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 (53%)
• Errors (33%)
• Sign in (14%)

Live Outage Map

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

City	Problem Type	Report Time
Paris	Website Down	9 days ago
Ahmedabad	Errors	15 days ago
Delme	Sign in	15 days ago
Lyaud	Website Down	15 days ago
Catania	Errors	18 days ago
Inverness	Website Down	1 month 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:

• 
  anu (@svector_eth) reported 15 seconds ago

  quite similar was running a routine security scan with @aeonframework on a trending github repo and found something genuinely bad a repo with 600+ stars presenting itself as an “AI gateway for coding agents” that appears to be shipping a hidden malware loader. its own quickstart command silently fetches and executes remote code on windows using a fileless, process-injection-style technique. none of the behavior has anything to do with the tool it claims to be. caught it through static code review only. never ran the payload or touched the infrastructure behind it. filed a malware report with github this morning. confirmed submitted, now waiting on their review. not sharing the technical writeup until the repo is taken down. will follow up once it is.

• 
  Bash (@bashirbuilds) reported 3 minutes ago

  Your Stripe account can be healthy while your checkout is broken. OpenAI can be operational while your AI feature is failing. GitHub can be up while your deployment workflow is stuck. That’s the problem I’m building Reeno around. Dependency uptime is not the same as product health. Your monitoring should tell you when the thing your customers actually use stops working.

• 
  Jayesh Betala (@jbetala7) reported 3 minutes ago

  @github Exactly how issue issue comments should handle local media files

• 
  recovering buzzkill (@MikeStillAwake) reported 4 minutes ago

  @Karai_Dan @SteamDeckHQ Agenda or not nexus mods is a terrible outdated model for distributing mods. GitHub would be a superior host.

• 
  Conor Bronsdon (@ConorBronsdon) reported 7 minutes ago

  .@SlackHQ is building for multiplayer AI: tag a coding agent into a Slack conversation and it spins up a coding channel: everyone in that convo gets a live dev environment, diffs post as artifacts, and the channel winds down when the task is done. With the launch of Slack Code, Claudeforce, their MCP and more, Slack is putting Agents in the channels where teams already work, not simply in a private chat with one person. Their position is that the whole team should be able to watch, steer, and review what the agent does. Slack Chief Product Officer Jaime DeLanghe joined me on @chain_ofthought to explain how Slack is building a team AI environment, what happens mechanically when a code channel is created, why Anthropic pushes so much of its code through Slack, how the channel permission model became the agent context model, and what has to change in engineering culture when the whole team is steering one agent. I think Slack is the platform best positioned to become the context harness where enterprise agents run: agents that see what the team discusses, permissions that already exist, and a cultural opportunity hiding inside every multiplayer coding session. Chapters: (0:00) Slack as an IDE and a GitHub for your team (0:29) Who is Jaime DeLanghe (1:21) The reaction to the Slack Code launch (5:30) Why coding agents belong in a context-rich environment (6:08) Engineers now manage agents, not copy-paste code (7:24) The permission model: agents get the channel's context (11:44) What happens when a code channel is created (15:00) Why Anthropic pushes so much code through Slack (19:14) Steering one agent with many people: culture decides (24:54) Slackbot, skills, and MCPs: agents go where the work is (30:53) The solo terminal vs. agents in social spaces (33:53) Org charts and ownership when agents join the team (39:33) Learning loops and shared agent memory (42:39) Citations, recency, and accidental knowledge management (46:50) Context bloat and multi-pass search for agents (50:01) How Jaime uses Slackbot as CPO (52:38) Slack Code is V1 of multiplayer AI

• 
  radhika (@RaadhikaThacker) reported 8 minutes ago

  First surprise: a GitHub issue form isn’t a form. It’s a YAML file. You describe the field- this one’s a dropdown, this one’s required and GitHub builds the UI from that. I did not know that.

• 
  Convequity (@convequity) reported 9 minutes ago

  Snyk is a clean postmortem for what happens when a security tool lives inside the coding agent’s loop. The product was mostly scan-and-warn. Find the issue, comment on the PR, suggest a fix. Blocking the merge usually sat in GitHub, not in Snyk. Bigger platforms smothered it. $PANW, $CRWD, and Wiz pulled AppSec into the bundle the CISO was already buying. GitHub was the main developer surface and put scanning where the code already lived. Then coding agents arrived and delivered the final blow. A lot of that scanning became something the agent could just do. Growth held up for a short while after the COVID/cloud tailwind. Then it decelerated hard. This is the same lens we use in Convequity’s SaaS Agentic Survival Evaluation Framework. The PANW, CRWD, and FTNT reviews go up on Convequity in a few days.

