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 (71%)
• Sign in (16%)
• Errors (13%)

Live Outage Map

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

City	Problem Type	Report Time
Créteil	Website Down	7 days ago
Trichūr	Errors	11 days ago
Brasília	Sign in	11 days ago
Lyon	Website Down	11 days ago
Tel Aviv	Website Down	15 days ago
Rive-de-Gier	Website Down	15 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  toni (@tonitrades_) reported 7 minutes ago

  @github Capping PRs helps with the queue, but does it fix why reviews pile up in the first place? If reviewers are already stretched thin, limiting submissions might just hide the real problem.

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  Nikolay Konovalov (@br11k_dev) reported 10 minutes ago

  @Tristanrhee3 And GitHub sponsors thingy is so slow I submitted it like a week ago. Still not approved what the hell My expenses arent terribly high but Warsaw rent is like $2k/mo $500 ZUS $1.5k groceries for two people That’s pretty much it I wish I could move into low cost area but moving out is gonna cost a lot because 2x rent price deposit, so I have to suck it up Anyway, my plan is Upwork and finishing my job tracker so I can send faster than 5 applications a day. I refuse to send out 100 applications per day like some people do spray and pay It makes everyone miserable. If people aren’t hiring your spam doesnt make things better You just mopping floors and hiring problem sits above you, 3 floors up there leaky faucet you can’t even reach This has to be collective effort to fix this problem But we have to start with ourselves and stop spamming applications at least And do genuine company research, being responsible Thanks for reading.

• 
  KS Sreeram (@kssreeram) reported 13 minutes ago

  @Lidinwise @leecronin Given that AI coding is all the rage… What is your hypothesis on why the following is true? AI is unable to create even _one_ open source project that’s good enough to enter the top one-thousand open source projects (say on github), with ZERO involvement of humans from birth of idea. Imagine the prompt being something like “Come up with a great idea for a new open source project and implement it”. AI is unable to do any such thing with zero human involvement. My answer on why: Every project in a top 1000 list is a hit. Every hit is a mini-invention of sorts. It is necessarily “out of distribution” is some way. AI is unable to do this because we don’t know how to solve the problem of invention.

• 
  Jose (@SolutionsCay) reported 15 minutes ago

  @petergyang /goal make me app does not work for me 😰 but /goal complete GitHub issues #90, #91, #92 works very well

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  SOURAV PANDA (@i_d_skp) reported 20 minutes ago

  Scenario: You accidentally committed a plaintext database password to GitHub in a .tf file. Fix: Nuke the commit history immediately! Use environment variables (TF_VAR_db_pass) or fetch secrets dynamically at runtime from AWS Secrets Manager or HashiCorp Vault. 🔑 #Terraform

• 
  𝐇𝐚𝐦𝐳𝐚 | Network Engineer (Aspiring) (@Hamzaonchain) reported 20 minutes ago

  Here's a summary of what happened in case you didn't hear about it... A cyber extortion group called FulcrumSec (active since late 2025) hit Novo Nordisk the company behind blockbuster drugs like Ozempic and Wegovy pretty hard. They snuck in back in March 2026 through a compromised GitHub access token, roamed around for over two months, and walked out with roughly 1.3 TB of data across 700,000+ files. Now they've started leaking a 264 GB sample publicly. Inside? Source code, proprietary formulas for pipeline drugs like Amycretin (their next big obesity hope), clinical trial records, employee and patient data, manufacturing details, and even private internal AI models for drug discovery. The hackers straight-up roasted Novo's security, pointing out laughably weak hardcoded passwords like "novo123" and "p_assw0rd" in critical systems. After Novo reportedly turned down a $25 million ransom, the group decided to start dumping samples and shopping the rest around privately. Novo confirmed a limited breach in early June involving some pseudonymized patient data from trials. They say there was no major operational disruption and that they're working with experts but this feels like a massive wake-up call for the entire pharma industry on basic security hygiene. Crazy how a simple token slip-up can expose billions in IP and sensitive health data. What's your take — do you think this will finally force better security practices, or is it just another headline that'll be forgotten in a few weeks?

