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 (62%)
• Errors (21%)
• Sign in (18%)

Live Outage Map

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

City	Problem Type	Report Time
Tlalpan	Sign in	1 day ago
Quilmes	Website Down	1 day ago
Bengaluru	Website Down	4 days ago
Yokohama	Sign in	4 days ago
Gustavo Adolfo Madero	Website Down	8 days ago
Nice	Website Down	9 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:

• 
  Kendall Zettlmeier (@KZettlmeier) reported 33 seconds ago

  @davidfowl @github I would love agent mode to handle code review comments and issues but leaving the merging to the code writer (we have QA validate after an approval)

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  Kevin Worthington (@kworthington) reported 2 minutes ago

  Practical IT take after the recent npm / PyPI supply-chain compromise reports: Your build pipeline is production infrastructure. If a package install can expose GitHub tokens, cloud keys, or CI/CD secrets, that is not "just a developer issue." That is an operations problem with a security bill attached. #DevOps #Cybersecurity #SupplyChainSecurity

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  Zack Chapple (@Zackary_Chapple) reported 2 minutes ago

  @_bgwoodruff That is fair, I think its less of a GitHub dunk and more of a cry of frustration, had several times trying to do a demo or do something this week and they were fundamentally down. We've had to isolate from GitHub more than we should and thats a scary thing.

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  opdroid1234 (@opdroid1234) reported 5 minutes ago

  @HotAisle I do think making money on "github actions is too slow for agents" zeitgeist might be the same kind of side business for you that selling turbines is for boom supersonic

• 
  Kea (@alpinoWolf) reported 10 minutes ago

  @Bambardini @Polymarket @DegenApe99 What is the solution sir ? I tried to everything, but can't find a solution. AI says default wallets are proxy contracts, you are forced to use the POLY_1271 signature flow, which is currently bugged in Python see GitHub under Issues #55, #56, and #57.

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  Sukhjit Singh (@thesukhjitbajwa) reported 10 minutes ago

  Published the campus website, learned about Next.js static content and export output, uploaded the files via FTP to the server, and now brainstorming ways to automate the process using either GitHub Actions or local scripts.

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  ST-Automation (@ST_Automation) reported 15 minutes ago

  @cnakazawa @amadeus @fat Local diff viewers are the sleeper category. We do code review on five repos a week and the GitHub UI is just slow. If Codiff handles 10k line diffs without choking it replaces the GitHub tab entirely.

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  Your Friend Myk (@mykola) reported 18 minutes ago

  @joelhooks is this just static content? so like a github pages alterntaive? can't run a server etc?

• 
  David Cramer (@zeeg) reported 21 minutes ago

  @eternalmagi dont have context, is there a github issue by chance

• 
  Peter Steinberger 🦞 (@steipete) reported 21 minutes ago

  @EndGovTyranny Please file a github issue with more infos - with that alone we can't help. That's likely a weird model edge case. If you want a fast fix, use one of the top-gen models (OAI, Anthropic)

• 
  ฿Ø₮₴Ø₦Ɇ (@botsone) reported 26 minutes ago

  I just downloaded my entire github and told hermes to extract the file, and upload every repo to my home *** server. It one-shotted it.

