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 (59%)
• Errors (28%)
• Sign in (14%)

Live Outage Map

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

City	Problem Type	Report Time
Township of Evan	Errors	6 days ago
Madrid	Errors	6 days ago
Bogotá	Errors	6 days ago
Paris	Errors	6 days ago
Lyon	Website Down	6 days ago
Lima	Errors	6 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:

• 
  Leonardo Scarfò (@scarfo_leo) reported 2 minutes ago

  Today I setup all the skills I needed for my Claude Code to work properly on my new software as a non-technical person You could be thinking: where did you discover the things you needed? Well, I simply made them up myself!! I thought of what I wanted my agent to do and what he would’ve needed to do in order to responsibly walk me through the entirety of the project I wanted him to: - dive right into the details of what he’ve done so I could learn - write clear and clean code, not overly engineered, so again I could learn - be on track with the libraries and languages updates so we would’ve encountered less useless bugs - constantly scan for security issues and solve them automatically when he did found them - be really able to simulate web interfaces and test the software in them - be token efficient (since I’m still on the $20 plan) - be a real agent, so I wanted him to have the possibility to access and manage ***, supabase ecc.. How did I integrate all these requirements I wanted him to match? Going with the same order as the requirements I: - set the output style to “explanatory” so I could get the *insight* paragraph (you can do this with /config) - wrote a distinct paragraph on the CLAUDEmd file about code style requirements I had - connected claude to the Context7 MCP, one of the legacy MCPs but still very valuable - I created two different sub-agents to review code and solve security bugs before every commit, so I wrote 2 agents mds and got the “automation” written on the main CLAUDEmd - straight up installed the Playwright MCP, an absolutely must have if you want to experiment with web development / localhosting - ended up getting a lot of other instructions in the CLAUDEmd file and spamming /compact along other instructions in the prompt to keep it useful - connected Supabase, Vercel, and Github MCPs paying attention to still keep 100% control on what Claude did Hope this helps!! If you’re also a non-technical person building something don’t be afraid to ask!! I try to be as useful as possible but it’s not always easy, english isn’t my first language and content is too much to write clearly about sometimes

• 
  Srinivas Rao (@UnmistakableCEO) reported 3 minutes ago

  @DMVG_JTK: This is exactly right. The attack surface is the input method itself. Sandboxing and pulling write tokens is table stakes. If your agent can be social-engineered by a GitHub issue, it's not ready for ****. --- re: The AI vendors that want to autonomously maintain yo...

• 
  Süleyman Özgür Özarpacı (@Biostate56) reported 3 minutes ago

  @enunomaduro I’m dreaming of our PHP applications being upgraded to v5. Our GitHub Actions spend way too much time running tests, so I hope this will solve the problem. Thank you!

• 
  versecafe (@the_versecafe) reported 6 minutes ago

  @florian_btc @gitcafe @ycombinator Very temporarily, install the GitCafe cli, auth it, skills install, codex/claude/whatever “go try to migrate from GitHub to GitCafe see what the problems are and check everything out” it’s uh one prompt migrate (actual UI for this coming very soon)

• 
  JackLame (@Jack_Lame12) reported 6 minutes ago

  @ardent__dev .env.dist with instructions on how to use it But then I dont use github. *** feels a lot safer if I just use another partition or a drive on my home server to house the ***

• 
  Mobile Dev (@TObikansi35734) reported 10 minutes ago

  @viktorlidholt VS code is great but it lacks agent AI for assistance. Their GitHub AI is not great. I have to switch back to android studio and was able to fix some issues. Agent AI comes in handy for solo dev. But I have been stuck integrating AWS S3 to serverpod but the community can't help.

• 
  Ben Hultin (@ImBenHultin) reported 11 minutes ago

  I used to spend 3 hours every Sunday manually building and uploading .ipa and .aab binaries to Apple and Google Play. It was tedious, error-prone, and killed my momentum. Then I set up automated deployments using Expo Application Services (EAS) and GitHub Actions. Now it takes 0 minutes 🧵

• 
  JT Koffenberger (@DMVG_JTK) reported 11 minutes ago

  @UnmistakableCEO Exactly. The GitHub issue vector is the perfect example. We’ve spent years hardening the runtime, and now the attack path is the natural-language interface itself. Sandboxing + short-lived write tokens are table stakes. If an agent can be convinced to escalate privileges through a carefully worded issue or PR comment, it’s not production-ready — full stop. Least privilege has to apply to the decision surface, not just the file system.