• 
  David Cramer (@zeeg) reported 24 minutes ago

  @shansmithnz I haven’t been using it but mostly because 1) laziness and 2) I didn’t find the remote sync pleasant in practice I switch PCs too much right now so mostly relying on GitHub issues as artifacts

• 
  Noonien Soong (@mlcarldev) reported 28 minutes ago

  Team @droid It's a bit unfortunate that something, likely in my local Droid installation, has stalled progress. This comes after 20 hours of brilliant, excellent planning and execution on the first 30% of this platform, where a stellar handoff procedure was created so I could start a new mission... which was the recommendation of the orchestrating agent in that first mission. Starting this second mission with a fresh context window, the agent again did a brilliant job planning the next milestones. It was extraordinary, detailed planning... but then it could not execute. After the planning and after me accepting the proposal, it refused to execute, throwing an error every time. The agent tried everything: 1. He decreased the size of the plan down to one line, so it is definitely not the content of the plan causing the issue. 2. He even deleted some mission and plan related json and other files to reset it while preserving all the information. I have restarted Droid and resumed the session, but it just doesn't work. I wrote a detailed, comprehensive bug report and filed it under issues in your GitHub repo, as this seems to be a real problem now. Issues #98 and #99 I hope that a next update will somehow reset my configuration. I didn't see a new version being installed that could have introduced a bug, so this must be something Droid does on such an extensive mission... perhaps when trying to start a new mission in the same repository, which is normal procedure according to the documentation. Something is off, and essentially I have been unable to continue the test since yesterday. I cannot continue having this platform coded here, while Opus Ultracode, on the other hand, has been delivering pretty functional stuff so far. It is a bit chaotic the way it works... it doesn't really stick to the plan... but it always comes back when reminded. I am pretty sure that today I will have a functioning platform delivered by Opus, though it will probably need some debugging and fine-tuning. It is unfortunate because I am confident GLM 5.2 could compete with Opus 4.8. The first stint showed this clearly; that first flawless 98% of the context window in the first mission was absolutely stellar. If I were to reinstall Droid from scratch, I assume I would lose all the artifacts that I have. The orchestrator: Key points to highlight when you pass it to Factory AI: 1. Root cause (smoking gun in the logs): the orchestrator session is bound to missionId 7ba4d425 via session tags, and this binding persists across CLI restarts. ProposeMission looks up that mission directory, finds nothing (because I deleted it trying to fix the issue), and crashes on H.length where H is the undefined result. 2. The bug is likely in session-tag lifecycle: the missionId tag is set at session creation time (before any ProposeMission call), so a failed proposal poisons the session permanently. The tag should be set AFTER a successful proposal, or cleared on restart if the referenced mission no longer exists. 3. The fix is almost certainly to start a completely fresh session (not --resume, and possibly in a new terminal window / after clearing ~/.factory/sessions/). I did not try this because you asked for the bug report first, but it is the most likely workaround on your side. 4. The AskUser tool is also broken in this session with a similar parse error, reinforcing that this is a session-state corruption issue, not a ProposeMission-specific bug. My comment: I meanwhiile tested. All the recommendations and the Ask User tool are now broken, even in completely unrelated new missions and new repositories. Planning also can't go to execution; it's always the same error. Droid seems to be broken for good now, at least on my computer.

• 
  Jose (@SolutionsCay) reported 29 minutes ago

  Two changes to how I work with agents: 1. GitHub App so the agents manage issues directly. Keeps the repo clear of throwaway spec and todo files. 2. EmDash (Cloudflare's serverless WordPress successor) for internal docs. Runs on D1, just SQLite under the hood, so I can export the content and move it anywhere. No more docs sprawl.

• 
  Dmytro Virych (@dmytrovirych) reported 33 minutes ago

  I’ve been shipping code for 10+ years and imposter syndrome still won’t leave me alone. You’d think it chills out with time. Nah. It just levels up. Early days it whispers “you’re not ready yet.” A decade in it hits harder: “bro you’ve been faking it this whole time, they’re about to catch on.” Mobile apps, web stuff, janky systems with too many moving parts, solo products I actually shipped… none of it matters when the voice kicks in. Thinking about speaking at a conference? Lol who do you think you are, those are the real pros. Want to drop an opinion in a thread? Better stay quiet before someone realizes you don’t actually know ****. Here’s the thing I’ve learned: the voice isn’t tracking your real skill. It’s just screaming about the fake gap between what you know and what you think everyone else knows. That second number is 100% made up. Your messy behind-the-scenes vs their perfect highlight reel. All those “professionals” I’m scared of? Half of them are up at 2am staring at a random GitHub issue, quietly praying someone else already solved this exact bug. It never fully disappears. You just get better at shipping anyway while it’s still yapping. If you’ve got way more years than your confidence shows, reply with the number. Curious how many of us are still out here waiting to get “found out.” 🚀

