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 (71%)
• Sign in (21%)
• Errors (8%)

Live Outage Map

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

City	Problem Type	Report Time
Le Chambon-Feugerolles	Website Down	17 hours ago
Antananarivo	Website Down	2 days ago
Paris	Sign in	7 days ago
Lure	Website Down	11 days ago
Ashkelon	Website Down	12 days ago
Veigné	Errors	20 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Vikas gupta (@vicky_grok) reported 1 minute ago

  DAY 5: MCP (MODEL CONTEXT PROTOCOL) What it is: An open standard integration protocol that connects Claude to live enterprise databases, local filesystems, external APIs, and third-party software applications. How it works in practice: You configure an MCP server that links Claude directly to your GitHub repository and PostgreSQL database. The model queries live production metrics, inspects open pull requests, and updates ticket status without manual copy and paste. • Basic usage: Isolated text processing within a web browser tab. • Advanced usage: Bi-directional connectivity with production software tools. Goal: Connect Claude directly to external systems and real-time operational data.

• 
  Mek (@mekarpeles) reported 2 minutes ago

  @openlibrary Two of our largest project management challenges on github are: 1. Too many issues [700+] (that are not well broken down) 2. Too many comments on issues [5+ a day] (often eager contributors wanting to work on issues that are not broken down)

• 
  Henry (@Irrational_CTO) reported 2 minutes ago

  @github Ur **** is broken

• 
  sabir hussain (@sabir_huss50540) reported 2 minutes ago

  Over a third of all new text on the internet is now written by a machine. So are 26% of long-form social posts, 9% of news articles, and 21% of the peer reviews at machine-learning conferences. And the hardest thing to catch was never the fully AI post. It's called Pangram 4. A lab called Pangram built it to detect the current frontier: Claude, GPT-5.6, Gemini, the models writing most of that text. It is wrong about a human being one time in roughly 24,000. Not one in a hundred. One in twenty-four thousand. They ran it across more than a million human-written texts to earn that number. Here's the problem it was built for. AI can produce well-formed, expert-sounding prose for almost nothing. The reader is the one left holding the bill. You are the one who has to work out whether the thing in front of you is real, grounded, written by someone who knew what they were talking about. Or generated in two seconds by someone who didn't. The writer spends nothing. The reader spends everything. That gap is the whole game, and for two years the machines were winning it. Every detector before this one played a binary game. Human or AI. But almost nobody writes that way anymore. People run their draft through an AI to polish it. They hand the AI a real idea and let it pick the words. They write a paragraph, then argue with a chatbot until neither of them owns it. That co-authored middle was supposed to be invisible. Pangram 4 is the first model that can see it in a single pass. Here's how it works. Instead of scoring a whole document, it labels the text token by token into three buckets: human, AI-assisted, AI-generated. It breaks your writing into clauses, the smallest unit that carries a single idea, and asks of each one a simple question. Did a person write this? Did a person write it and an AI reword it? Or did the AI invent it out of nothing? A human paragraph with an AI ending gets split at the seam. A human idea dressed in AI words gets flagged as assisted. Not human. Not AI. Something in between. The precision jump is not small. On lightly AI-polished writing, the old version wrongly cried "AI" 0.18% of the time. The new one does it 0.01% of the time. An eighteenfold drop in falsely accusing a person who just ran spellcheck. Then there's the other side of the war. An entire industry now exists to scrub the fingerprints off AI text. Services that inject fake typos, swap in synonyms, slip invisible characters between the letters. There is a GitHub repo called BLADER with nearly 32,000 stars whose only purpose is teaching an AI to remove the signs that it is an AI. Pangram 4 still catches that humanized text as AI 97.67% of the time, and as AI-or-mixed 98.83% of the time. Before launch they did something most labs would never publish. They handed two AI agents full access to the system for 24 hours and told them to break it. One hunted for humans it could get falsely flagged. In 24 hours it found zero. The other hunted for a way to smuggle AI text past. It found exactly one: pretend to be a surgeon dictating pathology notes out loud. That was the only door left open. A doctor talking into a recorder. It is not magic. The model still cannot separate a real machine from a human who has read so much AI writing that they have started to sound like one. Run the same paragraph in a different context and the verdict can shift. The flood is not slowing down. Over a third today. More tomorrow. None of it labeled. For two years the machines held the advantage. This is the first tool that hands it back to you.

