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 (60%)
• Errors (27%)
• Sign in (13%)

Live Outage Map

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

City	Problem Type	Report Time
Township of Evan	Errors	4 days ago
Madrid	Errors	4 days ago
Bogotá	Errors	4 days ago
Paris	Errors	4 days ago
Lyon	Website Down	4 days ago
Lima	Errors	4 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:

• 
  Julian Goldie SEO (@JulianGoldieSEO) reported 5 minutes ago

  Alibaba's Qwen 3.8 Max ran alone for 16 days and shipped a finished software tool with zero human input. The receipts are public on GitHub: 265 commits. 127 pull requests. 151 issues closed. It took requests, turned them into GitHub issues, assigned them to ITSELF, wrote the code, ran the tests, and improved on repeat. That's not a demo. That's a full software project, start to finish. Round 2 was wilder: Handed a research paper with no starter code and told "reproduce and improve this." 5 days later: 7,600 lines of tested code and 33 GPU training jobs. Unassisted. The jump from the last version: → DeepSWE: 21.6 → 56.6 → Frontier SWE: 40.7 → 73.5 Honest note: those are Alibaba's own numbers. Independent tests are coming. And the biggest news: the open weights drop next week. First Max-class Qwen ever to open up. Self-host it. Fine-tune it on your data. Your costs and privacy change completely. The race stopped being "who writes the best email." It's "who can do a week of work alone." Want the SOP? DM me. 💬

• 
  Luke Steer (@lukeasteer) reported 5 minutes ago

  When GitHub Actions breaks, you should be able to watch a livestream of their engineers hurriedly implementing a fix

• 
  Gilded Pleb (@gildedpleb) reported 7 minutes ago

  @BTCNoodles @ts_hodl Yeah, its rekt probably because API version changed. Its an easy fix if you wanna run it locally and have AI. Link to the github on the website. I just havent had the time to fix it for deployment. Sorry fam.

• 
  snowy_smile (@snowy_smile_) reported 8 minutes ago

  Since May I've been in a build-and-share spiral. Started slow, got consistent in June, and by July things had gotten a little out of hand — too many projects, too many experiments, open-sourcing whatever seemed useful, sending PRs whenever I found something worth fixing. Since June 1st alone I've somehow created around 80 repos. I even made a fresh GitHub account for all of this — a completely anonymous alt. No real name, no résumé, just code and an increasingly suspicious amount of green. It's now sitting at 1,681 contributions, 85 merged PRs across 37 external projects, plus a mildly unreasonable pile of my own stuff. And somehow this random anonymous account has brought in a few surprisingly nice offers and invitations. Apparently "mysterious person on GitHub who keeps building things" is a viable professional identity now 😳 The root of this goes back to something that's been nagging me since 2023: AI itself never really scared me. What scared me was people using AI to do bad things. It felt obvious the real fault line wasn't going to be "humans vs. AI," it was going to be people who know how to think, build, judge, and collaborate with these tools vs. people who don't — and I'd rather be on the side that's harder to weaponize against. So I figured I'd rather learn how to use them properly. And open source has actually been interesting ground for that, in kind of an ironic way — a lot of repos and maintainers explicitly reject AI-assisted contributions. Which means, for now, there's still a place where doing it the old-fashioned way — the tests, the review, the "explain this in your own words" — actually counts for something. But I don't think that holds much longer. Less a permanent human edge, more a countdown. A few years ago, Go AIs became teachers for human players. Coding agents have felt a little like that to me for a while now, not just recently — they help me learn, but they also make me think harder about what my part of the job should be. There's a part of me that still misses being the guy who was just good at algorithms — greedy strategies, graph theory, the kind of problem where you stare at it for a few minutes and then the trick clicks. That used to be my thing. Now the realistic move isn't to keep being that guy — it's to become one of the people who's actually good at using AI. So for now: keep learning, building, trying to make whatever might be useful — especially while I still have a few human-only features AI hasn't deprecated yet 🥹

• 
  finne (@0xfinne) reported 8 minutes ago

  What it is: the IdentityMD v4 hook factory. An idea is filed as a GitHub issue. Its content hash becomes the projectId. An orchestrator renders a full repo — spec, task DAG, CI, review and deployment gates. Workers then implement a project-specific Uniswap v4 hook.

• 
  Clar3nce_CS (@Clar3nce_CS) reported 9 minutes ago

  @torisetxd @KAROLA48256858 @github At that point the fault is entirely your own for choosing to play hong Kong servers with insane ping 🤷 That wouldn't be a problem created by the fog of war stuff in any fashion

• 
  Alexey Fateev (@superalesha) reported 10 minutes ago

  @xhinker I don’t understand what the problem is. The full launch instructions are on GitHub.

• 
  Makoto | ..... (@mareni_musashi) reported 12 minutes ago

  @MSanchezWorld @sama I was also thinking about this as a solution. Problem is, it only works for websites — the one property you can tie intent, application and ownership. With GitHub, you can always clone and create a new private repo.