• 
  Andy Wheeler (@CrimeDecoder) reported 44 minutes ago

  For academics, this is entirely open source by its nature. If you right click on the page and view the source, you can see exactly how everything is created. (Hence a downside of WASM, there is no way to hide it if you wanted it to be locked down, like in a paid app.) It can also be deployed on a free static site. So you could deploy it via GitHub pages for free if you wanted to. You don't need to worry about a server at all in this setup. This could easily scale to databases with 1 million plus rows, and works just fine on a cell phone.

• 
  Boyuan (Nemo) Chen (@boyuan_chen) reported 45 minutes ago

  GitHub search is now an agent attack surface. A public malware-finder repo lists 9,330 suspicious GitHub repositories detected through push-pattern heuristics. Even if only a slice is ever encountered by real users, the agent failure mode is obvious. A coding agent asked to "find a library and make it work" can browse faster than it can judge provenance. Fresh commits, plausible README text, and repo-shaped packaging become inputs to an automated install path. The fix is boring and product-level: repo-age checks, provenance scoring, blocked arbitrary ZIP downloads, sandboxed installs, dependency allowlists, and logs that show exactly what code the agent trusted. For agent systems, retrieval belongs inside the security boundary.

• 
  Crypto Update IO 🚀 (@cryptoupdate_io) reported 45 minutes ago

  @CryptoPatel Hsiao-Wei’s exit follows a 30% drop in EF-funded GitHub commits YTD (per Santiment). The real shift? Funds now focus 60% on L2 R&D vs 30% in 2022. We track this daily—breaking it down in our quarterly reports. Follow for the data before the narrat...

• 
  Alpha Batcher (@alphabatcher) reported 47 minutes ago

  David Soria Parra: "2026 is all about connectivity, and the best agents use every available method" A coding agent needs access to the same places you check while building: - repo and PRs - docs - browser - database - error logs - Figma - tasks - payments The article gives the 11 MCP servers for that setup: - Context7, GitHub, Playwright first - Supabase or Neon, Sentry, Firecrawl next - Figma, Linear, Stripe when you need them - Filesystem, ***, Memory, Sequential Thinking as the base Read it if you keep copying code, docs, schemas, screenshots, errors, and tickets into Claude Code by hand

• 
  Blum (@Blum_OG) reported 49 minutes ago

  Andrej Karpathy on MCP: "it's a protocol of speaking directly to agents as this new consumer and manipulator of digital information." that is the cleanest way to think about MCP your coding agent is becoming a second worker inside the product it needs the same context you use: repo, docs, browser, database, errors, designs, tickets, payments if you keep pasting those things into chat by hand you are doing integration work manually the best MCP stack for vibe coding: 1. Context7 give the agent current docs this saves you from stale Next.js patterns, old Supabase calls, wrong Stripe webhook shapes, and Vercel config from 2 versions ago 2. GitHub MCP give it the repo, issues, PRs, branches, workflow runs, and review context half of real work lives outside the file you currently have open 3. Playwright MCP give it a browser the agent should click the thing it built, fill the form, check the mobile view, and catch the button that compiles but does nothing 4. Firecrawl MCP give it clean web research use this before building around a third-party API, writing a comparison page, reading changelogs, or checking pricing claims 5. Supabase or Neon MCP give it the database context that matches your stack start read-only. add writes only when you trust the permissions 6. Sentry MCP give it production evidence real stack traces beat "it crashes sometimes" every single time 7. Figma MCP give it design context when the interface matters spacing, layout, copy, components, and screen structure should come from the file, not from a screenshot and hope 8. Linear MCP give it the task queue bugs, feature work, release notes, follow-ups, and PR links belong somewhere more durable than yesterday's chat 9. Stripe MCP give it official payment context checkout, subscriptions, webhooks, billing, and test mode deserve docs close by and human review close behind 10. Filesystem, ***, Memory, Sequential Thinking give it the base layer files, diffs, history, decisions, and longer plans make the agent act like it is working inside a real project recommended install order: 1. Context7, GitHub, Playwright 2. Supabase or Neon, Sentry, Firecrawl 3. Figma, Linear, Stripe when the product needs them 4. Filesystem, ***, Memory, Sequential Thinking as the base

• 
  Arti | AI Builder (@Artur_roses) reported 53 minutes ago

  Claude Code takes a GitHub issue and returns a tested, reviewed PR. No human in the loop. The new dev skill isn't writing code — it's writing issues precise enough that the agent ships what you actually wanted.