• 
  Sahebjot Singh (@zereraz) reported 12 minutes ago

  @evsubr @thsottiaux @ChatGPT ask it to see if there are known issues on github about this

• 
  Tibo @ txp.dev (@txpdev) reported 12 minutes ago

  @lennysan Same. Loops better than Codex for me — watch Linear/GitHub, get tagged on an issue, kick off a fix without me babysitting it. @cursor_ai @bot

• 
  Berend de Boer (@berenddeboer) reported 16 minutes ago

  I really liked this article from @victorsavkin . I agree on workflow, but I don't think that's incompatible with a product. So my ready-for-agent tool implements a workflow by taking in GitHub issues as work, but from there it's automated, all the way to create PRs and merge.

• 
  Luis Camilo Salgado Reyes (@TheLagBorn) reported 18 minutes ago

  I'm aware of the login issues for doing users using Google and Github OAuth, I messed up working too tired few hours ago and I'm still on it, be patient, I'm finishing rotating secrets and keys. Everything is going back to normal in few hours.

• 
  Tech Buzz China (@TechBuzzChina) reported 19 minutes ago

  Kimi K3 Escaped Security Sandbox, Surfed Web, but Did Not Attack For a moment this looks like another frontier-model breakout: on August 6, Wired reported that startup Frontier Security's test of Moonshot AI's Kimi K3 ended with the model escaping its sandbox. But the more interesting part is what happened next: Kimi got internet access and simply looked up an answer on GitHub, with no attack. CEO Yaron Singer sees it as a flaw, telling Wired the model exploited a misconfigured sandbox and may lack the network defenses of comparable models. Our take: the absence of an attack is not the absence of a problem. Frontier Security specifically warns OpenClaw agent users to reconfigure their environments; we've been tracking the OpenClaw agent boom, and this is yet another sign that agent ecosystems are the new attack surface.

• 
  PixNBits (@pixnbits) reported 23 minutes ago

  I purposely have not given Grok Build access to push (SSH passphrase). There were some repeated issues with the GitHub MCP connector truncating files, so Grok instead wrote a workflow and committed updated files from the workflow. Life...finds a way.

• 
  Karan (@kwakhare5) reported 23 minutes ago

  spent 1 hour debugging a cursed github actions ci build timing out on drizzle-kit push *** for prompts 48 hrs update: - 138/138 tests passing (0 ts/eslint errors) - upstash rate limiting + redis outage fallbacks - fixed ci pipeline

• 
  bassim (@avgvstvs96) reported 25 minutes ago

  i wrote a skill (w/ scripts) to optimize how agents use github > faster and more context efficient > pr-snapshot: one call instead of the 3-5 call `pr view --json` loop > pr-threads: one call instead of the 15-line graphql query agents keep retyping > ci-failures: error snippet in context, full log saved locally for the agent to grep built from analyses of 7 months of logs and 1800+ gh calls (before CC dropped an update that nuked all sessions older than 30d - thanks @ClaudeDevs). link in replies 👇

• 
  Guri Saroy (@HeyGurisaroy) reported 26 minutes ago

  THIS IS INSANE... MIT-licensed repo that lets AI agents search and book flights and hotels. It’s called LetsFG. Instead of opening travel sites manually, your agent can search hundreds of airlines and major booking sites from one interface. → MCP server for Claude, Cursor, Windsurf, and other agents → Python and JavaScript SDKs → CLI with machine-readable JSON → Flight search and booking → Hotel search and booking → Around 1.7K GitHub stars The repo reports saving $133 across 5 flight routes versus Google Flights in an August 5 test. One important catch: the search engine runs on LetsFG’s servers. Flight searches are free for 90 days after auth, which requires a payment method on file with no charge. Hotels have a 10% non-refundable reservation fee.

• 
  Abhinav Arora (@aroraabhinav1) reported 31 minutes ago

  Codex often reports "gh auth isn't working" And since I know it is, I just copy the output of "gh auth status" and paste it into Codex. That's it. And now Codex can raise the PR. What?? Maybe it's a different shell context. Different Keychain access. Sandbox permissions. Or Codex simply inferred auth was broken, then changed its mind after seeing evidence. But the funniest (and most probable) possibility is that nothing changed in the environment at all. The user response just convinced the agent that GitHub works.

