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 (19%)
• Errors (13%)

Live Outage Map

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

City	Problem Type	Report Time
Paris	Website Down	12 hours ago
Saint-Paul	Website Down	1 day ago
Saint-Paul	Website Down	1 day ago
Mexico City	Sign in	2 days ago
León de los Aldama	Website Down	2 days ago
Créteil	Website Down	25 days ago

Full Outage Map

Community Discussion

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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:

• 
  Julian Goldie SEO (@JulianGoldieSEO) reported 4 minutes ago

  Google AI Studio: You can now import your GitHub code with one click. There's a free update inside AI Studio that fixes its biggest problem. For months, it was a one-way street. You could build an app and push it OUT to GitHub. But you could never bring old code back IN. That wall is gone. Here's why this is huge: → Got an old project sitting in GitHub? Import it. Gemini reads the whole thing. → Tell it "add a contact form" or "fix this on phones" in plain English. → It works with your real code. Not a copy. Not a guess. → Build in Cursor or Claude Code, push to GitHub, polish in AI Studio. → No rebuilding from scratch. No copy-pasting files by hand. You don't need to be a coder. If someone built you a website, you can now update it yourself by typing a sentence. Start small. Import one old project. Ask Gemini what it would improve. That dusty repo you gave up on? It just came back to life. Want the SOP? DM me. 💬

• 
  Suvrakamal Das (@SuvrakamalD) reported 4 minutes ago

  i use fable to fox all my mac softwares. it is specifically designed for my usecase. works great with open source softwares. a click and drag function in macmouse fix was not working properly in my mac for a long time. instead of raising an issue on github i just reproduced the behaviour to claude and boom. my customized software is ready

• 
  Ray 👨🏽‍💻 website & app developer (@Raynerdtech) reported 4 minutes ago

  Yesterday I posted: “**** programming. **** Java. **** databases. **** servers. **** networking.” A lot of people thought I was joking 😭 I wasn’t. The code worked. The problem was everything around it. Deployment. Servers. Databases. Infrastructure. The funny part? Most of that headache could have been avoided if I knew about Symplax earlier. Built by my guy @LazyCode3 The easiest way to describe it: Vercel for your own VPS. GitHub deploys. Databases. Metrics. Backups. You keep full control of your infrastructure without the usual VPS pain. Self-hosting shouldn’t be harder than building. Link in the comments. 👇🏾

• 
  Nicholas Preston (@Mike_Preston17) reported 4 minutes ago

  @Arrghtv I seem to recall using BasedOn just once in a similar manner. It was rough forcing triggers to honor styles, but I think I pulled off an extension method that did it safely for a very specific trigger situation. Maybe when I implemented `on:hover`. Will dig in the library. I keep a series of nuget packages that like to chain off one another and that also solve specific issues like this. It's about 20. I call them "micro libraries". I use them like a surgeon's wire, because so many W2 (software has an underbelly of jobs no one wants, even in the C# world) contracts repeatedly had the same stupid problems and I got tired of rewriting the same fixes. Wpf is one of them. Unreleased, tho. I'm releasing a package today specifically for Pocketbase connections. Just a simple client. I'm also forking all my favorite, starred repos on GitHub and keeping track of them, lest the go bad. Tired of the old, "**** went down because padleft changed versions" problem. Wpf and (w2 contracts) trained me to have a DIY mindset. Tough to stick to when everyone wanted to have a Agile-Democracy,lol. But now with AI, this changes! I can be make waves and actually be DONE with a project. I've always wanted that.

• 
  Abhas Bhattacharya ⤵️ (@abhas_tweeter) reported 7 minutes ago

  @NoriSte @siddharthkp Great idea. I assume this repo is created intentionally for interviews? Or is it somehow derived from real Github codebase and old issues?

• 
  Raj raorane (@raorane_raj) reported 9 minutes ago

  there was this other tool before it called OpenClaw it got huge. 382k stars on github. everyone wanted it. but it had a big issue for eg: if you told your AI "check my email" and the email contained a hidden trick, it could spit out all your passwords.