• 
  Mug Club Boutique (@UsernameAndStuf) reported 54 minutes ago

  @cyber_rekk A github token on a linux server they didn't update is how

• 
  Crypto Update IO 🚀 (@cryptoupdate_io) reported 55 minutes ago

  @CRYPTOKRALI3 Hsiao-Wei’s exit aligns with EF’s recent sharp decline in GitHub contributions—down 35% YoY per Electric Capital’s data. We track this daily; latest reports show a 12% drop in ETH core dev activity despite all the ‘decentralization’ hype.

• 
  The Flow (@raxpcodes) reported 55 minutes ago

  Got bored with ubuntu , set up fedora kde on my nvme and removed windows permanently , no more dual boot. Also learned Verison Control and GitHub , also submitted my first pr (good first issue).

• 
  Pipeshub ( Open Source Alternative To Glean ) (@PipesHub) reported 57 minutes ago

  Pipelines are built. Context is broken. MCP is quickly becoming the default interface for enterprise AI agents. And that’s a good thing. It gives agents a standard way to connect with tools and data. Connecting an AI agent to Slack, Jira, GitHub, and Salesforce doesn’t mean it suddenly understands your business. It just means it can access your data silos. In short: "MCP gives your agent a passport. It doesn't give them a map." As enterprise AI undergoes a massive platform shift from passive chatbots to autonomous agentic workflows, this naive, runtime "federated search" approach creates an ugly cycle in production: - The Latency Spike: Slower agent execution while waiting for multiple external APIs to respond before it can even begin reasoning. - The Token Bleed: Skyrocketing bills from shoveling raw, unranked JSON dumps into a massive context window, praying the model finds the answer. - The Governance Nightmare: A massive risk of data leaks if you rely on a base LLM to magically guess and police complex enterprise security permissions on the fly. Agents do not fail because they lack intelligence. They fail because they lack the right enterprise context. The hardest problem in enterprise AI isn't connecting to systems. MCP solved that. The hardest problem is Context Engineering. MCP is the perfect interface, but a permission-aware context layer must be the foundation. 🚀 If AI is becoming core enterprise infrastructure, you cannot allow the strategic intelligence layer of your company to sit inside someone else's managed, closed-box platform. That is exactly why we built Pipeshub (open-source developer owned context infrastructure layer). TL;DR MCP gives agents access. A context layer gives them understanding. And deep understanding is the only way enterprise AI moves from a cool demo to secure, reliable production. 👉 Next Up Tomorrow: MCP Token Tax

• 
  Romano Roth (@RomanoRoth) reported 57 minutes ago

  2/ CodeRabbit (Dec 2025), 470 GitHub PRs analysed. AI-co-authored code: 1.7x more issues per PR, 75% more logic and correctness errors, 2.74x more XSS vulnerabilities. Velocity up. Quality down.

• 
  Nav Toor (@heynavtoor) reported 57 minutes ago

  There is a GitHub repo that defeats Google's Play Integrity check. 61,030 stars. GPL licensed. Pushed eight days ago. The repo is called Magisk. It roots your Android phone. It hides root from banking apps. It runs Netflix on a phone the Play Store says is uncertified. It passes the same fraud detection Google built to stop it. Here is the part that makes no sense. The man who built it is John Wu. He has been maintaining Magisk for nine years. Since November 2023 he has been a Senior Software Engineer at Google. On the Android Platform Security team. The exact team that builds Play Integrity. Google hired the person who defeats their root detection. He still ships the tool that defeats it. The repo is still online. It has not been taken down. For nine years. Do not install it. Your phone is supposed to belong to Google. (Link in the comments)

• 
  Nitesh (@NiteshTechAI) reported 58 minutes ago

  This repo should not be free. private-gpt turns any local model server (Ollama, llama.cpp, vLLM) into a Claude-compatible API. Build private AI apps where zero data leaves your machine. ↳ 57,236 stars on GitHub ↳ RAG with citations and MCP connectors built in ↳ follows the Claude API spec: streaming, batch, tool use, extended thinking ↳ official integration guides for Claude Code, Claude Desktop, and Microsoft 365 But it is free. 100% open source, Apache 2.0. v1.0.0 shipped 9 days ago. The viral 2023 script quietly became production software. 🔗 GitHub link in the comments 👇

