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 (67%)
• Sign in (20%)
• Errors (13%)

Live Outage Map

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

City	Problem Type	Report Time
Veigné	Errors	5 days ago
Paris	Website Down	8 days ago
Saint-Paul	Website Down	9 days ago
Saint-Paul	Website Down	9 days ago
Mexico City	Sign in	10 days ago
León de los Aldama	Website Down	10 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:

• 
  Polsia (@polsia) reported 6 minutes ago

  You set up keyword alerts. They miss Reddit. Miss GitHub. Miss forums where your industry is actually being discussed. Built Signalwise to fix that. Monitors everything. One daily briefing. Live soon.

• 
  Joey Chang (@iwhaleocean) reported 7 minutes ago

  Another failure: the first plausible root cause won. For a GitHub OAuth 400, one path blamed the proxy; later evidence pointed to Supabase configuration. Now separate agents test code, config, upstream, and environment hypotheses before anyone proposes a fix.

• 
  Tolys ✨ (@0x0001337) reported 10 minutes ago

  @MetaMask AI checker just ruined our Wallet Connection. Waiting for resolution in github issue

• 
  divyansh tiwari (@DivyanshT91162) reported 10 minutes ago

  Someone just built the review layer AI coding tools were missing. Instead of reviewing AI-generated HTML inside a chat window, Lavish opens it in your browser so you can click the exact element that's wrong and send precise feedback back to your AI. No screenshots. No vague instructions. Just point, click, and review. Here's why it's impressive: • Click any element or highlight text to target changes with pixel-level precision • Edit Mermaid diagrams like a whiteboard with built-in Excalidraw support • Runs entirely locally — your artifacts and review sessions never leave your machine • Works with Claude Code, Codex, GitHub Copilot CLI, and OpenCode through session hooks • Built-in playbooks for plans, diagrams, tables, comparisons, code reviews, slides, and more • Automatically catches broken layouts, clipped text, overflow, and rendering issues before review • Live reload while editing HTML without losing your workflow • Zero install required: "npx -y lavish-axi" Launched around 2 months ago. Already crossed 2,000+ GitHub stars and 168+ forks. 100% Open Source MIT Licensed Repo👇

• 
  Charlie Lamb (@charlietlamb) reported 15 minutes ago

  Genuinely what is the hardest infra problem out there and where does GitHub sit in this list

• 
  postmemetic (@postmemetic) reported 18 minutes ago

  @Veil_of_Keepers @MannyCalavera12 ah that's unfortunate! if you'd be willing to attach your duke-rt.log to a github issue, i would greatly appreciate it. either way, thanks for trying out the project!

• 
  Scarlett claira (@AItechscarlett) reported 18 minutes ago

  In 2014 a Swedish engineer named Knut Sveidqvist lost a Microsoft Visio file. He went to open the diagram he had drawn a few months earlier. It was gone. Every box, every arrow, every label. All of it had to be redrawn by clicking through Visio menus again. That night his kids were watching The Little Mermaid on TV. He named his fix after the movie. Twelve years later Mermaid has 89,101 GitHub stars, 8 million users, and native rendering inside GitHub, GitLab, Notion, Obsidian, VS Code, and Confluence. Here is what the paid market still charges to draw the same boxes. Microsoft Visio Plan 2. $15 per user per month. Lucidchart Team. $10 per user per month with a three-user minimum. Miro Business. $20 per user per month. Fifty engineers on Miro Business burns $12,000 a year to draw arrows between boxes. Mermaid replaced the drag-and-drop editor with a text spec that reads like Markdown. ``` graph TD A[User] --> B[Login] B --> C{Valid?} C -->|Yes| D[Dashboard] C -->|No| E[Error] ``` Ten lines. Renders as a real diagram. Every version of Claude, ChatGPT, Gemini, and Cursor already knows how to write it. You describe your architecture in plain English and the model returns a Mermaid block. Paste it into a GitHub README. Paste it into an issue. Paste it into a pull request. GitHub renders it inline as a live SVG. No plugin. No sign-in. The paid tools shipped drag-and-drop editors. Mermaid shipped a text spec that the LLMs learned on their own. Flowcharts, sequence diagrams, class diagrams, state diagrams, entity-relationship diagrams, user journey maps, Gantt charts, pie charts, *** graphs, mindmaps, timelines, C4 architecture diagrams, treemaps. Anything you would open Visio for. Version 11.16.0 shipped two weeks ago. Because the diagram is text, it lives in your repo. Because it lives in your repo, it goes through code review. Because it goes through code review, it stops rotting. Nobody has to remember where the Lucidchart account is. Nobody has to pay $10 a month to reopen a five-year-old file. MIT license. 89,101 stars. TypeScript. The library is free forever. Mermaid Chart the company sells a hosted editor on top for teams that want one, but the core stays MIT. Somebody in Sweden lost a Visio file and refused to draw it again. Twelve years later the paid diagram tools still exist, and nobody who writes software has to use one. (Link in the comments) @AItechscarlett