• 
  adas🧦🌹 (@adastroworld) reported 14 minutes ago

  Codex is broken so I had to go to GitHub to get the actual install from a comment in an Issue Today separates the boys from men

• 
  NIKHIL (@badnikhill) reported 14 minutes ago

  Wake up→open github project →write insane amounts of code → break everything→fix it like a maniac →repeat till 5AM. No sleep. No chill. Just pure unhinged contribution mode. That's how you go legendary. Who else going full degenerate this summer? #GSOC2026

• 
  Christian Aranda (@ChristianInProd) reported 15 minutes ago

  @karrisaarinen We were toiling away using GitHub issues, tried out Linear and my quote in Slack was “I hate how beautiful Linear is” and we moved everything over immediately.

• 
  Insider.Space (@InsiderDotSpace) reported 25 minutes ago

  @RuneCrypto_ LOOOLLL $200B ? memes ? :D:D:D:D:D:D:D The network is terrible and slow, they're begging GitHub for help. 🤠🤠🥳🥳🤡🤡🤡

• 
  H I K A R U (@Terry3nty) reported 29 minutes ago

  Now imagine an AI agent. Today it needs GitHub. Tomorrow it needs Gmail. Then PostgreSQL. Then Docker. Then your local files. Then AWS. Then Notion. Then a browser. Unlike traditional software, an AI agent isn’t built for one workflow. It’s expected to perform many different tasks across many different systems. That’s where the problem starts. Every tool speaks differently. Every API has different rules. The AI doesn’t just need access to tools… It needs a consistent way to understand and use them.

• 
  Clifford Richardson (@CorvusCrypto) reported 33 minutes ago

  @kellabyte If you're a leader you need to be better about handling emotion. It really drags down my confidence in Andrew being the person toead zig to 1.0. I get your point about empathy but it's a pattern with Andrew (this, GitHub, etc.) He becomes vitriolic at the slightest challenge.

• 
  Techjunkie Aman (@Techjunkie_Aman) reported 33 minutes ago

  GitHub has quietly become one of the biggest Android app stores on the internet. The only problem? Nobody built a Play Store for it. Thousands of amazing Android apps live only in GitHub Releases. Installing them means hunting through repositories, checking release pages, downloading APKs manually, then remembering to check for updates. Developer Samyak Kamble got tired of that. So he turned GitHub itself into an app store. RepoStore automatically discovers public GitHub repositories whose latest stable release contains a real installable APK. No manual submissions, no private index, no middlemen. Every app must meet strict rules: • Public repository • Latest stable release • Real APK attached • No draft or prerelease builds The result feels remarkably polished. Material 3 UI, Material You theming, rendered READMEs, screenshots, release notes, install tracking, update detection, developer profiles, and one-tap installs, all fetched directly from GitHub. Optional GitHub sign-in boosts API limits from 60 to 5,000 requests per hour, making browsing much faster. Built entirely in Kotlin with MVVM architecture and released under the MIT License, RepoStore is the bridge between GitHub's open-source ecosystem and the app store experience Android users have always wanted. One developer got tired of digging through GitHub Releases... ...so he built the Play Store GitHub never had.

• 
  Hamcodes (@Hamcodehacks) reported 33 minutes ago

  @Daily_CyberSec "Indirect" is the word that should scare people. The attacker never talks to the model. They just plant text in a GitHub Issue and wait for the agent to read it. Any channel your agent reads from is now an input to its instructions. Treat all of it as untrusted.

• 
  *nilpointer (@Dastagi39923618) reported 36 minutes ago

  github's diff page is completely broken always showing a single file diff. whats happening at @github

• 
  Dawson James (@Dawson_James_) reported 36 minutes ago

  @hunterhammonds @linear We’re currently switching from linear to notion. Biggest gap in linear was (1) no easy way to manage docs/artifacts produced during the dev cycle, and (2) no way to facilitate the product operating model (see Marty Cagan’s work) - writing down business problems, creating OKRs, aligning on outcomes, etc all before creating a ticket. Agreed though that Linear is much much better and easier to use once you have your tickets identified, and connecting them to GitHub branches and releases. Notions solution here feels over engineered and I don’t want to set up more databases, agents, and workflows inside our notion workspace.