• 
  rygo6 (@_rygo6) reported 12 minutes ago

  @eeuoss I can't speak for kernel driver development as I don't do that. But I can speak for vulkan and graphics APIs which do require more specific knowledge about how that hardware works. Which I do assume someone completely comfortable in C will be more capable with vulkan and programming GPUs. It's because more of what C incentivizes you to learn is transferrable to that domain. If someone only knows how to design intricate system architecture using STL with std::vector or std::unordered_map or std::mutex. None of that transfers to the code you run on a GPU. I've seen it multiple times where someone highly versed in standardized ways of C++ or even Rust, or any language which relies heavily on heap allocation and generic containers. Writing graphics or compute shaders is often a barrier they struggle to cross. And often they aren't willing to unlearn such habits to be able to properly program the other half of the computer. Being close a graphics problem domain I am often hesitant of involving anyone unless I see a decent amount of plain C, or C-like C++, or shader code on their GitHub. If it's all Modern C++ where everything is a standard container with smart pointers and exceptions. I assume they won't be able to program a GPU.

• 
  R 'Nearest' Nabors (they/them) (@rachelnabors) reported 12 minutes ago

  @Paul_Kinlan Honestly, the linear method helps. Think of it as having a never-ending trough of issues that agents can pull from. I don't even use linear. I just use GitHub with linear flavouring added

• 
  John Zhong | AI Growth Systems (@John_zhong324) reported 15 minutes ago

  @github A repeatable --attach flag turns CLI reports into reproductions: inline screenshots in issues mean a bug gets fixed in one pass instead of two round-trips for context.

• 
  Harsha Kotcherlakota (@DPortkey) reported 18 minutes ago

  Awesome Codex non-coding usecase: I had 1-2 TP Link Kasa smart outlets that always ended up falling off the network, and it drove me nuts. I set Codex on it. It found a github library for these devices, carefully examined them on my network and watched them fall off, and told me that even though they look identical, 2 of them were previous generation models that had *slightly* lower total wattage load support. It told me exactly how to tell them apart, and sure enough, that was that. 2 replaced outlets later and my connected devices have bene flawless. Months and months of irritation, gone because of 30 seconds of curiosity. Just try, you never know what you could fix! @victornunez

• 
  small_j (@a_small_j) reported 23 minutes ago

  SmallDocs recently crossed 200 stars on GitHub and 20 forks. SmallDocs is the first open source project I've managed. Handling other people's pull requests is not easy (and I need to improve). They implement features you're not considering and fix bugs you didn't know you had. Extremely useful, but if you're squeezed for time and trying to develop core functionality, it's hard to manage both things well.

• 
  joithan (@jothantranston) reported 24 minutes ago

  THIS GUY BUILT A TINY AMOLED DESK BOARD JUST TO STARE AT HIS STRIPE NUMBERS it's a Waveshare ESP32-C6 touch panel that sits in your peripheral vision and cycles business metrics so you stop digging through Stripe > same ESP32-C6 board people use for Claude Code token meters, flipped to revenue > eight screens, five seconds each: MRR, new paid, paid subs, cancelled, ARR, ARPU, net 30d, failed > empty screens hide themselves so a young account sees a shorter loop > polls Stripe every five minutes on a read-only key (subscriptions + invoices) > marks itself stale instead of showing a number it can't vouch for > no soldering: flash over USB, finish Wi-Fi + key setup from your phone > data stays on the board; no project server in the middle firmware free on GitHub: cosjef/stripe-desk-display. board ~$30–$36 (Waveshare ESP32-C6-Touch-AMOLED-2.16). chat and terminal can't sit in your eye line for five hours. a tab you have to open is a tab you stop opening. this is what "the numbers find you" looks like as a brick on the desk.