• 
  NEET INTEL (@neetintel) reported 29 minutes ago

  A post "decoding" X's new algorithm has gone viral. It tells you what's dead, what wins, and to screenshot it. X open-sourced the entire algorithm on GitHub, so I downloaded it and checked the claims against the real code. Most of it doesn't hold up. What the post got WRONG: → "Small accounts get a 3x boost from out-of-network reach." It's the opposite. One part of the code (a file called oon_scorer) exists purely to turn DOWN posts from people you don't follow. Its own comment says "prioritize in-network." The thread printed the algorithm backwards. → "Media gets 2x the weight." There's no 2x. The code just records whether a post has an image. It's a plain yes/no without any multiplier attached. → "Posting 4+ times a day triggers a penalty." There's a real rule that stops one person flooding your feed. But here's the deal: it only spaces out how often you show up in a single scroll. There's no daily count, and no number 4. That was invented. → "Closers like 'what do you think?' get you flagged." There is no engagement-bait detector anywhere in the code. → "Long 4,000-character posts get boosted." I searched the whole codebase for "4000." Nothing. What it got RIGHT (one thing): → Replies really are judged by WHO replies, not just how many. The code has a setting for whether a large account joined your thread. Credit where due. The irony? The repo ships a file that scores post quality. One thing it measures is literally called a "slop score" — X built a tool to detect low-effort filler. A recycled "what's dead / what wins" thread is exactly that. The takeaway? X's algorithm is public. Anyone can open it, but almost nobody does. Instead, they reshare a thread that summarized a blog that paraphrased a tweet. When a post hits you with confident numbers, ask the one question that matters: did they actually open the file?

• 
  logan (@loosenedspirit) reported 30 minutes ago

  @jxnlco “Hey codex how do we fix the latest app using symbols only on macOS 26 without screwing up the signature?” “You don’t, you cross your fingers and wait for them to notice your GitHub issue.”

• 
  craig carpenter (@ccarp87) reported 34 minutes ago

  @rfleury @awesomekling AI is bad at writing Rust, so Anthropic's answer is training it on Bun's github bug reports. Rust devs can't help themselves -- they just have to talk about how smart they are in GitHub Issues. They'll have this thing trained in a week.

• 
  Glitch Truth (@glitchtruth) reported 35 minutes ago

  OpenAI just put a coding agent on your phone. Codex, the model that originally powered GitHub Copilot in 2021, now ships as a mobile-native agent. You prompt from your phone, it spins up a cloud sandbox, runs the task, writes the diff, and opens a PR against your GitHub repo. No laptop, no terminal. "Fix the auth bug" typed at lunch becomes a merge-ready PR by the time you pay the check. GitHub's own 2022 study showed Copilot users complete tasks 55% faster. That was an autocomplete assistant living inside an IDE. The mobile agent doesn't assist you. It does the whole task in a sandbox and hands you the PR. The defensible skill is no longer typing the syntax. It's knowing what to build, what to ship, and what to measure after. Action this week: pull Codex on iOS, point it at a real repo, ask it to fix something small. You'll either see the next decade of work, or you'll convince yourself it isn't real yet. Either is information you didn't have on Monday.

• 
  Sharbel (@sharbel) reported 36 minutes ago

  Someone opensourced a Chromium browser that passes every bot detection test. Not by injecting JavaScript. Not by patching configs. By recompiling Chromium itself. It's called CloakBrowser. 12,071 stars on GitHub. You swap one import line. That's it. Same Playwright API you already know. Same code you already wrote. Three lines of code. Thirty seconds to go from blocked to unblocked. Here's what it does: → 49 source-level C++ patches baked directly into the Chromium binary. Canvas, WebGL, audio, fonts, GPU, screen resolution, WebRTC, network timing, CDP input behavior, automation signals. All modified before the browser even compiles. → Passes Cloudflare Turnstile. Not sometimes. Every time. Verified live. → Scores 0.9 on reCAPTCHA v3. Human-level. Server-verified. → Passes FingerprintJS and BrowserScan. Tested against 30+ detection sites. 30/30 tests passed. → `humanize=True` flag adds human-like mouse curves, keyboard timing, and scroll patterns. One flag. Behavioral detection gone. → Drop-in replacement for Playwright and Puppeteer. Python and JavaScript both supported. → `pip install cloakbrowser` or `npm install cloakbrowser`. Binary auto-downloads on first run. Zero config. → Auto-updating binary. Background update checks. Always on the latest stealth build. → Optional GeoIP flag auto-detects timezone and locale from your proxy IP. → Docker image available. Try it with zero install: `docker run --rm cloakhq/cloakbrowser cloaktest`. Here's the wildest part: Every other antidetect browser patches JavaScript at runtime. Detection systems catch JavaScript patches. They have for years. That's why your $99/month tool stopped working after two weeks. CloakBrowser patches the C++ source before Cloudflare's systems ever see a single byte. Antibot systems score it as a normal browser. Because it is a normal browser. One that happens to have 49 fingerprint modifications compiled in at the source level. There is no JavaScript to detect. There is no injection to flag. There is nothing to catch. Browserless charges $120/month for cloud browser automation. Bright Data's Scraping Browser starts at $500/month. Multilogin starts at $99/month. Per user. Apify cloud actors run on usage-based billing that scales fast. CloakBrowser: $0. Unlimited scrapes. Unlimited sessions. Your hardware. Your code. Forever. 12,071 stars. 921 forks. Available on PyPI and npm. MIT licensed. MIT licensed. Self-hosted. Free forever. 100% Open Source.