• 
  Sean (@Sean1h3z) reported 37 minutes ago

  Had a small financial planning firm reach out to me for help on tech. They were already using Claude, thanks to a 21-year old intern at the office. They got offers from overseas shops asking for ~$5k/month retainers to rebuild a website and optimize it for marketing. I told them don’t do that. The intern generated one file of html with Claude, looks really nice, way better than their current website. They couldn’t figure out how to get it deployed. I told them get a GitHub and Vercel account and let’s connect in a week. Sat down with them for thirty minutes yesterday, got *** installed on their machine, showed them how GitHub works. Got Claude desktop app downloaded and had them making quick changes and deploying things within an hour. Saved them $5k/month and now they understand how to make changes to their website.

• 
  Rituraj (@RituWithAI) reported 41 minutes ago

  🚨 Someone built the web crawler that every AI agent actually needs. Not a scraper. Not a spider. A crawler designed specifically for feeding LLMs — structured, clean, and fast enough to process the entire web at scale. It's called Crawl4AI. 44,000 GitHub stars. The most starred web crawling repo in AI history. And it does something every other crawler gets wrong. Here's the problem. Every web crawler built before AI was the primary consumer was built for humans or databases. They returned raw HTML. Noisy. Bloated. Full of navigation menus, cookie banners, ad containers, and script tags that have nothing to do with the content you actually need. Feed that raw HTML to an LLM. You're wasting 60-80% of your token budget on noise. Your context window fills with irrelevant markup before the actual content loads. Crawl4AI returns clean, structured Markdown. Not HTML. Not JSON. Markdown — the format LLMs read most efficiently, with all the noise stripped and the structure preserved. Here's what it actually does: → Async-first architecture — crawls hundreds of pages simultaneously without blocking → LLM-ready Markdown output — clean content, no navigation noise, no ads, no cookie banners → Smart content extraction — identifies the main content block automatically, ignores boilerplate → JavaScript rendering — handles SPAs and dynamic content via Playwright integration → Media extraction — images, videos, audio all captured with context → Link analysis — internal and external links extracted and categorized → Structured data extraction — CSS selectors, XPath, and LLM-based extraction strategies → Session management — maintains login state, cookies, and browser context across requests → Proxy support — rotate proxies for large-scale crawling → Magic Mode — automatically handles consent forms, cookie banners, and overlays Here's the architecture that makes it genuinely fast. Crawl4AI uses an async browser pool — multiple browser instances running simultaneously, each handling their own queue of URLs. No sequential processing. No waiting for one page before starting the next. Hundreds of pages crawling in parallel. Combined with smart caching — pages already crawled get served from cache without re-fetching — large crawls that would take hours on a traditional crawler finish in minutes. Here's the wildest part. It ships with a Deep Crawl mode and an AI-powered extraction pipeline. You describe what you want to extract in plain English. Crawl4AI uses an LLM to intelligently extract structured data matching your description from any page — no CSS selectors, no XPath, no brittle scraping rules. "Extract all product names, prices, and descriptions" — it understands that instruction and applies it to any e-commerce page it crawls. And it has full MCP support — Claude Desktop, Claude Code, and any MCP-compatible agent can call Crawl4AI as a native tool. Your agent can crawl the web as part of its reasoning process without you writing a single line of crawling code. Your agent can now crawl any website, extract clean structured content, and use it directly in its reasoning — at the speed of async Python, at the scale of a professional web crawler. 44K GitHub stars. 6.2K forks. 847 commits. Apache 2.0 License. 100% Open Source. GitHub link in the comments 👇

• 
  JurixAI (@JurixAI_) reported 44 minutes ago

  We've officially registered JuriXAI Auditor as an ASP on the @XLayerOfficial AI Marketplace and we are now awaiting listing approval. The initial automated checks have already returned a PASS. JuriXAI brings automated, micro-payment-powered smart contract and GitHub repository auditing to the X Layer Mainnet. No more slow manual reviews. No more biased judging. Just fast, objective, and on-chain auditing. Here's how we are changing developer audits 👇

