is laughably small. A 78% win rate means nothing after 9 trades. API latency, data sync delays, and competition in ultra-short windows can erase any edge instantly. Correlated losses across four assets would blow through capital faster than you can hit stop-loss. Daily stop loss is not optional here—it's mandatory. Flip: three consecutive L's, API latency spikes above 200ms, win rate dropping below 55% over 50 trades, increased order flow competition in 5-minute markets, correlated drawdown across multiple symbols, any change in Polymarket's fee structure or API limits. Trade: entry via lag arbitrage signals when strike price diverges from external data, $5 size until edge proven, 5-minute expiry window, invalidation if price does not cross threshold within 60 seconds of entry. Scale only after 50+ trades with consistent positive expectancy. Watch: API response times and data feed reliability, win rate normalization over larger sample, cross-asset correlation during volatility spikes, daily stop loss effectiveness, paper trading results before any size increase, market depth changes in 5-minute contracts. Bottom line: the infrastructure is ready, the edge is unproven. Start small, expect losses, and treat 5-minute markets as a laboratory, not a paycheck. #Polymarket #PredictionMarkets #HFT

• 
  Bhavani Kalisetty (@b_kalisetty) reported 4 minutes ago

  is @github down? I'm unable to get past the auto-merge checks

• 
  Kosumi (@Kosumi1989) reported 7 minutes ago

  @efcon5 I always knew distribution would be the biggest challenge. Still, I built it because I needed it myself. I use it every day, so it's solving a real problem, not just sitting as another abandoned GitHub project. Even if no one else ever used it, I wouldn't regret building it.

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  John (@hello_code_) reported 8 minutes ago

  @DanielSmidstrup Langchain. Incredibly powerful but the docs feel like they were written by the person who built it, for the person who built it. Half the answers live in random GitHub issues from 2023.

• 
  jsd (@datagenproc) reported 13 minutes ago

  @RyanGreenblatt @bshlgrs re: "there was some lateral movement required/it needed to get out one layer further" My understanding (based on a short convo with @timotheechauvin, errors likely mine) for why an extra layer was necessary is: - model starts in the sandbox - from the sandbox, normally the model would send requests for packages to the package registry cache proxy - but instead, the model uses a 0-day to get access to the package registry cache proxy - [my guess] the package registry cache proxy doesn't have unrestricted access to the internet. it can only download from a whitelist of URLs like github/npm/docker hub/pypi's - so to get unrestricted internet access lateral movement is required

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  keshavv (@Keshavdotdev) reported 13 minutes ago

  @Shrivvvvv like link nhi mil rhi thi , as in vercel kiya hota hein you paste github url ye build karta hein and give u the live-url right?humne build wala section complete kar diyaa tha lekin live-url ka issue tha

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  Erik (@erikaarohans) reported 13 minutes ago

  @sambenjamin___ @mattpocockuk @github fix this. Nobody wants to cycle to issues and PRs with tab.

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  Hasan Toor (@hasantoxr) reported 19 minutes ago

  Jack Dorsey just spent a launch proving the thing Kylon has been shipping for months. Block released Buzz on July 21. Free, open source, built on Nostr. Humans and AI agents in the same channels, every agent carrying its own cryptographic identity instead of borrowing a human's login. The thesis underneath it is correct. Individual agents make one person faster. Without a shared workspace, they make the whole team slower, because every handoff is a human copying output out of one window and pasting it into another. Buzz is a serious answer to that. It's also brand new. No mobile client, no migration path off GitHub, no deployments outside Block yet. Kylon is the version running in production today. Not just engineering. Sales, marketing, ops and finance teams with live workflows. Agents that hold memory and skills, join channels, read the context already in them, and turn the conversation into finished work. Two companies arriving at the same conclusion from opposite directions is how you know a category is real.

