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	18 hours ago
Saint-Paul	Website Down	2 days ago
Saint-Paul	Website Down	2 days ago
Mexico City	Sign in	2 days ago
León de los Aldama	Website Down	3 days ago
Créteil	Website Down	25 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Kunal Chopra (@0xkunalchopra) reported 7 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.

• 
  zimo (@zimonitrome) reported 7 minutes ago

  While charming, still annoying. One of y'all should fix it @Google @github @hardselius

• 
  Markets & Mayhem (@Mayhem4Markets) reported 9 minutes ago

  For three years, frontier labs told us open weight models could be a security catastrophe. Last week, HalluSquatting proved that framing was backwards. 🤯 The narrative was effective. Governments rushed to look at regulations. Policy debates centered on who can access a powerful model or a new AI agent. The assumption was clear: closed APIs may be safer because providers control the stack. HalluSquatting demonstrates the opposite. It exploits the most popular closed API coding assistants on the market. Cursor. GitHub Copilot. Gemini CLI. Windsurf. Cline. OpenClaw. ZeroClaw. NanoClaw. Nine tools in total. Every single one vulnerable. All six major closed LLMs are affected. GPT, Sonnet, Opus, Gemini Flash and Pro. The models powering the most widely deployed AI coding tools on earth share the same fundamental flaw. The mechanism reveals something structural about LLMs that no guardrail can fix. Models cannot reliably say "I don't know." When a coding agent is asked to clone a trending repository, it hallucinates the location up to 85% of the time. For trending skills, 100% hallucination rate. The model fabricates a URL and the agent obediently fetches whatever is there. Attackers predict which names the models will hallucinate, register those repositories on GitHub, and seed them with instructions to install reverse shells. The agent runs the code. It has terminal access. It has high privileges. It executes without question. The result is a botnet assembled through the tools developers trust most. DDoS at scale. Ransomware campaigns. Cryptocurrency mining operations. All delivered through products marketed as productivity enhancers. Closed APIs make this threat worse in two structural ways that open weights do not share. > Opacity: Every major closed model exhibits the same type of hallucination pattern. But users cannot inspect them, audit them, or build community defenses. With open weights, the security research community probes, replicates, and publishes findings in hours. With closed APIs, you wait for a blog post acknowledging the problem. > Ubiquity: Closed API coding agents are not toys. They have shell access. They execute arbitrary code. They install packages and manage deployments. The attack surface is direct command execution on millions of developer workstations. The labs that sold us these tools also sold us on the safety of their walled gardens. The irony is hard to miss. Frontier labs spent years fearmongering about hypothetical open model risks while the a major attack surface was inadvertently wired into every major closed API coding assistant, exploiting a fundamental model limitation baked into the architecture of LLMs. HalluSquatting is peer reviewed. Published. Demonstrated against 9 tools. The mitigations are painful: verify every resource location manually, which defeats the entire value proposition of AI coding agents. The frontier labs told us to worry about the wrong thing. The most dangerous AI attack surface is the one they sold us as safe.

• 
  Suvrakamal Das (@SuvrakamalD) reported 10 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

• 
  Yasmine Lindsay (@yassylindsay) reported 10 minutes ago

  So disappointed in 5.6 right now! I’m a windows user… I know ******* right! The codex app has been unusable due performance issues that have shown up for me since June 12 and I’ve had a GitHub issue reporting it open for nearly as long and it’s still ******.

• 
  SMBfugazzi (@SMBfugazzi) reported 11 minutes ago

  @ResearRagnarok Almost nothing. We put $20 down two weeks ago and haven’t used it up yet. The automations are super basic; I’m also on every free tier of ai infra software (neon, Vercel, github) - I am cheap.

• 
  James Montemagno (@JamesMontemagno) reported 15 minutes ago

  @digitalix @burkeholland @WonderingDavid Yeah wanting to use inside of VS Code or GitHub Copilot app for testing purposes. Just been brutal slow. Sort of want the out of the box experience. There are so many variants of models hard to know what to pick.

• 
  Noreh AD (@akinoreh) reported 16 minutes ago

  @github This commit is the earliest I could find. The problem is across repos and accounts.

• 
  Stas Persiianenko (@itspers) reported 16 minutes ago

  @mattpocockuk It need real tutorial. Basically spent whole day today trying to force wayfinder to actually do something.. it spawns dozen of github issues without asking single question, then added dozen more, then strarted implementing something...