• 
  TnvMadhav (@TnvMadhav) reported 46 minutes ago

  For some reason in the past two days I haven't really got @OpenAI 's Codex to use the gh cli properly. While it works in the terminal in both Codex and otherwise, it doesn't work in the sandbox environment of Codex. I smell some updates that ChatGPT is trying to use to install the GitHub plugin but I like to do things with battle-tested existing gh CLI, with as few dependencies as possible. Could this be because of a security issue? As in the access token in my local work computer shouldn't be read? So I wanted to debug this a bit more and installed the Codex CLI on my Mac. While the same prompts, which involve the use of gh CLI tools, "work" on the CLI but not on the desktop app. I'm not sure if this was intentional on the desktop app. I asked Codex itself to perform a root cause analysis but it seems to have no clue or because there is no published documentation on this. By this I meant the execution environment change. It is clear that the sandbox does not have access to the network or the Mac OS keychain but I guess if you give it access once, there is some sort of expiry time for it to work.

• 
  rachaelsacks.eth (@RAnSacks) reported 46 minutes ago

  @GJarrosson 9/9/6 is an embarrassing psyop, saying you're working hard is not working hard. Period. Like let me see your contributions on github; go and flex that instead.

• 
  Farhan Tawfeeq ✦ (@farhantawfeeq56) reported 46 minutes ago

  We humans are bad at one thing (me included): spotting changes in large amounts of information. Now imagine spotting changes in huge codebases. @github has became a leader by solving this exact problem. Imagine your teammate says: "I changed the authentication system." There are 50,000 lines of code in the project. Now answer this: What exactly changed? ?? Without a comparison view, you'd have to open the old file, open the new file, scroll, compare them mentally and hope you didn't miss anything.. That’s why instead of showing the code, GitHub shows the change. Only the thing that changed. Old line New line Green means added. Red means removed. That’s it. This is a very good way to answer the exact question the user asks: "What changed since the last time I saw this?” And.. Github optimizes for that exact question. Many people think that Github is a code viewer. But in reality, it is a change viewer. And there is another thing which I really like in there: Instead of just showing the changes/changed line, it also shows a few unchanged lines above and below them. Example: function login() { validate(user); + return false; - return true; } Without the surrounding context.. you'd have no idea where the change happened. Too much context is overwhelming. Too little is confusing. GitHub gives just enough. And the best part is that it scales. Whether you have changed 1 line or 100 or 1000 or 50000, the interaction stays almost the same. To me, this is good UX.

• 
  tux (@gitcommit90) reported 47 minutes ago

  Tencent Hy3: Apache 2.0 open weights, claims to match flagship models with 2-5x more parameters. Numbers from the blog: > hallucination rate 12.5% -> 5.4% > commonsense errors 25.4% -> 12.7% > tool-call scaffolding variance within 4% across CodeBuddy/Cline/KiloCode > ~47-49% fewer tokens vs GLM-5.2 on doc/presentation tasks WorkBuddy internal: task success 72% -> 90%, time -34%. API: 1 RMB/M input (about $0.14), 4 RMB/M output, 0.25 cached. HN thread has operators comparing it to DS4 Flash on DGX Spark. One says Hy3 stays on track better despite being slower. Nobody's posted local tok/s yet. Free on OpenRouter until July 21. Weights on GitHub and HuggingFace. I'll try it on the Spark before I trust the bench numbers.

• 
  Nikhil Kumar (@nickssbuilds) reported 49 minutes ago

  Cognition AI announced Devin and charged $500/month for it. The open source community built OpenHands in response. It now has 70K+ GitHub stars, a $18.8M Series A, and scores 72% on SWE-Bench - at or above proprietary alternatives. What it actually does: - reads a GitHub issue - writes a fix inside a sandboxed Docker environment - runs tests - opens a PR The part that matters is that every action is logged. You see exactly what the agent did and why. No black box. No vendor lock-in. This Runs on any LLM through OpenRouter or local models via Ollama. This is what the open source community does when someone charges $500/month for something engineers could build themselves.