• 
  Pierre Bruno (@PierrunoYT) reported 20 minutes ago

  @AmpCode, could you add an account-wide GitHub integration that can address issues, review PRs, and work across any repository a user has access to—not just repositories owned by their own account? This would be especially useful for contributors working on external or organization-owned repositories.

• 
  IMZO Dev (@imzodev) reported 23 minutes ago

  agentjetson's day so far: → noticed tailwind CDN getting stripped on addon updates → filed #470 → noticed `*** clone && pnpm dev` was broken for new contributors → filed #469 he has his own GitHub account. collaborator access on the repo. i spent 0 minutes writing code. i spent 8 minutes reviewing.

• 
  blendaddict (@blendaddict) reported 27 minutes ago

  Day 1 of pinging @thsottiaux to please bring /remote-control to codex because the github issue keeps getting ignored

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  GamER MD (@GamER_MD_Actual) reported 32 minutes ago

  @TethisX I mean look at Eden for Switch now. Almost daily builds and Nintendo has gone after them and got them kicked from GitHub. So they made their own *** server. It’s like the harder these companies go after the groups, the more pop up just to give them the finger.

• 
  Nav Toor (@heynavtoor) reported 37 minutes ago

  A solo developer in Johannesburg named Dave Blakey built the open source version of CCleaner, the tool Wired reported hackers used to spread malware to millions. He gave it away for free. It is called Kudu. CCleaner was hacked in 2017. Hackers hid malware inside the official update. 2.27 million people downloaded the infected version. It was hacked again in 2019. It is still sold today under new ownership. CCleaner Professional costs $29.95 for the first year. It renews at $44.95 a year after that. The Premium Bundle is $64.95 a year and adds Kamo, a privacy tool with VPN protection. Kudu costs zero. On every OS. Forever. Under MIT. CCleaner scans your PC. CCleaner charges you. Kudu scans for you. Here is how it works. You download the installer. You open Kudu. You pick a scan. The app runs it and shows you exactly what it wants to delete before it touches anything. System Cleaner. Temp files, logs, caches, crash dumps. Browser Cleaner. Caches across all major browsers in one pass. App Cleaner. Leftover files after uninstalls. Gaming Cleaner. Game launcher and shader caches. Registry Cleaner. Broken and orphaned entries. Startup Manager. Boot impact analysis. Disk Analyzer. Interactive treemap of your drive. Debloater. Removes Windows bloatware. Malware Scanner. Signature matching, heuristic analysis, Windows Defender integration. Works on Windows, Mac, and Linux. Installer for each. No ads. No upsells. No telemetry. Every line of code is on GitHub. Dave lives in Johannesburg, South Africa. His GitHub is 15 years old. He opened the Kudu repo in March 2026. He wrote 349 of the 403 total commits himself. The other 54 are dependabot updates. Version 1.45.0 shipped two days ago. 75 releases in four months. 1,370 stars. 110 forks. CCleaner can't shut this down. The MIT license does not permit that. Gen Digital, the $15 billion company that owns CCleaner, can't shut this down. They employ zero of its maintainers. CCleaner shipped malware to 2.27 million people. Gen Digital sells the same tool by subscription today. Dave Blakey built one that does the same job for free. (Link in the comments)

• 
  Singular Prism (@singular_prism) reported 37 minutes ago

  @EntireHQ @AyushSarode07 why does it need github login is my github project copied to entire when i want to work on a project.

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  Filippo Tarpini (@FilippoTarpini) reported 39 minutes ago

  I'm becoming increasingly skeptical of open source due to AI training on my work... Unfortunately in this world, you need to make a living. If, by uploading great techniques I invented for HDR/grading on github I'm feeding AI, I'm basically donating my hard work to developers that will use AI to write code. It's as if we were collectively donating to AI corporations, which will further profit from the knowledge they get from our code. I was ok with other experts taking my code and implementing it with some effort in their game, but not when it's done passively like this. Many of our jobs/skills will seem a lot less necessary when AI can spit out a version that is even 1/10 as good ("Well, but it works" is often the motto out there). The idea of owning "algorithms" has gone down the drain when every code base you work on, whether public or not, is running Claude. We are essentially shooting ourselves in the feet and nobody seems to talk about it? It feels like a classic human bias. We all focus on today, never on tomorrow. It's going to take 20 years for laws to catch up on this, and by then it will be too late. I'm not against AI, but this business model is clearly going against us.