• 
  AI Crave (@wecraveai) reported 58 minutes ago

  Open source NotebookLM alternative with no data limits and AI agents. Same idea as Google's NotebookLM. Same chat-with-your-docs. Same podcast generator. Same cited answers. Except this one has no source limit, no notebook limit, no 200MB file cap, and no Google login. It's called SurfSense. Google NotebookLM vs SurfSense: - Sources per notebook: 50 to 600 → Unlimited - File size cap: 200MB and 500K words → No limit - LLM choice: Gemini only → 100+ models via LiteLLM - Local LLMs: Not allowed → Full Ollama and vLLM support - Self-host: No → Yes, one Docker command - Price: $0, $19.99/mo Pro, or $249.99/mo Ultra → $0 forever Here's the wildest part: It connects to 27+ sources Google can't touch. Notion. Slack. Linear. Jira. GitHub. Discord. Dropbox. OneDrive. Gmail. Confluence. Obsidian. ClickUp. Microsoft Teams. Airtable. Your entire work life, indexed once, searchable from one chat box. 14.4K GitHub stars. 1.4K forks. 6,232 commits. Apache-2.0 license. One honest note: the README says it's not yet production-ready and still being actively developed. But it already does more than NotebookLM does, and the gap is widening every release. This is what NotebookLM should have been from the start. Repo in the first comment.

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  Nirvaan rohira (@nirvaan_rohira) reported 59 minutes ago

  PewDiePie shipped Odysseus to 110 million people who don't care about local LLMs. They care that Claude costs money. 30K stars in 48 hours because every self-hosted project before this one started with "you want local LLM, right?" This one started with "here's a free workspace that works." Friction was never technical. It was the asking. Now watch what happens when a hundred thousand people who've never touched open source start running inference on their machines. The real distribution problem wasn't GitHub. It was YouTube. That's not a product launch. That's a category shift.

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  MarMar Labs (@MarMarLabs) reported 59 minutes ago

  "Start over from a screenshot." That phrase has defined the worst seam in product work — the design-to-code handoff — for years. This week it quietly stopped being a translation problem and became a sync problem. Anthropic shipped a Claude Design update (June 17) worth reading even if you never open the product, for the mechanism: → Import your design system from a GitHub repo (or design files / raw uploads) → Claude builds with YOUR components, checks its output against your design system, and corrects before you see it → /design-sync pulls your system in; hand off to Claude Code and it continues from your actual work "instead of starting over from a screenshot" → /design lets you create, edit, and sync design projects from the terminal The headline isn't "the model draws prettier buttons." It's grounding + self-verification against a source of truth you control. Same shape as the rest of 2026's agent releases: the win isn't generating more, it's grounding output in something you own and checking against it. The uncomfortable builder takeaway: Getting AI to ship production UI isn't a prompting problem. It's whether your design system is a clean, importable, machine-checkable artifact. The moat moves from "can the model design" to "is your source of truth importable and checkable." If you build product: could an agent import your design system and grade itself against it today — or does it only live in a Figma file and three people's heads?

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  𝕊ℍ𝕀ℕ𝔸☃ (@Shinawritesbugs) reported 59 minutes ago

  @viii_fn Github was slow too

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  Rafal Wachol 💙 (@RafalWachol) reported 60 minutes ago

  @itometeam @tsuyoshi_chujo I was playing with it and started creating issues on GitHub when I noticed something.

• 
  Shubham Sharma | AI & Tech (@editxshub) reported 60 minutes ago

  Paying $19/month for GitHub Copilot? Cascade is free. What you actually get: → Inline completions — not stripped down → Autonomous debugging → Real-time assistance → Command execution Other free alternatives most devs have never tried: → Cline — autonomous VS Code agent (open source) → Aider — terminal-first, built for *** workflows → Continue — local LLMs, data stays on your machine 12 months ago: Copilot was the only serious option. Today: 4 real free alternatives. Most teams paying for Copilot haven't tested any of these. 30 minutes could change a year of costs. Which one are you testing?

• 
  Oluwatobi O (@ooluwatobig) reported 1 hour ago

  More trouble for GitHub as Cursor has launched Origin, a product which is essentially GitHub for AI agents