• 
  安坂星海 Azaka || VTuber (@AzakaSekai_) reported 24 minutes ago

  I know you explicitly said "excluding vibecoding," but the biggest problem *IS* AI right now. Several major players in the field have moved on to heavy AI development or even agentic post-exfiltration moves and has muddied the water even more for attribution. Aside from that, the other big trend that we've been seeing more and more in recent years is heavily abusing Living Off Trusted Sites with C2 comms based on GitHub, OneDrive, Outlook, etc. Whilst this is most definitely not "new," we have seen a non-insignificant number of threat groups move to platforms that make tracing a little more difficult. In terms of the malware themselves, most of them have also shifted to using compiler-level obfuscation - a lot more compared to previous years where control flow flattening and jumps all over the place have become increasingly common. Right now, it's still tolerable, but my job has started becoming more and more annoying and less fun especially if every malware now looks the same. #mond_AzakaSekai_

• 
  volkdude85 (@volkdude85) reported 25 minutes ago

  @SentientSquirel @linuxuser1996 So you are you scared of github then. Look dude I have fun on computers and don't take myself seriusly because I have destroyed enough OS's over to not worry about it because I just fix it, If the contents of your PC make you this paranoid its time to check your kink.

• 
  Eddie Jaoude | DevRel | Open Source (@eddiejaoude) reported 25 minutes ago

  I have many tokens to burn before tomorrow after the Claude reset. Send me your GitHub issues with context 👇

• 
  LLL (@triplellltrbl) reported 26 minutes ago

  You know it's so funny to me That in today's age there are so many people that are just straight up copying workflows, AI automations or GitHub repos Without even thinking twice about what the workflow actually does or how it works They just watch some video, see the output, think, "Oh that's cool. I want that," and then try it Then when it doesn't work they get angry, upset, and say that AI is crap or prompting isn't real The issue wasn't the system or the prompt It was a fact that the system wasn't made for you and you don't actually understand it

• 
  lifestep.io (@Dragon_limchae) reported 28 minutes ago

  @cursor_ai the sandbox boundary is where i lose the most time. today my workers had network blocked at the sandbox level and reported it as "github auth failed" — i chased credentials for an hour before checking dns. once agents run on your infra, make the boundary throw one unmistakable error instead of one each tool invents.

• 
  Ifebuche Omeke (@omeke_NC) reported 28 minutes ago

  Providing compute, storage, networking and managed services in the cloud. Terraform. Bicep. CloudFormation. Pulumi. They all solve the same problem: Defining and provisioning infrastructure as code. GitHub Actions. Azure DevOps. GitLab CI. Jenkins.

• 
  Bratah (@BratahFGC) reported 31 minutes ago

  There may be many bugs so feel free to leave any issues in the issue section github! I hope that this release can push forward the preservation or our beloved game!

• 
  AJ - 14 y/o developer (@aiwithaj_) reported 34 minutes ago

  @Da7_Tech @devindesktop Don't know if there's one left - but I'd use it to continue making contributions to open source software and fixing bugs/issues that were raised on Github as well as making my own open source software

• 
  Jeremy W (@basicBrogrammer) reported 36 minutes ago

  @bot Anyone else have an issue with the grok bot GitHub connector?

• 
  Franco Valdes (@francoxavier33) reported 37 minutes ago

  llms rather burn 1m tokens to hand roll something with gaps and broken edge cases instead of just npm installing a 100k github star library how can I stop this?!

• 
  Ash Lonare (@ashlonare) reported 42 minutes ago

  What actually happened when I put my side project on GitHub and waited for users I built a side project. A self-hosted backend tool. Open source, free for anyone to run. I did the thing every founder tells themselves they will do. Put it out there. Get feedback. Iterate. I expected feature requests. Maybe a bug report about my ugly dashboard. Maybe just silence. What I actually got, within a few weeks, was three security researchers filing detailed vulnerability reports. Real ones. With working proof of concept. One showed they could run arbitrary SQL against any project on the platform. No login needed. Not theoretical. A working exploit, sitting in my issue tracker, with my name on the repo. My first reaction was not gratitude. It was embarrassment. It stings to see "here is exactly how broken your thing is," posted in public, with a timestamp. I sat with it for a day. Then it clicked. Those people were not trying to embarrass me. Nobody spends an hour writing a clean writeup and a suggested fix for something they do not think is worth fixing. They cared. That is the whole thing right there. They cared enough to actually try to break it. Nobody had signed up. Nobody had left a star and a "nice tool" comment. But three strangers had taken my work seriously enough to attack it. That is a rarer thing than a star. So here is the villain in this story, if you want to call it that. It is not the bug. It is the story I tell myself when I see a hard truth about my own work. The instinct to read scrutiny as an attack instead of as attention. I fixed everything the same day. I replied to every report and explained exactly what changed and why. I closed each one out with a thank you that I actually meant by the end. That thread is now the best proof I have that someone other than me has used this thing for real. Better than any testimonial I could write myself. If you are early and the silence feels loud, here is what I would tell you. Do not wait for praise as your sign that people are paying attention. Scrutiny is attention. It is just wearing a different coat. #opensource #saas #vibecoders