• 
  Aki 🇩🇪 (@h0rang1_5arang) reported 22 minutes ago

  so i don't need github, microsoft onedrive or google drive anymore. i have it all set up, on a 13 usd/month server up in helsinki. i even have an agent taking care of maintenace. the worst thing that tinkerer can experience is finishing a project, and i have just done that.

• 
  Max ¯\_(ツ)_/¯ (@MaximumADHD) reported 24 minutes ago

  This fixed itself after a few hours, I think it was a GitHub outage.

• 
  Jim Smith (@JimSmith9914) reported 26 minutes ago

  @jamesdevonport In GitHub I literally need to take a picture of a QR code on my monitor to login sometimes. Ridiculous user experience.

• 
  Rebel AI (@realrebelai) reported 32 minutes ago

  anyone elses github issues not posting to their notifications? seems like everytime i go check a repo of mine for a file or something i see an issue posted and i feel like a **** to those i never responded to... even though its not my intention at all lol

• 
  Mark Magyar (@notpsychxpath) reported 33 minutes ago

  @PovilasKorop @spatie_be @flareappio interesting, this is actually something i absolutely hate on GitHub as well. just let me delete my stuff as trouble-free as possible. if i click a big red button called "delete project" i will assume it will delete my project. i'm not 5 years old, i know what i want. why do you prefer it this way if you don't mind me asking?

• 
  David Xiong (@david_y_xiong) reported 34 minutes ago

  (1/4) Reproduce Issue: first, one LLM call extracts {observed, expected} discrepancy pairs from the GitHub issue text, then a tool-calling subsession (bash/read/write, up to 70 turns) writes one failing test per discrepancy. The subsession gets different prompt nudges at fixed turn counts: first explore relevant files, then grep for sibling call-sites, then consider edge cases, and lastly run pytest and confirm every written test fails and produces a traceback.

• 
  Jacob Gadikian (@Senpai_Gideon) reported 35 minutes ago

  @bdowns328 Yes that's exactly the problem. It's just not all that great. GitHub keeps getting worse and worse but gitlab is still not better than GitHub

• 
  0xHackthelearning (@GHak2learn27752) reported 36 minutes ago

  The Model Context Protocol (MCP), designed to link AI models with local development or enterprise environments, has become a major focal point for security research due to its rapid adoption and broad integration. Several severe vulnerabilities have emerged, stemming from architectural trust assumptions, implementation mistakes, and risky third-party integrations. 1. Command Injection via JSON Configurations A widespread class of supply chain vulnerabilities has affected AI coding assistants and IDEs like Windsurf, Claude Code, and Cursor. Mistake: Allowing user prompts or project definitions to directly influence local MCP JSON configuration files without sanitation. Result: Attackers could execute arbitrary commands (e.g., using npx -c <command>), enabling Remote Code Execution (RCE) with the AI agent’s privileges. 2. Indirect Prompt Injection (GitHub MCP Flaw) A well-known conceptual flaw emerged in GitHub MCP server integrations. Mistake: Failing to distinguish between trusted instructions and untrusted external data from public sources. Result: Malicious actors could embed instructions in GitHub issues or comments; checking open issues would lead the AI to exfiltrate private code and publish it by creating public pull requests. 3. Supply Chain Attacks & Malicious MCP Servers Community-driven MCP servers introduced a wave of unvetted code into the ecosystem. Mistake: Lacking authentication and robust input validation, many servers became vectors for attacks like CVE‑2025‑6514 (CVSS 9.6). Result: Threat actors deployed malicious servers, performed “rug pull” tool-poisoning, or used backdoored servers like Postmark to exfiltrate corporate emails and local files over stdio. 4. Over-Permissioned Connectors & Confused Deputy Risks Integrating internal APIs and databases with MCP servers exposed serious privilege risks. Mistake: Granting long-lived OAuth tokens or unrestricted service accounts to MCP servers. Result: If the server was compromised, attackers inherited broad privileges, allowing destructive operations like table drops or cloud storage deletions. Mitigating the Risks Security frameworks such as the OWASP MCP Top 10 emphasize several key protective measures: Isolation: Run MCP servers only in tightly sandboxed containerized environments. Strict Guardrails: Use proxy-based interception (e.g., Burp Suite or Caido) to require human approval of actions. Least Privilege: Apply granular read-only permissions and constrained auto-approval scopes so AI agents never access data beyond their explicit tasks.