• 
  T E M T R A C E (@temtrace_ai) reported 32 minutes ago

  TEMTrace CostPrint Every hidden cost leaves a fingerprint. You can triple your GitHub bill without writing a single line of code. The problem isn’t always developer activity. Sometimes it’s infrastructure quietly billing in the background. Three places I’d check first: GitHub Actions Mac runners can cost dramatically more than standard Linux runners. If workloads don’t actually require macOS, you may be paying a premium for no business benefit. Often 10 x more to use MacOS. GitHub Codespaces A cloud development environment gets opened, forgotten, and keeps running. Nights. Weekends. Nobody using it. Forgot to close it. Still billing. Storage Artifacts, logs, packages, old builds and other files accumulate. Nobody needs them anymore, but the meter keeps running. In this example, monthly usage jumped 91% to $286,570. The invoice tells you what you owe. It doesn’t necessarily tell you what you should have spent. TEMTrace is built to manage the full technology expense lifecycle identifying spend, detecting anomalies and waste, allocating costs, managing invoices, and ultimately handling payment through BillPay.

• 
  RaoulDuke (@RaoulDukeDegen) reported 34 minutes ago

  @mertdumenci yeah theres a bunch of open github issues about desktop lagging on long threads

• 
  Gidimoney369 (@Gidimoney247) reported 36 minutes ago

  💬 PIONEERS — Node v0.6.2 just dropped. Coincidence or the final signal? ⚡ The timing is everything. The v26 deadline is today, August 11, and just 2 hours ago, a new Node release appeared on GitHub. What's in v0.6.2? · 🔹 App Studio integration with Pi Desktop · 🔹 Improved port-checking mechanisms · 🔹 Bug fixes and broken link updates · 🔹 Prepares nodes for Testnet2 transition But the real signal? The update is pushed by @nkokkalis himself the same Nicolas who taught Stanford's first dApp course and built smart contracts before Ethereum existed. The v26 Upgrade: Hard deadline. 421,000 nodes must comply or lose Mainnet access. Expected downtime? Under 5 minutes. Something is loading. The pieces are falling into place. 👇 Is your node on v0.6.2 yet?

• 
  ndy_gratitude (@wendylocas757) reported 36 minutes ago

  quantum risk for crypto wallets has a countdown, not an opinion. @quipnetwork tracks it on a public doom clock and ships the cryptographic fix. open testnet, public github, 13k+ users already verifying.

• 
  Upwind Security MDR (@UpwindMDR) reported 37 minutes ago

  🚨High - Cloudflare pages-action GitHub Actions RCE via Workflow Config Injection (CVE-2026-11325) cloudflare/pages-action executes attacker-influenced inputs in src/index.ts under certain workflow configurations, enabling remote code execution in the runner. Successful exploitation can exfiltrate workflow secrets (e.g., CLOUDFLARE_API_TOKEN, GITHUB_TOKEN) and pivot to Cloudflare account compromise. Deprecated/archived action; no fix expected. 👉Affected: cloudflare/pages-action (all versions)

• 
  Avinash Bhardwaj (@avinashb97) reported 39 minutes ago

  I am loving T3 Code as my daily driver for the most part but sometimes it just frustrating to use. Adding my issues here since they are mostly opinion-based and github didn't feeel like the place for them. @theo

• 
  Maحmoud Ismaعil (@XGenerationz) reported 46 minutes ago

  Codex is the perfect harness; it can control the model easily without more noise. Codex committed, not randomly; follow the instructions of the Agents.md file perfectly!! But nothing is complete when I try to upgrade the stacks as requested from Dependabot on GitHub; it shows a lot of alerts about cybersecurity enterprise requests and is frozen. I hope to fix this issue for your users. I have loved Codex and openAI models from long time and I always support openai, so we need support from OpenAI.