• 
  Mr.UNIX (@mrunix0) reported 52 minutes ago

  @kirancodes Now it's written in Rust and still has twice as many open GitHub issues as both Node and Deno combined

• 
  Johnny 5 (@macncrash) reported 53 minutes ago

  some kind of stall but it restarted & now about 15% done, the panel now won't show me the real-time results but we are still cooking for more than 12 hours straight. I think this happened when I switched VPNs so probably a bug in the dashboard. Many s1 issues found as expected. Every repo on github with more than one 1000 stars probably needs an audit to survive the next wave

• 
  Rajan Bhattarai (@cdrrazan) reported 53 minutes ago

  GitHub makes you clear ~6 confirmations and type the full repo name by hand to delete a repo. Fine! Except it does the same thing whether the repo has 100K commits or one commit you pushed 20 minutes ago. That's the tell. The friction isn't calibrated to risk; it's calibrated to nothing. Real "confirm your intent" design scales with blast radius. Deleting a repo with 40 contributors and 2K issues should hurt. Nuking a throwaway you made this afternoon shouldn't. GitHub knows the commit count, the stars, the age, the contributors. It uses none of it. Uniform friction is the easy version to build. It's also the one that trains you to click "confirm" without reading — which quietly kills the whole point. Good instinct. Lazy implementation!

• 
  Kunal Chopra (@0xkunalchopra) reported 53 minutes ago

  peak ai era is asking claude to debug why obsidian won’t load community plugins, watching it spend 20 minutes checking github access, devtools, sync errors, tailscale, vpn configs, firewall, dns, proxies, avast filters, network panels, websocket statuses and then the fix is: quit the app and open it again we had this skill in 2006. every uncle, cousin, cyber cafe guy knew it. “restart the computer” was the original agentic workflow. we just got too sophisticated and forgot.

• 
  Mikhail Rogov (@i_mika_el) reported 54 minutes ago

  @AyushSarode07 then probably not a GitHub-wide issue. I would check the workflow/status checks on that exact commit first, warning sign usually means one check or integration failed.