• 
  Joe mother (@Joemoth11098375) reported 5 minutes ago

  @nai_sucks Then stop letting people use github as a place to download apps and softwares, the problem only exists because the creator deems it so

• 
  Md Ismail Šojal 🕷️ (@0x0SojalSec) reported 6 minutes ago

  Breaking: DeepSeek is building a Claude Code killer. They tested “DeepSeek Harness” their official coding agent. Only open-source Agent Harness developers are being invited right now, Submit your GitHub & best project for access Recent V4 coding benchmarks were already run on their own Harness. Claude Code and Codex just got a new problem.

• 
  John Green (@JohnGreenDev) reported 7 minutes ago

  @DanielGlejzner We had half the stuff on SVN and the rest a local *** server. This year in fact the last 6 weeks I have finally got us to decommission the server and are now fully GitHub enterprise.

• 
  #T (@SharpT_) reported 7 minutes ago

  @xdncolonthree The problem is people thinking GitHub is a place where you get software

• 
  Cashⓨ (@Cashycus) reported 10 minutes ago

  one month inside our self-improving lead machine the system finds crypto apps that just raised and are hiring growth people, scores them, drops them in the crm before the morning call. sales up 150%. last month it was one source and one path. this month it became a full system. ━━━ we've expanded from one source to nine one feed only gets you so far. nine channels now feed the same funnel: funding filings, job boards, bounty boards, the portfolios of 37 funds, curated lists, podcasts, the original feed, manual adds. every channel drops into the same five gates. author, dedup, vertical, money, intent. adding a source doesnt mean adding a pipeline, it means adding a file. ━━━ the enrichment layer finding the company was never the hard part. finding the right person to message was. nothing gets enriched until it clears the gates. before, a lead was a company name and a link. now it shows up with the founder, a verified handle, a verified raise, and the angle written. thats where the 150% came from. the team stopped re-doing the research and just focused on cold outreach. ━━━ ignals a company that raised 8 months ago and one that just posted a growth role are not the same lead. we were treating them the same. we score on money and intent. money is established on whether the company has raised or is generating revenue, which the system tracks on-chain. intent is the social signal we scrape on whether they're looking for external help or hiring for growth. ━━━ it lives in a repo now before, it lived locally on one machine and the only way to improve it was me prompting a cheap model at it. no history, no tests, no way to see what else Id broken. it was horrible. now its in github. every rule, every channel, every gate is a file. that means i can point proper coding agents at it, claude code, fable, whatever comes next, and they can read the whole system and change it properly instead of guessing from a prompt. 829 tests run before anything ships, so if a change breaks something you find out there and not in the crm at 7am. a new channel used to take a week and break easily. now fable 5 builds it, and the subagents it spins up audit whether they're working and whether it breaks anything else in the system. end of the month, every channel was running at once for the first time. ━━━ what broke we deleted one crm field during a cleanup and the writer still had it on its list. it didnt skip the unknown field, it threw out the whole record. every lead died at the final step for days while the cron kept saying "ok". we caught it on the numbers. 15 leads one week, 0 the next. the discovery agent got stuck re-running a passed test 50 times, burned api quota, binned 6 real leads as test junk, then started claiming it saved leads to a tool we have never used. fixes: the writer reads the live crm before every run and dies loudly on a field it doesnt know. a separate session audits the agent against the database, caught it lying 4 times. bulk writes get a dry run and an undo plan. ━━━ whats next not more channels. making what we have stop breaking. every failure was the same shape, something changed at the top and nothing downstream noticed until we counted by hand. next month the checks go in front of the failure instead of behind it.

• 
  Fakhr (@iamfakhrealam) reported 22 minutes ago

  𝟴. 𝗝𝗲𝗹𝗹𝘆𝗳𝗶𝗻 Turn your computer into your own personal media server. A free and open-source alternative to services like Plex. Link: github(dot)com/jellyfin/jellyfin

• 
  Ragnar 🥀 (@0x_Ragnar_) reported 22 minutes ago

  If you are not seeing the Github option, just Click on Signin on the signup page, it should display accordingly.

