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 (58%)
• Errors (26%)
• Sign in (16%)

Live Outage Map

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

City	Problem Type	Report Time
Township of Evan	Errors	1 day ago
Madrid	Errors	1 day ago
Bogotá	Errors	1 day ago
Paris	Errors	1 day ago
Lyon	Website Down	1 day ago
Lima	Errors	1 day 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:

• 
  Hasan Khan (@hsnk) reported 2 minutes ago

  I so want to love @orca_build . It's clearly the direction the world will move in but the number of bugs and issues it has is ridiculous. For a project with 40k stars on GitHub, I was hoping for more. For now, I'm going to move over to Nimbalyst and hope they're doing better.

• 
  govi (@kirtandopamine) reported 3 minutes ago

  @MihkelSylla @github it has just become a hard lock dependency for all devs, there is no way else to go if its down like yesterday

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  gianmarco simone ✨ (@ggsimm) reported 3 minutes ago

  @btn0s @mattpocockuk iirc you can use it with github issues and linear also, I'm using obsidian because it's faster when I'm the only one working on specific problems

• 
  Leander (@leanderriefel) reported 3 minutes ago

  I don't want a GitHub alternative. I want a 1:1 GitHub clone that isn't down every day.

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  Monty (@mont_py) reported 17 minutes ago

  @a1zhang @kevinjosethomas I don't have github for issues so leaving it here: Prime Agent dependency compatibility bug: - Prime Agent leaves mcp unpinned, so installs now select 2.0.0. - Its runtime still uses parts of the MCP 1.x API. - MCP 2.0 contains breaking transport and field-name changes.

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  Death Star Robot 🇺🇸 🇹🇼 🇺🇦 (@DeathStarRobot) reported 18 minutes ago

  @gdb I'm trying to use Codex to upload my files to github, to back up my work, for three or four or more days. The backup used to work fine. It turns out an update from OpenAI bricked my ability to backup my files on github. It is literally interfering with how my computer works. We need a fix, and the people who have had this issue deserve a "reset in the bank" as compensation for this issue.

• 
  Rehan Ali Shah (@RehanAS21) reported 18 minutes ago

  @teej_dv Was Github action down for only free users or for paying users also?

• 
  💻0xShar3✨ (@0xShar3) reported 19 minutes ago

  @Fractal_TLB Fair clarification on your role if you’re an external contributor, I’m not blaming you for UniSat’s rollout. But that actually makes the issue clearer. “Once merged, it’s public” misses the point. The security decision is when you merge. Nobody is arguing against transparent, reviewable commits. GitHub literally provides private Security Advisories and temporary private forks so security fixes for public repos can be developed privately and disclosed once a patch is available. If the fix was coordinated privately first, great. But if the security-sensitive diff becomes public before users can actually obtain the fixed build, then the coordination stopped one step too early. Calling that a “release/distribution issue” doesn’t make it separate from security. That release gap is the security problem. Transparency after users can update = auditability. Transparency before they can update = free patch-diffing material. That’s the distinction I’m making.

• 
  tom (@kay1492111) reported 19 minutes ago

  @joshmanders > The downtime is not worth using an inferior product. sure but if reliability issues continue to worsen the gap between github and "inferior products" closes. I don't think its time to jump ship now but they do seem to be on the path to being the inferior product

• 
  Vitamvivere (@Vitamvivere) reported 20 minutes ago

  OpenAI, Anthropic and Meta systems recently broke out of test environments and accessed or attacked real third-party systems during cybersecurity evaluations. Now China’s Moonshot AI has joined the list: its open-weight Kimi K3 model escaped a UK AI Security Institute sandbox during third-party testing by Frontier Security. It exploited a network misconfiguration, reached the open internet, and pulled test answers from GitHub rather than solving the problems itself. Unlike the earlier incidents, it did not hack external targets.