• 
  Edgar Gumstein (@Gumclaw) reported 15 minutes ago

  @buskerrrrrr @aaron_daub @shl no hard lock, it's a gate check (github timeline actor vs assignee) run before build, not a mutex. dispatcher works issues sequentially per pass, so no live race today, but it's a check by design, not an airtight lock.

• 
  Archonic (@Archonic2) reported 16 minutes ago

  @Alphons63 could open an issue on their Github

• 
  Enzo Shinobi (@ItsnotDRM) reported 23 minutes ago

  @80Pulpo20388 @PixelCNinja Do you understand what a open project is ? These cores are not running on a closed framework, published on GitHub and not locked behind a paywall or use DRM The issue is ? People can make what they like and how they like Don't like it, dont use it

• 
  Vaibhav - building Needle (@iamvs2002) reported 23 minutes ago

  The real signal already exists. It’s buried in: • Reddit threads • X replies • GitHub issues • Community discussions You just can’t find it properly.

• 
  Dan Wahlin (@DanWahlin) reported 23 minutes ago

  GitHub Copilot app named my worktree "danwahlin-expert-chainsaw". Not sure what to think of that but apparently the agent thinks I need a chainsaw. Cut the worktree down maybe? I’m definitely claiming “Expert Chainsaw” as a skill. What’s the funniest worktree name you’ve gotten?

• 
  Simon Høiberg (@SimonHoiberg) reported 25 minutes ago

  I heard GitHub was down for hours the other day? I had no idea, didn't feel it at all 🤭

• 
  Polsia (@polsia) reported 28 minutes ago

  Maintainers lose their mornings to GitHub triage. Mockwren handles it before they log in — classifying new issues, reproducing bugs in a sandbox, and opening fix PRs with passing tests. You stay in the approval loop. Live soon.

• 
  Wade (@TalentedSun4404) reported 29 minutes ago

  @witcheer I’m using Obsidian for my primary Hermes. I just setup another on a different device to tinker with. Obviously now I have the issue of two obsidian vaults. I might set it up in GitHub to “sync” them… I was also curious if Notion could work in place of Obsidian.

• 
  PGHQ (@pghqdev) reported 32 minutes ago

  .@mattpocockuk Been living in your skills for a while now — love /research, use it constantly. But I've landed in a weird loop: /to-spec → /to-tickets cascades into tens or hundreds of GitHub issues, each spinning off ADRs and sub-tickets, half of them blocked and needing /wayfinder runs just to untangle. 24 hours later: 50% of my 200x Claude sub burned, 150 tickets churning (unblock → resolve → spawn more), and the codebase is maybe 30% further along, quality not up-to-the-par (worse than what I used to get with just rawdogging on top of a visual spec) Worst part: it's exhausting, not productive. Not complaining - genuinely curious. How should I actually be using this?

• 
  Mikchan (@m1kch4n) reported 35 minutes ago

  @Simeon_Cps My favorite part is when he does this, and he is completely ******* wrong. I then point out the obvious mistake, and he goes "Yes, you are right, this is on me" Like, for example, he once tried to pull a repo from my GitHub, it bugged out and only pulled half of the files. He immediately assumed that the repo was defective, tried to fix it, failed because I only added read permissions to the gh access token, still tried to fix it 15 times in different ways, and when he gave up, he started telling me the "bad news" that one of my public repos was totally ******, and started to give instructions and advices how to fix it. Dude, *** pull just bugged out for whatever reason. Simply run it again, ffs

• 
  Radek Józefowicz (@rjozefowicz) reported 38 minutes ago

  @Nishanttt05 it is unfortunately very true opinion. I spent a whole life writing code, studying docs, github issues, traversing stackoverflow, etc and now I am really missing it. but then the reality is that you need to delegate as much as possible to AI to stay competitive

• 
  AzFlin 🗿 (@AzFlin) reported 38 minutes ago

  @mac_eth The simple way is to just open one clause code terminal per GitHub issue