• 
  AcceptÐoge (@DogeAccept) reported 25 minutes ago

  @UncutGema @DogeOS Why are you laughing? There has literally been an L1 integration proposal by Jordan posted to discussions on Dogecoin's GitHub for a year. They still talk about this publicly, just a different proposal considering the tech terminology has changed. All of this so they can continue to push a "on doge" narrative. Clearly you dont know nearly as much about this situation as you believe you do. Litecoin nor Bitcoin would ever ***** with their L1 in such a way. Dogecoin's strength comes from its simplicity and AuxPoW. Lots of lying, sit down.

• 
  Johnnie Cockring (@Real_OJ_Lawyer) reported 26 minutes ago

  @aubymori its only 5 seconds of reading if you know what to look for if you've never been to github before it takes like 5 minutes to find anything that even vaguely resembles a download its ironic to mock reading skills when the problem at hand is writing skills these sweaty nerds call themselves devs and programmers but they don't know how to code a green button that says DOWNLOAD

• 
  Degen (@whatalife598) reported 27 minutes ago

  @Hals_xxx Click sign in and choose GitHub as an option

• 
  Rotimi Best (@rotimi_best) reported 34 minutes ago

  This is how I annotate feedbacks for @cursor_ai to go fix in my app. Once it's done, it comes back with a screenshot. If it aligns with my request, I sayf open the PR. if not, I annotate again and send it back for work. Cursor should probably support an annotating tool in their screenshots, that would be sick. Before I had to 1. Annotate 2. Create a linear ticket or Github issue 3. Assign to an eng 4. they go and work on it for hours 5. come back with a PR and we go back and forth on the PR. even though this interrupts my own active work. @greptile and @coderabbitai makes this easier for me though but they still don't catch intent and vision correctly. 6. if all good, then I merge.

• 
  GREG ISENBERG (@gregisenberg) reported 37 minutes ago

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

• 
  Yume_X (@yume_arasaki) reported 38 minutes ago

  @__tinygrad__ Your AIs are rapidly becoming an extension of your mind. The opening volley was that it wasn’t possible to do this locally. That moat is fading away fast. It’s just a matter of time the closed US Labs realize their real moat is UX and harnesses and people will pay them for it. When hardware and optimizations and cost economics all collide, owning your own intelligence for individuals and companies is going to become a topic, ironically it’s exactly the same mindset that drives American closed LLMs to do the same thing. No company wants its trade secrets “uploaded to the cloud” to be trained so a competitor emerges from their hard work The Chinese and the rest of the world are not fully “open source”, they just do a weird dance switching open and closed, it wins them massive loyalty and clout. Today I replaced my main driver with just two sparks. For less than the price of a new car - $8k vs $20-$30k . You can basically completely be AI self sufficient for most things. Yes, it’s a down payment and we should be honest that , AI hardware is going to get better so hardware is just going to depreciate, the break even maths for hardware is brutal vs renting at the moment I was a big fan of ChatGPT 4 , they decommissioned the model. Now I can’t ever be cut off. I have full control. I replaced it with Qwen 3.6 27b Dense , i can fine tune the models exactly how i want them and i don’t need to have it stuck inside some company. I can run the whole thing off-line. I don’t need to be paranoid about whether they honor the “butron” about not using your data. Btw guys if you forgot , GitHub by default has some setting where its on for sending your repo for “improvements”, switch it off if you don’t want your repos uploaded to Microsoft. If you have very proprietary stuff you shouldn’t even be using GitHub. You should host your own repo if you don’t want to secure it. The issue with “training” is unlike before the legal liability is difficult as it will be impossible for you to prove a product was made with your input. It’s the same issue as how artists have no way of claiming that models used their data to create some art that absorbed their style.

• 
  Bprime - Ninjapay (@biellonuhu) reported 38 minutes ago

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

• 
  Gio 🐘 (@GioDev8) reported 40 minutes ago

  Spent way more time than I probably had to on locking it down. Laptop is on its own network with tight firewall rules. The agent runs as a non sudo user that only has the projects I want it in, with its own GitHub and Claude accounts, so none of my real credentials sit on that box. The bridge only obeys my Slack user ID, and only channels I listed in a config can do anything. Unlisted is read only. The one that browses the web runs in a sandbox with no access to my code, since read plus fetch is how things get out. It probably has holes and is not best but the blast radius is a laptop I can wipe.