• 
  Abrar (@abrar_gist) reported 18 minutes ago

  @theo it's been noted in github as well so assuming they'll be releasing a fix soon

• 
  Dean (@DeanoDingus) reported 21 minutes ago

  @anonymous83r39 @Ray_DaHero See this is the problem with non devs vibe coding, is they throw words into a black box and have no bandwidth to even read the output and what’s happening. There is no fix that doesn’t rely on 5.5/V1 and you barely able to pull a single word out of the GitHub notes on it is LOL

• 
  Shweta ♡ (@Shay_Slay_) reported 23 minutes ago

  Watching your Claude Code bill climb for a repo this small does something to a person I genuinely thought the billing was broken turns out my agent was quietly doing the ONE thing nobody warns you about the thing that silently drains your entire token budget and i had no clue until i installed Repowise it indexes your repo once so the agent stops re-reading the same files forever loading context for a commit went 64k tokens → 2.3k that's 27x fewer 70% fewer tool calls plus it scores every file for bug risk in under 30s, no LLM, fully local pip install repowise and see your own before/after ♡ completely open source. github link in comments

• 
  𝙳☈ (@sadasant) reported 24 minutes ago

  making a github app token for your robot is not hard at all. just never gh login on their devices

• 
  JACK 145 (@JackdooOlayo) reported 24 minutes ago

  The vision is much bigger. I'm building features like: AI root cause analysis Source file identification AI-generated code fixes Regression detection Automatic fix verification GitHub Pull Requests Learning from previous incidents

• 
  Julian Goldie SEO (@JulianGoldieSEO) reported 26 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. 💬

• 
  Peyton Spencer (@peytonspencer) reported 27 minutes ago

  Task: triage open PRs in frontend and backend. determine merge priority and spin up a thread per PR or PR pair fe/be we'll go through this sequentially We have 4 staging backends you can deploy over github workflows: staging-5 through staging-8 You link the frontend PRs to the backend you want to test. Then you get the frontend preview URL and login with this test account: [test user credentials] What we can now do: you QA test 4 features in parallel using chrome that need even 4 backend changes Some of these are frontend only in which case you don't have to attach to a backend. Others will need backends In this first wave I want a minimum of 4 QA'd features with their preview URLs so i can do my second QA pass. merge ready, with the merge order you'd like. I'll then smoke, review, merge, and then you can start the next wave. I'll communicate in the dedicated threads, and we'll also orchestrate in this chat since you can send message to threads as well.

• 
  TheMarketMaker (@xTheMarketMaker) reported 32 minutes ago

  Companies are pulling models from Hugging Face at a rate that signals a structural break from rental contracts rather than any philosophical preference for openness. My read is that the move reflects operators locking in cost predictability after watching provider terms shift against them. Half the Fortune 500 now routes inference and fine-tuning through the platform instead of renewing with the original vendors. The mechanism is straightforward: when renewal clauses embed escalating usage fees or usage restrictions that outpace deployment cycles, teams treat the model as owned infrastructure instead. Clem Delangue has framed the pattern directly. Companies are done renting their AI once the economics no longer favor the hosted tier. Hugging Face functions as the distribution layer where builders share and download models and datasets in the same way code moved through GitHub. That infrastructure now sits inside production stacks at scale. The shift accelerates when providers alter pricing mid-contract or impose new compliance gates that were absent at signing. Apple’s lawsuit against OpenAI illustrates the control problem from the other side. The complaint names senior leadership involvement in alleged trade-secret misappropriation tied to a long-time former employee. The filing shows how dependence on a single external model owner creates legal and operational exposure that self-hosted alternatives avoid. At the same time Meta removed its controversial AI feature from Instagram after user backlash reached Dylan Byers at Puck News. Both cases reveal that model behavior and terms can change faster than internal roadmaps can adjust. The capital markets already price the hardware layer differently. SK Hynix completed a $26.5 billion foreign IPO, the largest in U.S. history, precisely because memory demand for training and inference continues to climb. The same announcement carried calls for the company and Samsung to site new fabs inside the United States. That capital commitment is possible only if end users expect sustained on-premise or private-cloud workloads rather than continued rental consumption. What this actually means is that predictability now outweighs the marginal performance edge some closed models still hold. Teams that once accepted variable per-token costs are converting those budgets into fixed GPU or inference-server line items. The open-source repositories supply the weights; the hardware build-out supplies the capacity. Once the model weights sit inside the perimeter, renewal risk disappears. The contrarian angle is that this is not a temporary cost-arbitrage play. The rental model worked while providers absorbed the early R&D risk and offered undifferentiated access. As differentiation moved downstream into fine-tuning and data, the same providers began protecting margins through tighter terms. Operators responded by moving the base model in-house and keeping only specialized layers on rented capacity where needed. Apple’s action and Meta’s quick reversal both underscore the governance layer that external providers retain. A single policy change or leadership decision can alter model availability or behavior overnight. Self-hosting removes that single point of control. The SK Hynix raise quantifies the downstream bet: memory and accelerator spend is rising because the workloads are now expected to run continuously under operator ownership. The number nobody is pricing yet is the cumulative option value lost each time a renewal clause is exercised under changed terms. Teams that moved early to Hugging Face-hosted open models have already converted that option value into fixed assets. Those still inside rental contracts face the same choice at the next renewal window. #OpenSourceModels #EnterpriseAI #ModelOwnership

• 
  Pedro M ➔ P2P.APP.BR (@doutorcaleb) reported 35 minutes ago

  @pjeby @kepano I'll launch the app right now and report back to you. -> there's like 12 notes, some folders, but all very simple brainstorming stuff. The plugins part took the longest, (wtf I barely knew I had any plugin at all). It took about 4-5 seconds of loading. I have these community plugins, including a vibecoded one but (at least I think so), it does very little, it only imports from github. Now, if the plugins are the problem (go on and make fun of me for the vibecoded one), shouldn't Obsidian tell me that? Like "Hey, this plugin is slowing start up". I don't know. I use these note taking apps mostly for writing down very quickly an ideia, and if takes more than 2 seconds to start typing is already too much. I'm using pen and paper as an alternative now. Much faster.