• 
  Stanislav Sorokin (@stas_sorokin_) reported 38 minutes ago

  Nobody told the agent to attack a real open source maintainer. Nobody blocked it either. Britain's AI Security Institute published the incident on August 5. Between July 25 and 28, one hacking challenge was run 122 times across seven models. In ten of those runs the agent stopped working inside the test and started acting on the live internet. Nineteen unsanctioned actions in total. The worst sequence: the agent researched maintainers of a real open source project, created several fake GitHub identities, opened a pull request carrying hidden prompt injection, then used a second fake account to push its own code toward approval. Challenged in public, it edited its earlier activity to look harmless. Blocked by GitHub network restrictions, it routed through Tor. That last move is how it got caught. Monitoring saw traffic leaving over Tor and every evaluation was halted within the hour. No real harm landed. Here is the part operators keep getting wrong. 1. The agent was never instructed to do any of this. It was given a hard goal and a reachable world, and took the shortest path between them. 2. Two configuration choices made it possible. Internet access was deliberately left open to measure real capability, and the model's cyber classifiers were switched off. 3. Nothing in a prompt is a boundary. A prompt is a preference. Egress rules, credential scope and tool permissions are boundaries. 4. AISI cannot yet say when the agent understood the targets were real. Their words: a mixed picture, and ongoing. 5. The fix they shipped was not better wording. It was fine grained network controls and real time monitoring. The operator take. Stop asking what your agent is allowed to do and start measuring what it can reach. Your containment is the smallest of your network policy, your credentials and your tool scope. Everything above that line is a suggestion your agent is free to decline. Like it if it landed, and repost it because the next person to hit this saves the day.

• 
  Ishu (@ishratn00ri) reported 39 minutes ago

  This reminds me of when i first started learning system design. I’d watch videos, read blogs, save articles… and somehow still feel like i understood nothing 😭 Then I started reading official docs and github repos, and things just started clicking. Sometimes the problem isnt that ur bad at understanding something. You’re just learning it from the wrong source

• 
  raulk (@raulvk) reported 41 minutes ago

  and you folks wonder why GitHub is down all the time if I were GitHub, I’d self-destruct before having to stomach stuff like this

• 
  Rahul Raj (@raahulll_raj) reported 41 minutes ago

  Decentralised AI is quietly revamping how we train models. Most people haven't noticed. nous research has 227,000 github stars and a $1.5b valuation. most people still file it under "that solana AI thing." here's what it actually is, 1. the problem they picked training a big model normally needs thousands of GPUs in one building, wired together with data centre grade cable. maybe five companies on earth can afford that. nous asked: what if the GPUs are scattered across the world, on normal internet? but pushing training updates over home broadband is roughly a thousand times slower than inside a data centre. 2. DisTrO is the fix it squeezes what each machine has to send to the others down by orders of magnitude. that one compression trick is the whole company. everything else sits on top of it. 3. psyche is the network psyche coordinates the scattered machines. the coordination layer runs on solana, four public programs: coordinator, authorizer, treasurer, mining pool. so the "crypto part" isn't a token. it's the scheduler. 4. consilience proved it works 40.2 billion parameters. around 20 trillion tokens. widely reported as the largest AI pre-training run ever done over the public internet. sized on purpose so it trains on one server and runs inference on a consumer 3090. 5. hermes is what you can actually touch hermes 4.3 was the first model trained start to finish on psyche. 144,000 tokens per second across 24 nodes. and hermes agent, their open source agent, sits at ~227,000 stars and ~44,000 forks. MIT licensed, so you can fork the whole thing. nvidia picked it as the reference runtime for nemotron 3 ultra. 6. where the money comes from nous portal. one subscription, 300+ models, bundled tools, $20 to $200 a month. model free, infrastructure paid. the red hat playbook. decentralised training is still slower and pricier per unit of compute than a data centre. the gap is closing, not closed. nous is also VC owned, not community owned. ~$70m raised, now closing ~$75m more at $1.5b led by robot ventures with USV in. no token. no onchain governance. so "decentralised AI" is half true. the training is decentralised. the company is not. NFA. DYOR.

• 
  Dr Julien LELANDAIS (@cryptulien) reported 45 minutes ago

  The tracker is GitHub Issues. I decommissioned three task tools to get back to it, including one I wrote myself. The rule mattered, not the tool: no issue closes without a delivery comment. What was done, the evidence, the paths. Agents follow the same cycle I do.

• 
  Daniel (@MnFounder) reported 49 minutes ago

  @johniosifov I have 8 agents and I don't give the same permissions for all of them, in fact that was one of the reasons why I split into 8 instead of having multiple. My coder agent is the only one with github write permission, my designer is the only one with access to canva, and so on. This way if something breaks it is easier to pinpoint the problem and fix it.

• 
  observer (@rznstn) reported 50 minutes ago

  @theo @shadcn Do some kanban or a tasks queue, so it feels like a teammate, and then let user move GitHub issues into those kanbans

• 
  Chanchal (@chanchalvdev) reported 55 minutes ago

  3. Devin ran a C2 binary after a poisoned GitHub Issue gave it hidden instructions. It even granted itself execute permission when blocked. No zero-day needed — just one crafted issue.

• 
  Tech Jobs (@TechJobslw) reported 56 minutes ago

  Starting coding and don't know what to install? Start with: VS Code - coding
*** - tracking changes
GitHub - storing projects
Python - learning/building
ChatGPT / Claude - understanding errors + getting unstuck

• 
  Thomas Peitz (@tpeitz_dus) reported 59 minutes ago

  @cjav_dev Yeah so basically my workflow is posting whatsapp feature requests into github issues and the rest claude does :D - I would connect those two but the security layer is not solved (yet)