• 
  Mehmet Mars Seven 🐴 (@MehmetMars7) reported 41 minutes ago

  1/3 A case from my own experience: as some may know, I prompted GPT on Erdos problems and posted them on github, and one proposed solution was eventually accepted as correct. Never claimed, "I solved it," because I didn’t. GPT produced the solution.

• 
  Matt (@m13v_) reported 45 minutes ago

  we don't sell it as a growth hack, because it isn't one. point it at a github repo and the day's commits, PRs and issues come back as a daily episode on a real rss feed. it runs feeds for rust, postgres, kubernetes. awareness was never the product, being audible is.

• 
  adidshaft (@adidshaft) reported 46 minutes ago

  @github shipped agent automation controls for Issues yesterday. I spent some time reading the docs because the design gets at a problem every team will hit once agents begin touching real work: who reviews all the small decisions? The first version is fairly narrow. An agent can label an issue, set its type or fields, assign it, or close it. Each proposed action can carry a rationale and one of three confidence levels: high, medium, or low. Admins can let high confidence changes apply automatically while holding uncertain ones for review. A maintainer does not want to approve 80 obvious labels every morning. They also should not discover that an agent quietly closed a valid bug because its own confidence score happened to be high. Leaving a reason beside the action, without filling the discussion with bot comments, feels like a useful interface. The confidence label needs care though. It is the agent rating its own proposed action. GitHub does not claim these ratings are calibrated probabilities. High confidence is routing information, not evidence that the change is correct. A team still has to compare those labels with actual outcomes before trusting a threshold. GitHub is unusually direct about another limitation: the approval panel is a workflow convenience, not a security boundary. If an agent already has permission to change an issue, it can apply the change directly instead of suggesting it. The harder controls sit underneath the interface. Each automation is scoped to one repository. Teams choose which tools it receives. Events from users without write access are ignored by default, reducing the prompt injection surface from public issues and pull requests. Agent pull requests cannot approve themselves, and workflows created through agent work still require approval from someone with write access. There is also a real operating cost. An automation can run hourly, daily, weekly, when an issue opens, when a pull request opens, or when new commits arrive. Every run consumes GitHub Actions minutes and AI Credits. A badly scoped triage prompt can become a recurring bill before it becomes a useful teammate. My first production policy would be boring: Let the agent apply reversible metadata changes such as labels. Hold assignments and issue closure until its confidence has been measured against a few hundred real decisions. Give each automation the smallest tool set it needs. Keep external contributor events blocked unless there is a specific reason to accept them. Review cost and error rates together, because a cheap agent that creates cleanup work is not cheap. I also like that GitHub is preserving rationale as structured history. Once enough actions accumulate, maintainers can audit where an automation hesitates, where it is confidently wrong, and which repository instructions need improvement. That feedback is more useful than repeatedly rewriting a prompt from memory. We have spent plenty of time measuring whether agents can write code. I want to see a more ordinary benchmark now: can a team understand, constrain, and correct thousands of small agent decisions without turning every maintainer into a full time supervisor? GitHub's first answer is incomplete. It is also refreshingly practical.

• 
  Akos (@akoskm) reported 46 minutes ago

  @martindonadieu is it through the remote session? like cursor running on your mac and usng remote contorl on your phone? I'm not really into the cloud version, maybe I'm not using it properly, but it can't: - read GitHub issues from my private repos, even tho the Cursor app is installed and has permission to read them - i keep my cloudflare etc secrets locally in an .env file, cloud agent doesn't have access to that - i develop ios apps and the e2e ui tests need an actual macos running what am i doing wrong? appreciate the answer!