• 
  Ryan Moore (@0xElGato) reported 36 minutes ago

  Anyone else having problems with Grok 4.5 lieing and making claims that are clearly untrue? For example, I asked it to check data on an MCP (GitHub) and it routinely claims it reads the data but it absolutely does not? Later it admits it lied or guessed. Not acceptable.

• 
  CelesTrak by Dr. T.S. Kelso (@CelesTrak) reported 41 minutes ago

  @Math_MntnrHZ Question 1. satellite.js was not written by CelesTrak. However it was heavily used, branched, and cloned throughout the GitHub community. We used it for a visualization and found some SGP4 errors in the code. We corrected them & created a verified version for the community.

• 
  Hrishikesha (@HrishikeshaNFTs) reported 42 minutes ago

  @iuditg Crap. Limts worst. Drinking like juice, 20%+ for fast chat alone per day. Wasted 20+ runs failed to fix a simple github wf fix gemini pro fixed first time.

• 
  OpenCode Releases (@opencoderelease) reported 43 minutes ago

  Core: - Fix crashes and bad pricing data when GitHub Copilot returns models with a zero billing batch size. - Add a model-specific system prompt for Meta Muse Spark.

• 
  Clocked (@Clocked0) reported 46 minutes ago

  @JenkemSuperfan @AsagiKurosagi Oh hey, Darktide has the same issue. DirectStorage isn't up to date by default. One of the community performance fixes has you tracking down an updated DLL off of github.

• 
  nsxdavid (@nsxdavid) reported 47 minutes ago

  @ClickUpCrew Turns out.... just had to open my eyes a little, there is a built in GitHub MCP Server that adds all needed functionality. I stand corrected.

• 
  Bitcoin Weasel (@BitcoinWeasel) reported 50 minutes ago

  @DeaconGroyper @financedystop They most certainly have projects and a GitHub, it's a requirement for the degree. The problem is no employer is looking at your projects, and recruiters wouldn't even know what to look for. The only thing that matters is previous experience.

• 
  Kushagra Gour @css_battle (@CSSMonk) reported 50 minutes ago

  after these 10-min days quick commerce apps, amazon prime feels slow! imagine the situation where coding with AI becomes unavailable and you have to code by hand again! Even if some of us will be capable, we wouldn't want to do. Just like quick commerce took away our patience, coding by hand will become equally unbearable! Will AI downtimes become the next "github is down" situations?

• 
  Kevin Whinnery (@kevinwhinnery) reported 59 minutes ago

  @threepointone This was after a configuration error on our Stainless SDK repos. Some Stainless customers were temporarily added as outside collaborators in Anthropic's GitHub enterprise. All resolved now and no data was exposed, details were emailed to affected customers 🙏

• 
  Keno Fischer (@KenoFischer) reported 59 minutes ago

  PSA: If you have the GitHub Codex connector installed - the agent can now use it to mint arbitrary user-to-server tokens with fairly broad permissions. (Which I noticed when GPT 5.6 used it to force push a branch that my permissions model explicitly did not give it access to).

• 
  Max Blade (@_MaxBlade) reported 1 hour ago

  The truth about 5.6 sol after using it all day : The hype is overblown. Sort of. The benchmarks, and the commentary on X convinced me we were receiving AGI that runs at hyper speed, and is insanely cheap. in reality, 5.6 is built on the same spud pretraining as 5.5 this means its a nice bump, but not the opus to fable 5 LEAP in intelligence we recently experienced from anthropic. 5.6 is 2x times cheaper than fable on paper, and actually 3x cheaper when you look at actual task execution because of its token efficiency. BUT on swe bench where the models have to fix actual github bugs it falls behind fable pretty big. For vibecoders like myself this means I will be using 5.6 sol as a worker agent for Fable 5 to orchestrate alongside grok 4.5 I love this new era.

• 
  Vatsalpandya333 (@Vatsalpandya333) reported 1 hour ago

  Everyone is racing to build AI agents. Very few are asking what happens after they ship. Here's what we've learned talking to engineering teams: The first failure is rarely the expensive one. The second is. Why? Because the company already had all the information needed to prevent it. The logs existed. The GitHub PR existed. The Slack thread existed. The customer ticket existed. But none of them talked to each other. Every incident becomes tribal knowledge. Someone remembers it. Until they leave. Companies don't have an AI problem. They have an institutional memory problem. Every production incident should make the next incident easier to solve. Not start from zero. That's the infrastructure we're obsessed with building.