• 
  Dusko Licanin (@dulelicanin) reported 36 minutes ago

  Your AI wastes 65% of its tokens saying "Sure, I'd be happy to help you with that." A 19-year-old developer made a markdown file that fixes this. It got 12,000 GitHub stars in 4 days. Here's what happened: Julius Brussee created "Caveman" — a Claude Code skill that forces AI to talk like a caveman. No articles. No filler. No pleasantries. Just the technical answer. Before (69 tokens): "The reason your React component is re-rendering is likely because you're creating a new object reference on each render cycle. I'd recommend using useMemo to memoize the object." After (19 tokens): "New object ref each render. Inline object prop = new ref = re-render. Wrap in useMemo." Same fix. 72% fewer tokens. But here's what most people miss: A March 2026 paper (arXiv:2604.00025) tested 31 LLMs across 1,485 problems and found something wild: Forcing large models to be brief improved accuracy by 26 percentage points. Bigger models literally perform WORSE because they over-elaborate. The researchers call it "scale-dependent verbosity" — the model rambles, and rambling introduces errors. Less words = more correct. Not a meme. Peer-reviewed science. The real cost math: → Anthropic charges 5x more for output tokens than input → 10,000 API calls/day at 150 tokens each = $8,212/year → With caveman compression = $2,847/year → Savings: $5,365/year per agent And here's the honest part most viral posts won't tell you: The 75% reduction only applies to isolated chat responses. In real coding sessions, independent benchmarks show 14-21% savings on output, and ~25% on total session tokens. Still meaningful. Still worth it. But not the headline number. The deeper insight? Chinese developers have had this advantage all along. Chinese has no articles, no verb conjugation, and each character carries more semantic weight. Chinese prompts naturally use 30-40% fewer tokens than English. Caveman mode is essentially porting the token-efficiency of Chinese into English. We spent billions training AI to be eloquent and polite. Now we're paying $15/million tokens for that politeness. The most sophisticated AI systems ever built — made to grunt through code reviews. That's the real story. Link to the repo and the research paper in comments. What's your take — does forcing brevity help or hurt AI reasoning?

• 
  Neo (@neodevils_) reported 37 minutes ago

  @codeblue87 @diabrowser Hey, A few weeks ago, I tried to refresh to view all of my PRs in tabs with new GitHub Pull Request preview. But it was not working. I know this is a beta feature in GitHub and they might publish it sooner. Will Dia work on that before it is late?

• 
  Crypto Scores Rating (@CryptoScoresCom) reported 38 minutes ago

  Did the team build before the money showed up? That's exactly what the "GitHub Before Crypto" metric tells you. It compares the first GitHub commit date to the token creation date. Positive number = code came first. Negative number = token came first. Ethereum: +589 days. Nearly two years of building with zero financial incentive. Solana: minus 63 days. Token launched before the repo even existed. Neither is an automatic verdict. But it tells you everything about priorities. CryptoScores just dropped a full tutorial breaking it down. Watch it now :

• 
  Morgan / JUUNI-P (@butchtendo) reported 39 minutes ago

  @WasThatZero I understand your concern but it's also important to note that just because there's something ai generated in the code with these that doesn't mean the original creator did it. All these are open-source and GitHub has had a big problem w AI spam lately