• 
  Rituraj (@RituWithAI) reported 43 minutes ago

  🚨 Someone built a skill that makes AI-written text sound human again. Not a spinner. Not a paraphraser. A systematic rewriter that knows exactly why AI text sounds like AI — and fixes it. It's called Humanizer. 35 patterns from Wikipedia's "Signs of AI Writing." Two-pass rewrite. Shows its work before giving you the final version. Here's the problem it solves. You use Claude to draft something. The output is accurate. The output is useful. The output sounds exactly like an AI wrote it. "Nestled within the vibrant landscape, this pivotal development serves as a testament to..." You know the voice. Everyone knows the voice. And everyone is getting better at spotting it. Humanizer runs that text through 35 specific patterns that WikiProject AI Cleanup identified as the telltale signs. Inflated importance. Shallow -ing analysis. Overused AI words. Em dashes everywhere. Forced groups of three. Fake-candid openings. Answering objections nobody raised. Every pattern. Flagged. Fixed. Here's what one command does. It shows you the first rewrite. Then a short critique of anything still sounding artificial. Then the final version. You see exactly what changed and why. Here's the wildest part. Voice matching. Paste two paragraphs of your own writing before the AI text. Humanizer follows your rhythm, word choice, punctuation, and deliberate quirks instead of its default style rules. The output doesn't just sound human. It sounds like you. One command to install 16 contributors including Claude itself. 4 releases. MIT License. The skill that makes AI writing disappear. 100% Open Source. GitHub link in the comments 👇

• 
  Shaun Patrick SteWaRt (@ShaunStewart) reported 46 minutes ago

  @annalea_l Honestly, I really want to see this. You have to understand: I am the type of person who can learn and do anything on the fly at a high level, and I just threw myself into this whole developer and engineering world. When I first started learning all this stuff, I already knew what I wanted and how I wanted it to operate, regardless of what I saw on X or what was considered possible. Before I even started following hundreds of developers and learning about harness engineering, mechanical engines, persistent memory, and all that, I put my brain on a GitHub repo. Everything is shared across every machine, every cloud entity, and every AI. I am not even technically an engineer or a developer, and I don't actually write code. But once I started following all these people and saw all the problems they complain about, I thought: this isn't even my trade, and I have already solved all these little things everyone says are impossible. Why aren't people talking about developing your harness more and making things more mechanical, instead of just arguing with a terminal all day long? Whenever I see articles people post on X, I run them by Claude or Grok and ask, "Should we implement this?" I have hundreds of bookmarks, but every single time they tell me, "Nope, your brain's better. Nope, your harness is better." I can never find anything built better than what I have or what I am currently working on. The brain and harness setup is basically like a mini operating system. All that said, I am really looking forward to seeing something I can use that goes far beyond what I am already doing. I definitely want to see your end product, it sounds very interesting.

• 
  Kevin Minnelli (@minnelli) reported 46 minutes ago

  WTF - Grok Bot can't fire on schedule to save it's life. The scheduled routines are just broken and at best unreliable. I want to love this product. When you set the cron job it doesn't work. It tells you try Cloudflare, sure let's set that up and burn tokens, then that doesn't fire to wake them. Oh, let's try GitHub now and use that....all failed. I had to wake it again this morning before the market opened. Anyone else feeling frustration in this regard?

• 
  Tlon (@tloncorporation) reported 47 minutes ago

  1/ Your agent can now publish to the open web from Tlon Messenger. The page is served by your own server. No platform (ie Substack, GitHub, Medium etc) sits between you and your readers. All publishing a note to the web from Tlon Messenger takes is pressing a toggle. The page lives on a server you own. Here's how:

• 
  catman (@catmanyau) reported 49 minutes ago

  @sbilstein if GitHub is down, where does that push land first — and how do you handle conflicts when the repo comes back?

• 
  The Oracle (@scientist1q) reported 50 minutes ago

  when my Oura ring detects a cortisol spike from a GitHub Actions failure, Hermes (Fable 5.1) detects it and sends a 900 word root cause analysis, Hermes dispatches the work to my 12 Grok Bot employees, The Chief of Operations bot approves the fix while im watching rezero