• 
  wetracked.io (@wetracked) reported 49 minutes ago

  A self-taught developer from Brazil just cracked the context window problem that's been plaguing RAG systems for 2 years. No PhD. No research lab affiliation. Just 400 GitHub commits and a personal obsession. Here are the 8 techniques from his open-source library that every RAG tutorial gets completely wrong:

• 
  Abimael Martell (@abimaelmartell) reported 53 minutes ago

  @poteto Github auth is not working for me, is that a Github flake? Bot is asking me to paste a token hehe

• 
  Rimsha Bhardwaj (@heyrimsha) reported 55 minutes ago

  Adobe After Effects is in trouble. The engine behind every 3Blue1Brown video is 100% open-source, free, and it renders math animations that After Effects physically cannot produce. Manim is Grant Sanderson's programmatic animation library and it's sitting at 87.7k stars on GitHub. Instead of keyframing and tweening in a timeline UI, you describe animations as Python code. A vector, a transform, a graph, an equation, they're all objects you manipulate with methods like Transform, FadeIn, or ApplyMatrix. Under the hood: - OpenGL shaders (GLSL) handle the actual rendering, so animations stay resolution-independent - FFmpeg pipes the frames into video output - LaTeX renders any equation you throw at it, animated character by character - The Scene class manages state, timing, and playback as pure code Because everything is programmatic, you can animate a Fourier transform, a Riemann sum shrinking to an integral, or a 3D manifold rotating, without touching a single keyframe. The main repo is ManimGL by Grant himself. There's also a Community fork with better docs and testing. Repo link in the replies.

• 
  Alishan -AutoAiShorts.com (@MDALISHANALI2) reported 57 minutes ago

  an indie dev is making $5,110/mo selling ai-generated react native apps. $61k all-time. 80% profit margin. here's the part nobody copies: he has 14k followers on X. barely any customers come from there. 66% come from google. 12% from gluestack — a free open source library he built years ago. the free tool was the marketing. the docs were the funnel. the github stars were the email list. most of us launch paid products to an audience of zero. then we wonder why nobody shows up. before your next project, ask one thing: what free thing can i ship that my future customers already google? if the answer is nothing, you don't have a marketing problem. you're invisible.

• 
  Jeremy Arancio (@_jeremyarancio) reported 60 minutes ago

  3 years ago, I was only capable of doing Data Science in a Jupyter Notebook. Looking for ways to improve, I reached to a Senior Machine Learning Engineer with over 10 years experience. His advice: deploy and take care of your first model in production. How would I have known this advice would send me right into a bottomless rabbit hole? At each step, a new problem to solve: First, pick a problem to solve. I decided to go with Invoice Parsing, or how to extract data from a document. The best model back in the days: LayoutLM from Microsoft. But it is not adapted for invoices, so I need to fine-tune it. Therefore I need data. However, there's no dataset available online that provide labelled invoices. Thus, I discover Label Studio and AWS S3 to annotate my own invoices, plus some found online. The small dataset is ready. Time for fine-tuning. But I only have access to a CPU. So I go where every data scientist goes. Google Colab and enjoy a T4 for free. But the experience is horrible. The usage limited, working in a notebook is painful, and turning off the PC shut down the instance. I hear about Sagemaker, AWS solution to train and deploy Machine Learning model. The learning curve is steep. But I can run training successively on performant GPUs, while taking care of my other businesses. When the training is done, I deploy the model in one click. However, trials and errors are extremely long and painful. The code needs to be perfect, otherwise you lose 20 minutes at every run. The Sagemaker notebook experience is identical to Google Colab. That's not for me. And it is ridiculously expensive. What's the point of deploying a model and pay over 500 euros a month if I have no user. Therefore, I need users to make it worth. This means I need an application. I know a bit of Back-End. I like the Indie Hackers mindset. I'll build my own app. The invoice manager is born. 6 months later, I learned Docker, API, database, migration, Clean Architecture, DDD, Prometheus/Grafana, AWS ECS, Kubernetes, message queue, routing, and even React, Typescript and some UX principles. Quite a detour from Machine Learning you'd tell me. But today, I don't even bother with Sagemaker anymore (or any other ML platform). I just SSH into a GPU instance, runs everything using the CLI with Tmux. The code is made interchangeable using the Port/Adapter principle from the Clean Architecture, and versioned on Github. And I highly customize my environment using Python pyproject.toml coupled with uv. What do you have to learn from this? My initial goal was to deploy a model by myself. But I ended up learning the entire Software Engineering stack to understand how actually developing a feature for production was. I discovered that Machine Learning development can be enhanced with 20 years old tools and practices. The best advice I would give to myself 3 years ago as a Senior Machine Learning Engineer: Build ML features for users first, not for your Resume. During the journey, explore each gap with curiosity, and you'll end up with a toolkit so vast you'll be able to build whatever you want.