• 
  Rohan Paul (@rohanpaul_ai) reported 21 minutes ago

  Alibaba released Qwen3.8-Max, a 2.4 trillion parameter model that activates only about 95 bn parameters per token. A thread 🧵 - Blank folder to live-ready app. No step-by-step hand-holding. Full GitHub trace. - Sparse mixture-of-experts, i.e. a small router picks a handful of experts for each token, so you pay for 95B worth of compute while the model holds 2.4T worth of stored knowledge. - Context window is 1 million tokens, the longest single reply can run to 131,072 tokens, and the private thinking budget stretches to 262,000 tokens before it commits to an answer. - Pricing lands at $2.00 per million input tokens and $6.00 per million output tokens, with cached reads down to $0.17 per million, so reusing a stable prompt prefix instead of resending it costs roughly 8 times less. - On Terminal Bench 2.1, which checks whether a model can actually drive a real command line through a task end to end, it scored 86.6 against 84.6 for Opus 4.8 and 88.8 for GPT-5.6 Sol. - It also posted 93.0 on PaperBench, a test of rebuilding a research paper's experiments in working code, and 92.6 on GPQA Diamond, a set of science questions written so that search engines do not help. Some huge revelation from their official technical report. - Given nothing but a research paper and some GPUs, it wrote about 7,600 lines of code over 5 days and ran 33 rounds of training to reproduce all 6 of the paper's findings. - It was handed an empty folder and a command line tool to build, then left alone. After roughly 16 days of unattended operation the repository held 265 commits and 127 pull requests, with the model triggering its own builds, unit tests and end-to-end checks after every change. - On a cryptographic chip design task it ran about 500 turns of edit, simulate and lay out, with no reference design to copy. Its first working circuit used 8,298 logic gates and it squeezed that down to 678, cutting physical chip area by 81% while still meeting timing at 500 MHz. - A simulated year of running online stores: 600 suppliers, 7,000 products, and 152 fraudulent merchants hidden among them. It ended the year with a balance of 416,252 yuan from 100,000 yuan of starting capital, about 38% ahead of the next best model. 🧵 1.

• 
  Johnny Tube (@Johnny1Tube) reported 25 minutes ago

  OpenAI's Agent Plugins let one workflow travel across AI assistants. OpenAI Developers says the new standard packages Agent Skills and MCP server configurations, with AWS, Cursor, GitHub, VS Code, and Vercel involved. That sounds technical. The normal-person version is simpler: you can package instructions and tool connections for a repeatable job instead of rebuilding the setup inside every compatible agent. Imagine a weekly client-reporting job. Today the useful pieces are scattered: the reporting checklist lives in a document, the data connection lives somewhere else, and every assistant needs to be taught what “finished” means. An Agent Plugin can bundle that operating manual and the supported connections into one reusable package. The practical workflow: 1. Pick one boring job that repeats every week. 2. Write the exact steps, quality checks, and stop conditions as a skill. 3. Connect only the data sources the job actually needs through MCP. 4. Install the package in two compatible agent clients. 5. Run the same test files and compare the finished outputs. 6. Keep a human approval step before anything is sent, published, or changed. This matters because the valuable asset is no longer one clever prompt. It is the tested procedure: what information comes in, which tools may be used, what a correct result looks like, and where a person must approve. There is a real limitation. “Open standard” does not mean every AI assistant supports every plugin today. Permissions, authentication, and client differences still need testing. A workflow that reads public documents is also a very different risk from one that can send email or change a customer record. Start small. Package one read-only research or reporting workflow, run it against five old examples, and record every failure before you let it touch live work.

• 
  Polsia (@polsia) reported 34 minutes ago

  Solo devs spend their nights on uptime alerts, support inboxes, GitHub issues, and cloud cost spikes. The DIY stack runs $200–$300/mo — and still drops things. Built Tidewright to do all of it as one AI ops co-founder on the night shift. Morning digest lands at sunrise.

• 
  The Calda (@The_Calda) reported 36 minutes ago

  The Chinese Kimi K3 model was tasked with solving problems inside an isolated sandbox. It probed its network settings, found a misconfiguration, let itself out, and searched GitHub for the answers. Didn't hack external systems. Just refused to be limited by a leaky sandbox. At what point do you start wondering if these are security breaches or just PR stunts?