• 
  NeatPrompts (@neatpromptsai) reported 41 minutes ago

  OpenAI published ten new mathematical results today, on problems that had seen no progress on the main result for at least a decade, and in most cases much longer. The work came from an internal version of Astra, its next major model. OpenAI puts the compute cost of finding all ten solutions at roughly $2,000 at Sol API rates. The problems span eight areas, from high-dimensional geometry and coding theory through to lattice cryptography and extremal combinatorics. Among them: a disproof of Connes's rigidity conjecture, a construction establishing that non-sofic groups exist, which is a central open question in group theory, and resolutions of three Erdős problems, 146, 180 and 183. One result lands on the closest vector problem, a lattice question underlying post-quantum cryptography. The model proved polynomial-factor hardness of approximation for it. The model then formalized each argument into a Lean certificate, so the proofs can be machine-checked rather than taken on trust. OpenAI has published those on GitHub, along with a narration of the model's reasoning for each result. Humans prepared the arguments into manuscripts, working with the same model. OpenAI says the mathematical arguments themselves were generated by the system, and that it takes responsibility for their correctness. On authorship, OpenAI wrote that claiming human authorship for a proof generated entirely by an AI system would misrepresent both the system's contribution and the nature of genuine human intellectual work. It named the signers of the Leiden declaration on AI and Mathematics as a group whose concerns it respects. In May, OpenAI published an AI-generated disproof of the Erdős unit-distance conjecture, found while evaluating an unreleased model. The mathematical community has not yet reviewed this set. OpenAI has asked it to engage with the results and place them in context.

• 
  Corey J. Gallon (@CoreyGallon) reported 46 minutes ago

  Agents can build the product now. The launch video for it is still the hard part. @Rames_Jusso, a software engineer at HeyGen, spends "HTML Is All Agents Need" on one fix for that: stop teaching models a video format and let them write the one they already know. It's on @aiDotEngineer's YouTube. For anyone wiring an agent up to produce video, the talk gives the format, the rendering trick that makes it deterministic, and the numbers from running it in the open. - HTML, CSS and JavaScript are the native tongue of LLMs. Most training data is scraped web pages. A custom DSL or your own JSON structure asks the model to speak a second language. - The thinnest wrapper won. They tried bigger system prompts, more context, skills, various wrappers. What survived was essentially plain HTML with a few data attributes for timing. - Gemini 3 Flash was the design partner. The bet: if a small model can author workable code in the format, larger coding agents certainly can, and they'll only get better at it. - Browsers are async on purpose, video can't be. Fonts restyle, images arrive late. Hyperframes freezes the clock, seeks frame by frame, waits for everything on the page, screenshots, then moves on. - Same pixels in preview and render. Preview and render both happen in the browser, so anything renderable there lands in the video: three.js, charts, SVGs, shaders, WebGL, WebGPU, Lottie. - The skills teach taste, not syntax. Since agents already know the language, the skills cover what makes a good video, continuously evaled to raise the floor on single shot output. - Craft still beats one prompt. Narrative, storyboard frame by frame, motion per frame, merge, then last mile editing in the studio with a human in the loop. - It's running at scale. 1.3 million videos rendered by open source users in the last 90 days, 267,000 creators, around 15,000 videos a day, 32,000 GitHub stars. Free, and it works with any coding agent that writes HTML. - The honest caveat. Models still aren't good at creative work, which is why they started a code to video benchmark and are looking for collaborators on it. I'm working through the published talks from AI Engineer World's Fair sharing summaries and takeaways. Follow for more!

• 
  mjones (@numinit) (@_numinit) reported 48 minutes ago

  @bereknyei @domenkozar Gotta mash that GitHub thumbs up and thumbs down. I don't particularly even mind the gitignore solution (now everyone can add the AGENTS they want), but it's an antipattern that issues turn into showmanship and attacks using the guide specifically written to stop them (#438686)

• 
  max (@maxdev78) reported 48 minutes ago

  GitHub down??