• 
  Alex Standiford (@AlexStandiford) reported 40 minutes ago

  @Iamkingsleyf The best advice I can offer about bug fixes is to set up a way to isolate each individual bug, and make sure those problems are being fixed individually. I push my projects into GitHub, and then have my AI agents work on bug fixes individually, and submit a pull request to fix them one at a time. This does require that you have *** (free) and a GitHub account (also free). You don't have to completely know how to use the system, you just need to be able to tell your AI to commit, push, and submit a pull request after fixing the bug. Learning some of the barebones basics of *** would help you just so you can understand how it all works. The reason why this is helpful is because it allows you to isolate each bug into its own little box so you can see exactly what AI is doing to fix that problem, and you can ask it to "fetch that pull request" so you can test and make sure that it works on your computer. This is important because it allows you to review each item individually to verify the problem was actually fixed in isolation, and it allows you to have more than one bugfix being worked on at a time without them conflicting with each-other.

• 
  Anthony Shew (@anthonysheww) reported 44 minutes ago

  @KareemMahlees @cramforce I’m not aware of any issues if that nature. Can you file a GitHub Issue with a reproduction?

• 
  Franz Hemmer (@franzhemmer) reported 48 minutes ago

  @burkeholland @github Anyone else getting this on first session request? Error: Execution failed: Error: 400 "checking third-party user token: bad request: Personal Access Tokens are not supported for this endpoint\n" (Request ID: E599:3D91FF:607E4C:690DC2:6A075036) I had copilot scrutinize that there is no trace of a PAT anywhere and that I'm authenticating correctly with OAuth. No issues in my account setup - all looks green and connected.

• 
  Alex Maximiano (@FARTURATECH) reported 51 minutes ago

  @enunomaduro Hi Nuno, the problem wasn't with Laravel, but with GitHub, which wasn't able to download the dependencies. Sorry.

• 
  Dewaldt Huysamen (@GodsBoy7777) reported 53 minutes ago

  @sickdotdev Getting insane and better results just on medium for all of the above categories. Weirdest is Opus 4.7 fails at basic school tasks help for kids and when I do code GPT 5.5 finds issues that are found in any case on github CI checks. If use codex CI passes more than 99%

• 
  AtomicNodes (@AtomicNodes) reported 54 minutes ago

  Hermes Agent vs OpenClaw on Local Qwen 3.6 35B We asked agents to scrape GitHub star history for both tools, find what caused the growth spikes, build a live dashboard in the browser. MacBook Pro M5 Max 64Gb. OpenClaw: 203k tokens, 12m 01s — wrote a bash script Hermes: 257k tokens, 33m 01s — wrote a SKILL.md OpenClaw: hit GitHub API, got truncated responses, paginated through contributors, pulled star-history JSON, found a security incident in OpenClaw's history, fetched SVGs, fixed broken HTML from trimming, rewrote it clean. Hermes: parallel tool calls across GitHub API, web search, and browser. Hit Google rate limit, auto-switched to DuckDuckGo. Fetched article contents, mapped viral moments, then built the dashboard. Both shipped a live dashboard with star growth charts and spike annotations

• 
  Adi (@wtfaditya_) reported 56 minutes ago

  @azwan_ Yes its down, They don’t want us to deploy anything on Friday, For global wellbeing 🫡 @github

• 
  Adibou (@Adibougre) reported 57 minutes ago

  @ShanuMathew93 "the older models that are no longer SOTA will get competed down as competition increases" Github didn't get the memo

• 
  Farhad zand (@farhad_pd) reported 58 minutes ago

  Hey @grok team, your GitHub connector is seriously broken. I ask it to make a change and push it to my repo. It confidently tells me “done,” but nothing is actually changed or pushed. It’s just falsely claiming the task was completed.

• 
  Alef Benson (@AlefBens) reported 59 minutes ago

  @_sirajuddeen_ @OfcMachete19 @iupdate I've been burnt too many times. Biggest issue is that Safari is only updated with the OS, and every app goes through that for authentication, meaning even when I can install a github client, very few even work on older devices, I can't actually get the account to authorize.