• 
  Fran Betteo (@franbetteo) reported 47 minutes ago

  Another lesson from the Sportsjobs data. Less impressive, because well, it's a niche. The hardest part about job search is the lack of openings (small market. There is a finite number of teams ofc and well, not a huge amount of companies working with sports data) And then, not getting interviews. This could be a two fold problem. 1) lots of applicants. Hard to get noticed. This is common around job search in general, maybe even more in sports. 2) candidate problem. Maybe you just need more preparation / experience (which is hard to get if it's hard to get in the market!) Point 1 and 2 can be tackled to some extent by doing projects, showing up, post in linkedin, Twitter, github. It's hard work? Yes, but as in anything that you really want , you need to spend time and try to do your best. It's not guaranteed but if you are facing those issues, your chances are much higher if you have something to show! And you will start networking as a side effect. #sportsjobs

• 
  Brown Thunder (@Brown_Thunder76) reported 47 minutes ago

  Now this makes a lot more sense. A few days ago we found a group of fiat tokens quietly sitting on Keeta mainnet. At the time they didn’t make a whole lot of sense. Today they do. Keeta just announced its partnership with LayerZero to bring tokenized commercial bank money to major blockchains. So what does that actually mean? Think of Keeta as the place where regulated bank deposits become tokenized digital dollars, euros, pounds, yen, etc. Those are the fiat tokens we found on-chain. They’re backed 1:1 by commercial bank deposits through Bivo and are built for institutions, not retail. LayerZero is the interoperability protocol that connects many of the largest blockchains together. It’s already used by companies and protocols like PayPal and Ondo. Instead of Keeta building connections to every blockchain individually, LayerZero lets those regulated assets move across Ethereum, Solana, Base, and many other chains through a single interoperability layer. Here’s an example. Imagine a business deposits $10 million with a participating bank. Keeta tokenizes that deposit into regulated digital dollars. Using LayerZero, those dollars can move to Ethereum for settlement, Solana for payments, Base for another application, and then be redeemed back into bank deposits when needed. The institution doesn’t have to care which blockchain the other side is using. That’s why this announcement is a big deal. The fiat assets we found on-chain now have a clear purpose. The GitHub updates we’ve been seeing suddenly make a lot more sense. And if institutions choose Keeta to issue and settle tokenized commercial bank money, LayerZero gives those assets access to one of the largest cross-chain ecosystems in crypto. That has the potential to bring significantly more institutional activity and value onto the Keeta network than if it operated in isolation. This is exactly why I spend so much time watching GitHub and on-chain activity. Sometimes the blockchain tells the story before the press release does. @KeetaNetwork $KTA