• 
  Tibor Blaho (@btibor91) reported 55 minutes ago

  Summary of Reddit AMA about "GPT-5.6 and Codex in ChatGPT" with OpenAI's Codex team on 2026-07-10 (opened with the stat that more than 5 million people use Codex every week, twice as many as three months ago, with 150 features and improvements shipped in that period) Model selection and reasoning levels - Sol Medium for most things, Sol Ultra for genuinely hard tasks, Terra for quick non-coding tasks or usage-conscious work with performance competitive with GPT-5.5 on some tasks at lower cost, and Luna for subagents - Use a light model with low reasoning for tiny edits, quick questions and docs cleanup, regular Sol medium for small bugs with a clear repro, Sol with higher reasoning for ambiguous bugs, unfamiliar repos and cross-cutting refactors, and Sol Ultra high with plan, verify and tests for migrations, security-sensitive changes, production issues and anything where being wrong is expensive - There is no "Auto" model today, but GPT-5.6 tries not to overthink simple tasks by itself, and the new slider in app and web maps most levels to Sol reasoning efforts and falls back to Terra on the lowest effort, with the team agreeing users should not have to become routing experts but still wanting an explicit override since latency tolerance varies by person and moment - For UI work Sol is best and shines with reference images, improved UI design in frontend web development was one of the goals with 5.6, and 5.5 is only worth using if your instructions were tweaked for it Speed, context window and persistence - Users who find 5.6 slower may not need the same reasoning level as with 5.5, Sol Medium is faster than 5.5 for most things, Fast mode runs at about 1.5x speed, and soon Sol will run on Cerebras at ~750 tokens per second - No promises on a 1M context window for Sol, the team said compaction works fairly well for long threads, and will take a closer look at the long-context feedback - The model can give up too fast and revert whole patches when results are not optimal, unlike Fable which tries to fix a bad patch instead, and the team said "/goal" helps make the agent more persistent, persistence and reduced code complexity are planned improvements, and suggested trying 5.6 Sol with High reasoning - Give Codex bounded goals with room to reason deeply instead of letting it prematurely conclude something is impossible - For long-running research and "/goal" work the example structure was explore broadly vs execute narrowly, try a defined number of hypotheses, run tests after each attempt, then stop and report what was learned plus the next best experiment Usage limits and pricing - Agentic usage counts by the feature being used, not the surface, so Codex everywhere (app, CLI, IDE, web, mobile) and ChatGPT Work consume the agentic bucket, normal ChatGPT chats do not, and image generation, file uploads and voice have separate limits - Task costs vary a lot, a tiny edit uses a fraction of the allowance and long-running tasks with large codebases or deeper reasoning use significantly more - OpenAI does not secretly change usage limits, unintended usage bugs are addressed and resets are provided, more transparency into consumption is being worked on, and missing resets can happen if you changed plans in the past 24 hrs - On pricing there is no promise it never changes, but the stated mission is to make sure AGI benefits all of humanity, which requires making tools like Codex broadly accessible, and Plus includes Codex usage with credits letting heavy users scale without jumping to a much more expensive plan - For MCP-heavy workflows burning limits fast (Unreal Engine example) the tip is to wrap the MCP into a CLI with a skill, or create a custom subagent with the MCP in its config at a lower reasoning level Desktop app merge and stability - The team hears the ChatGPT Classic frustration, both apps can run side by side for now, ChatGPT Work is pitched as significantly better at performing tasks especially with computer use, the new Chrome extension brings a sidebar chat into your browser that interacts with website context, filesystem and connectors - A long submitted bug list covering freezes and stuck threads, broken Browser and Computer Use, thread, connection and configuration problems, update and packaging issues, resource usage and smaller regressions was shared in full with the relevant teams, with the team agreeing the quality bar for the app needs to step up while shipping quickly - More automated testing infrastructure is being spun up and feedback on Reddit and X gets reviewed daily, and Browser Use and Chrome plugin issues from the merge were said to be fixed - Windows was admitted as historically shortchanged since the team mostly develops on Mac, a concerted effort on parity, testing and paper cuts is underway, 5.6 improves how Codex operates in the Windows sandbox, and auto review is recommended over full access to reduce risks - "Full Access" repeatedly asking for permissions is not expected, possible causes are workspace or admin policy, the specific command, a permission state mismatch or a bug Browser, platforms and release communication - The Chrome connector launch-day bug was fixed as of last night and Chrome Beta should work out of the box - Extension support for the Codex browser is in progress (password managers etc.) plus typeahead, history, translations and a better new tab page as Atlas retires - Features from ChatGPT Classic like recording are planned for the new desktop app so agentic features run on the more capable Codex agent harness, and chat can already reference open tabs in the in-app browser - A Linux desktop app was confirmed in the works, no timeline yet - Changelog granularity was acknowledged as needing improvement after 150 features shipped in 3 months with multiple ships a week Benchmarks, safety and research culture - On METR's reward hacking report the team actively checks for and penalizes cheating during evals so results reflect actual capability rather than solving tasks outside the spirit of the eval, and uses third-party vendors to run benchmarks independently - The team denied lobotomizing models before releases, iterative deployment means sharing core capabilities as is with guardrails for bad actors - Sol post-trained Luna, and researchers now work at a higher level of abstraction with multiple concurrent Codex threads validating hypotheses around the clock - One researcher put p(machines of loving grace) at 85.424242%, citing an internal model solving the Erdos problem, o3 helping diagnose previously unsolved children's diseases and 5.2 proposing a new theoretical physics formula, said the main worry is how society adapts, spent 1.5 years on safety research at OpenAI, expects a huge chunk of researchers to work on safety within a few years and says internal talent keeps their p(doom) very low - Connectors in the harness (Slack, GitHub, Notion) felt like a step function change in making Codex a productive coworker