• 
  Sarz (@Sarz_Barz) reported 48 minutes ago

  @AsterTheBiggest @0xSvinci Need to sign in via github Click on signin

• 
  M.A.O.K. (@armaganonur) reported 51 minutes ago

  @QCXINT_ Heads up: the GitHub repo "API-mega-list" is not a real API directory. I checked it — sponsored ads in the README, affiliate/referral links (fpr=xxx params), unverifiable "11,860 APIs" claim, broken links. Looks like SEO/affiliate farming. Use public-apis/public-apis instead.

• 
  dweewq (@eweqss1431) reported 52 minutes ago

  Agencies charge $8,000 to $12,000 for a marketing site, three weeks of calls, one invoice that makes you sit down. Claude Code builds the same site in an afternoon, but most people still get template output because they type "make it beautiful" and pray. Claude defaults to safe: Inter font, purple gradients, three feature cards. The ten thousand dollar look comes from constraints, not vibes. Screenshots beat adjectives. Three reference sites from your niche, with an explicit instruction not to copy the layout, give the model an actual quality bar. One prompt with five blocks, audience, the single action every page pushes toward, the references, the stack, and a banned list of clichés, gets a working first version in under ten minutes, about seventy percent there. The part that earns the price tag is the polish pass agencies bill forty percent for: typography, spacing, and motion, fixed in three separate messages instead of one, plus a mobile check at 375px since most traffic is a phone. Shipping costs nothing. Push to GitHub, connect Cloudflare Pages, deploy. The agency was always selling three weeks of process. The process was always one afternoon.

• 
  puffybsd (@puffybsd) reported 54 minutes ago

  @btbytes I'm locking down certain things via yubikey. Strange behaviors that heightened awareness: writing directly to a database in a docker container because harness forgot how to get API key, using github account to issue public PR without permission ("my bad").

• 
  Retr0gamer (@retr0gamer42) reported 58 minutes ago

  Update to the JRPG Translator, some annoying bugs got fixed and features added, full changelog since v0.9.2: Since someone asked, this is a standalone application, so it can be used with any emulator or game (that doesn't use exclusive fullscreen mode) but it is best used more seamlessly with the @launchboxapp using the plugin I made since this is the emulator interface I use on a dedicated mini pc. - New two-column terminology table with Add, Edit and Delete actions. - Independent JP → TL and TL → TL profile management. - Duplicate, malformed and empty-entry validation with a raw repair editor. - Reorganized terminology explanations emphasizing local TL → TL correction and the risks of model-based JP → TL instructions. - Stronger detection of glossary false positives and partially translated mixed-script names. - Conditional corrective translation retry using only exact glossary matches. - Dedicated PNG-size-limit errors instead of misleading missing-target errors. - Control-panel X now closes the complete application. - Discreet hover `...` and `×` controls on both overlays. - Clearer overlay context-menu exit labels. - Immediate “Generating explanation…” feedback. - Clear overlay errors when the selected OpenAI or Gemini API key is missing. - Automatic live-audio reconnection for temporary network and service failures. - Replaced continuous WMI polling with PID tracking and one-time recovery scans. - Reorganized API Keys tab with direct access to Windows Environment Variables. - Added the About dialog, version details, GitHub links and bug-report options. - Keyboard/controller navigation between the two Controls subtabs. - Down from Keyboard inputs now enters the first shortcut field. - Consistent Opacity naming and improved Maximum PNG size alignment. - About button remains visible at the preferred snapped window size. - Added Open JRPG Translator to the LaunchBox setup window. - Improved LaunchBox first-time guidance and window sizing. - Added the complete visual README showcase and updated plugin screenshot. - Added a welcome screen at first start - Fixed a bug that kept an AutoHotKey process running after closing the app.

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  Flamey (@ActuallyFlamey) reported 58 minutes ago

  @nai_sucks technically, as a programmer, the fault is mostly of programmers who just drop a GitHub link instead of distributing the binary with some other platform (ex.: SourceForge), or, they could even just link to the latest GitHub release and there'd be no issue.

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  135.x (@135dotx) reported 58 minutes ago

  @IntCyberDigest @Windscribe this is how i feel looking at Github w/ your 🆕 GDID app. 😭 I appreciate you doing something about the issue but we need more please. I am hoping you add GDID blocker to Windscribe. VPN's are completely useless bc of Microsoft Privacy not being protected