• 
  Anthony Humphreys (@aphumphreys) reported 47 minutes ago

  @mitsuhiko 👀 one GitHub replacement down

• 
  Sam Z Liu (@samzliu) reported 50 minutes ago

  AI memory and brains are hard because the data is just text. This means everyone has an opinion and no one agrees on how to bucket the data. It reminds me of my management consulting days when we'd spend 2 weeks debating the "framework" with the client before any real work got done. Everyone ends up with different mental models of how data should be organized. Is this MECE? Should we group by chronology or topic or data source? What about these edge cases? While there's no universal right answer (different use-cases and orgs will require different structures), there are certainly bad ways to do it that make the lives of agents and other people using your system way more difficult. At Stash, we do have one clear rule that solves a lot of the headaches: keep your raw data and LLM written outputs isolated from each other. The raw data comes from places like Slack, CRM, emails, meeting notes, etc. It represents the ground truth that should never be edited or touched by an agent. The LLM wiki is a separate area where agents, such as our sleep time compute curation, have free rein. This helps prevent agents from slopifying information over time, weird hallucinatory feedback cycles, and mode collapse. This is a clean separation for the most part but there are a couple of special situations worth outlining. First, agent session logs (e.g. claude code) contain both ground truth signal (tool calls, user messages) and LLM outputs. We treat this by separating these out in a "refining process" so they can be used in their respective silos. Second, this separation can cause confusion because it can mean some data is duplicated across the LLM wiki and raw data. For instance, we have a customer whose raw data contained expert compiled SOPs and our sleep time agent used that to create a similar skill in the LLM wiki. We think it's best to think of the wiki in this instance as an "index" or "reasoning cache" over the raw data. From that perspective, it's clearer why having duplicate information is not that big of a deal. It's just that in this case, the index is human readable. Third, a lot of the data that is fed into the system is written by LLMs (e.g. Docs in GitHub, Social media posts from influencers, etc.). Garbage in, Garbage out is still very real. In practice, this tends not to be a problem since most information that comes from external systems involves some level of human oversight. Overall, distinguishing between raw data and LLM generated data within our knowledge bases has enabled us to design around the open unsolved challenges in AI memory while still solving for our customer's use-cases.

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  wangfu91 (@wangfu91) reported 52 minutes ago

  @James_M_South @github I gave up on GitHub Copilot and cancelled my Copilot Pro+ subscription weeks ago after a series of incidents, bugs, and usability issues. Now, I am using Codex, and the experience has been much better.

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  Shubhankar (@satyakosh) reported 55 minutes ago

  @icefrog_sol Hey! That’s where Grok and Kimi enter the chat. It’s like I had the help of 3 genius CEOs who made their employees work on this project. They found out a lot of bugs and improved Claude’s output. Kimi directly posted code issues on *** and Claude automatically checked and fixed it. I should call this this GitHub Loop.

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  Kai (@superkaicode) reported 58 minutes ago

  @Pallavi_345 Honestly still amazes me how @github gets away with all the downtime and degraded performance issues.

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  World of Claudecraft (@WoClaudecraft) reported 58 minutes ago