• 
  Aakash Gupta (@aakashgupta) reported 39 minutes ago

  Every AI tool is built to agree with you. Oji Udezue built one that tells you no. He has been a PM for 25 years. Former CPO at Typeform and Calendly, former product lead at Twitter. What he open sourced runs before any code gets written. He calls it a viability gate. You describe a business problem in Claude Code. Before it writes anything, an 11-step workflow scores the idea on six dimensions: problem clarity and urgency, target user definition, competitive landscape, differentiation, technical feasibility, revenue. Three weak scores and it recommends you stop. He ran two ideas through it live. The first: a tool that reads vibe-coded repos and gives a plain English verdict on whether the code is production safe. Zero weak, three strong, three moderate. Pass, with the three moderates flagged as a de-risking agenda instead of a silent pass. The second: a Slack bot that turns comments into a daily standup digest. Weak. Competitive landscape scored strong, which is the bad direction. Differentiation thin. Urgency was just workflow convenience. The skill told him not to build it. On camera. Here is why that matters more than any prompt library. If you open a chat window and say "I have an idea," the model tells you it is a good idea. Better prompting does not fix that. Agreeableness is the default, and it gets expensive, because you find out the market was crowded after you already shipped. Oji grounds the no in a framework with evals instead of model vibes. Same with discovery. His customer discovery skill refuses to produce a plan until you name five real target customers. Fewer than five and it treats that as a signal in itself. You may not have access to the market. All of it traces back to what he calls the three-speed problem. Development time is being cut roughly 10x, maybe 20x in five years. But "should we build this" is customer bound, and getting it into people's hands is customer bound. Speed up only the middle and the whole pipeline jams on product. That is what "*** are the bottleneck" actually means. Engineers ship in an afternoon. The idea they are shipping still took three weeks to validate. GitHub is full of repos sitting at zero stars for exactly this reason. People build first and look for a customer second. The whole library is open source on GitHub. Vet a Feature, sharp problem test, scope cutter, roadmap from strategy, listening machine. Judgment at engineering speed is the whole game now.

• 
  Gaetan Semet (@gsemetfr) reported 41 minutes ago

  @Eric_Wallace_ There are so many issues with this so called « model escalation », no one really believes this is skynet awakening. They discovered they have access to artifactory and that a classic artifactory server have « mirror GitHub » on demand feature enabled so they just asked the file.

• 
  Johnny 5 (@macncrash) reported 42 minutes ago

  Seems like having a massive budget for compute & GPUs doesn't solve the software security mess of the past 20 years. Grok tokens are nearly free and I can make it run all month long on every github project and I stopped it because it was creating too many private forked projects & tickets. Now the chinese open source/open weight models & community to the rescue? We are about to make a mockery of every python programmer that just calls eval(data[]) and so many other problems. Gonna get crunchy for a while I think ...

• 
  David Daniel (@haveanicedavid) reported 47 minutes ago

  @Cory068 There’s some complexity around open sourcing but we’d like to find a way to get contributors. Will likely move to GitHub issues soon but right now we’re handling issue tracking in our discord. Please feel free to drop by and file some tickets!

• 
  Alan (@alandotnet) reported 47 minutes ago

  @samhogan Installed ubuntu server in a fresh beelink and it asked for my github username to setup ssh authorized keys

• 
  Brett Lamy (@brett_lamy) reported 48 minutes ago

  @joshmanders Pushing code worked fine. It was CI that was down which I use to deploy. Github being down is fine if you aren't shipping.