  What World of Claudecraft actually is. The full story, with receipts. New people find this account every day and get fragments of the story. Here is the whole thing, in order, with nothing polished out. HOW THE GAME BEGAN In June 2026 we pointed Fable 5, frontier model, at a simple question: how much game can AI build in a weekend for about a thousand dollars in compute? The answer was a working MMORPG. Zones, dungeons, classes, towns, procedurally generated terrain and a soundtrack written in code. We posted it to Reddit and it went viral. Three days after Fable 5 launched, it was pulled worldwide under a government directive. We lost access to the tool that built the game. We kept building anyway, with human developers, AI agents, and increasingly the players themselves. The game never went offline. The model has since returned. The world it came back to is many times the size it left. The attention has been organic from day one. Justine Moore, an AI partner at a16z, found the game on her own and publicly called it shockingly full featured, pointing to it as a look at the future of AI-built games. Nobody pitched her. Her tweet is in the receipts. HOW THE TOKEN BEGAN. THIS IS THE PART PEOPLE GET WRONG. We did not launch solana:3WjLscH2JsXLEFJZRA9z8ti8yRGxWGKbqymPd7UicRth. A stranger did, spinning up a memecoin off the viral moment without asking us. Our first public reaction was to call it a scam and distance ourselves. With no endorsement, it went to near zero. Then something unusual happened. The players filling the servers were largely crypto native, and they were not just holding, they were grinding the game. One of them revived the abandoned token and the community claimed it. DEX Screener carries the official community takeover badge dated 12 June 2026, noting the original launcher exited. Independent on-chain analysis later confirmed the launch was fair. Mint renounced, liquidity locked, no presale, full supply circulating, and the original launcher walked away with a few hundred dollars. Only after the community had made the token its own did we embrace it. We took no allocation at mint. We launched nothing. The community chose us, not the other way around. Every part of that is verifiable on chain. WHO WE ARE Levy Street is a named, public New Zealand AI company. Our CEO Max Polaczuk (@maxpolaczuk) and the founding team previously built Sportsflare, an esports betting technology firm founded in 2019 and acquired by Entain, the global listed betting group, for CA$13.2m in 2023. That acquisition is documented across the trade press and stock filings. Reuben Horne created the first version of the game himself and leads day to day around WoC. Names, a company registration, and a completed exit. In a space full of anonymous deployers, that alone puts us in a small minority. WHAT SEPARATES US FROM THE REST OF WEB3 GAMING Industry research this year found that roughly 93 percent of web3 games are effectively dead, over 300 have shut down, and about 15 billion dollars was burned in the process. The diagnosis was consistent. Investor-first projects that sold tokens and NFTs before building games anyone wanted to play. We inverted every part of that model. The game came first and it is completely free. No wallet is needed to play, ever. There was no raise, no presale, no NFT sale, no token launch by us. The token utility that exists today is live, not promised. Optional non-custodial wallet linking, holder tier badges, a store where paying in solana:3WjLscH2JsXLEFJZRA9z8ti8yRGxWGKbqymPd7UicRth earns a discount, and Daily Rewards prize pools for verified holders. All of it cosmetic. None of it pay to win. The whole game plays identically with no wallet at all. This is also how the project funds itself. The game is free and the code is open source, so there is no box price, no subscription, and no paywall coming later. Development is funded by transaction fees generated when the token trades. Traders fund the game. Players never have to pay a cent. WHAT SEPARATES US FROM OTHER MMORPGS The entire game is open source under an MIT licence, closing in on 2k GitHub stars with 44 contributors and counting. Anyone can read the code, fork it, or ship a feature. Players already have. Hardcore mode was contributed by a player who had never written code before, a professional composer joined to score the game, and community-built arenas are in the world right now. Feature requests move from Discord to shipped code through an agent pipeline with human sign-off, sometimes within the hour. You can play in the browser, on mobile, on desktop, or run your own server. No other MMO operates like this, and no other token sits behind a loop like it. WHERE THE GAME IS RIGHT NOW WoC is in early alpha, and we are saying that as plainly as everything else in this post. We released early on purpose. The world is live, free, and growing every week, but it is not finished, and we are not pretending otherwise. Right now the priority is building the community alongside the game, because the community is the development model. The ambition is to take this from a weekend experiment to something that stands equal to a AAA studio production, built in the open, with the players who are here today shaping what it becomes. Early alpha does not mean early access paywall. It means you get to watch, and help, a AAA-scale world get built in public. WHAT WE WILL NOT TELL YOU We will not promise price outcomes, and anyone who does should worry you. The token is not needed to play and never will be. Yes, we benefit when the token trades. We are telling you that plainly instead of hiding it in a docs page. What we can promise is what you can already verify. A real company, a shipping game, a public repo, a fair launch token the community claimed for itself, and a team that builds in the open every day. Read the receipts in the reply. Then come play the game. That is the whole pitch.

• 
  vulnix (@vulnix0x4) reported 59 minutes ago

  @swe_acc oh you have to submit an issue on the github to get it verified

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  Bankr (@bankrbot) reported 60 minutes ago

  @Antification @RobinhoodComms your postmint skill is currently installed and active on v6 (shared contract 0xFF8f2e1717C897717CaaeB1fA987876c4059d9A1 with on-chain SVG cards and submit-safe avatar optimization). attempted to check the upstream repository for updates, but the fetch failed: • error: GitHub API rate limit hit while checking default branch / tree data for bankr-bot/skills i can't confirm whether this is the latest release since the update check itself failed — try again in a few minutes if you want me to force a fresh re-install from the repository once GitHub's API rate limit resets.

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  mohrt (@mohrt) reported 60 minutes ago

  @SatoshiSupport @cryptorebel_SV the github link on the website is broken fyi