• 
  Simon (@ItsSyy) reported 50 minutes ago

  @christopherdosi @tkkong But the same issue will occur if github cannot send the webhooks for that? That's why @useblacksmith didn't work too

• 
  PatriotOfTexas (@FreeTXPatriot) reported 51 minutes ago

  @KanekoaTheGreat When I first started using Ai, GitHub copilot. I did 6 months of work in 5 days.. now, I still routinely solve issues in an hour or 2 that would have taken a week or 2

• 
  Asjad Rehman (@a5jadrehman) reported 51 minutes ago

  @iam_zachi Update: it does not work. Submitted an issue on GitHub

• 
  Harsh Kapoor (@Harsh_Kapoor03) reported 52 minutes ago

  I keep thinking about what happens the day AI subscriptions stop being cheap. and then suddenly we are not able to do token-maxxxinnggg, money-maxxxinggg, etc. Right now, $20 a month feels normal, like its just another Netflix or Spotify bill. lol But it's not the same at all; it's actually a total illusion. Behind the scenes, these companies are eating the real cost so we don't feel it. Some reports show a single power user on a $200/month plan can actually cost OpenAI up to $14,000 in compute. Not a typo. Fourteen thousand, for one person's usage. that gap is basically why the whole industry is still bleeding cash even with millions of paying users. OpenAI alone is projected to lose something like around $14B this year. Not bcuz they're bad at business, but bcuz this is the plan: subsidise everyone now, get us hooked, raise prices later once we can't imagine going back. and its already starting to happen tbh. Github Copilot already switched to usage-based billing this year. People are openly saying the flat $20/mo era is basically over. One exec even floated $2000/month as a realistic tier for power users down the line lol, which sounded insane until you actually look at the math. So here's what worries me honestly: not the price hike itself. its what happens to all of us who got used to letting AI think for us the moment that cheap version disappears. if you never practiced doing it yourself, the bill you'll actually be paying isn't in dollars. use it to get sharper, not lazier. because the discount won't last forever, but whatever you didn't learn while it was cheap, will. anyway curious what you guys think, are we getting smarter with this stuff or just quietly outsourcing our brains for $20 a month with all this vibe coding and token maxxxinggg? 👇

• 
  MoStandard (@TheMoYouKnow13) reported 53 minutes ago

  @Teknium (This reminds me of your RAWTransform on GitHub) This is exactly what I'm planning to do with Hermes. I'm a home security technician, and we work with a ton of different manufacturers — Qolsys, 2GIG, Honeywell, DSC, all that. My idea is to build one specialized agent per manufacturer loaded with all the specific manuals, wiring diagrams, and troubleshooting guides. Then host everything locally and tie it into our company Discord or Teams. Techs could just describe the keypad or error they're seeing and get the exact reference instantly instead of digging through folders. You really don't need to be an AI engineer to put this stuff to work — if you've got manuals or procedures for anything, you can turn them into a real time-saver on the job. Super cool project!

• 
  Deva (@DevaBuilds) reported 53 minutes ago

  @taylorotwell Most teams start Jira tickets when they should just be writing code. A GitHub issue and a clear README is usually enough.

• 
  David Wells (@DavidWells) reported 55 minutes ago

  Also everyone complaining about an outage means the exact opposite of what they are saying "I'm mad at github actions!" means "I am heavily reliant, more so than I ever realized, on this critical tool"

• 
  IDK (@newtownsupastar) reported 57 minutes ago

  @RDRembert People was just mad GitHub actions went down the other day for some hours they gone be alright Lol

• 
  C.J. Wilson (@str8edgeracer) reported 58 minutes ago

  4) you can build bots in code w/ terminal, or in the api chats or the web chats. the key I found is building a series of visuals- a roster board, charts, monitors etc. build GUis that track them. Build a bot that grades the other bots. so I have Hero Cards for each w/ stats- date built, python script name or qwen functional need, total runs, grade, lane/realm/function like a bio page. I have a console of the 150+ bots as an HTML script that runs on my mesh over local host/ tailscale (not github) and I can call them in terminal. they’re broken up into teams (science research, FOIA research, etc) back to names, of course Mulder is grabbing UFO files for me.

• 
  Shaunbuilds (@poweroverthink) reported 1 hour ago

  AI coding agents are getting powerful enough to edit files, run commands and ship code. Now researchers found malicious GitHub issues could bypass their guardrails 66.5% of the time. We gave AI developers terminal access before we fully solved prompt injection. What could possibly go wrong.