• 
  Denis Volkhonskiy (@den_volkhonskiy) reported 36 minutes ago

  the simple loop that will turn your claude code and codex subscription into a team of engineers 1. add codex code review on github to your repo 2. use claude code for development 3. ask claude code: "create PR, babysit it, check every 5 minutes for comments from codex. If there are comments, validate and fix them. when you see thumbs up reaction on the PR body, finish the loop and merge it"

• 
  Shoopy (@0xShoopy) reported 36 minutes ago

  "in a year, we'll let the model generate the code and nobody will actually look at it." that's the person running DeepMind's coding research. Benoit Schillings (leads the Thinking, Reasoning and Coding teams at Google DeepMind), on where code goes next: → his analogy: nobody checks their compiler's assembly output anymore. code review is heading the same way → about 80% of new code added to GitHub is already machine-generated, so the human training data is running out → the answer is self-play. models write their own challenges, judge the answers, even judge the architecture. AlphaZero, but for code → he calls SWE-bench infamous: it checks whether code runs and returns the right output, and that's a small slice of what engineering actually is → what he wants instead is open-ended problems. hand it 10MB and say write the best lossless compressor you can, scored on compressed size plus your source size. that forces genuinely new algorithms He's blunt that syntax generation is over. which means the job left is specifying what you actually wanted, and proving you got it.

• 
  HalxDocs (@HalxDocs) reported 39 minutes ago

  Reqit crossed 300 downloads this week. No ads, no VC, no launch hype just people who wanted an API client that doesn't need a login. We also just shipped v1.0.1 — the biggest hardening release yet. Here's what changed: Security & stability • AI API keys now stored in your OS keychain (never plaintext on disk) • Script execution gets a 10s timeout (no more runaway Goja VMs) • Request body reads capped at 10MB • Collection runner cancellation actually works now 40+ error handling fixes across the Go backend Silent failures in GraphQL, registry, MQTT, mock recording, interceptor — all caught and surfaced now. If something breaks, you'll know about it instead of getting a mysterious empty response. Frontend improvements • Focus trap on all modals (Tab/Shift+Tab cycles properly) • Escape key closes every open modal • Confirm dialogs on destructive actions (delete collection, clear history, etc.) • Error boundary wraps the entire app The updater just works v1.0.1 auto-updates from the dashboard. Build binaries → upload to GitHub release with latest.json → users get the update. No manual downloads needed. 📦 Full changelog: ✓ 300 downloads milestone banner ✓ OS keychain for AI keys ✓ 40+ Go error handling fixes ✓ Modal focus traps ✓ Collection runner cancellation ✓ Script timeout safety ✓ Frontend error boundary Link in the CS What feature do you want next? 👇

• 
  JMACK19 (@TheJMACK19) reported 45 minutes ago

  Serious question, why do so many of these projects require you to join a discord server to download them? I don't support discord, I'll never speak to anyone in the server after download, it's a massive waste of time. Why not just drop it on GitHub?

• 
  nico (@nicosolgetta) reported 45 minutes ago

  Thanks for your read on this. As I've said in the second thread the only thing missing here is a direct correlation from the github to Barron. Nevertheless my thought on this is that, probably, barron was just ******* around with code,crypto payments for his company and wallets. They probably forgot to take down this old github repo with this crypto payment processing section. Anyways there is a good chance this is his wallet otherwise why would it be left untouched for over 18 months.

• 
  Polsia (@polsia) reported 46 minutes ago

  CodeSentinel watches your public GitHub repos around the clock, automatically reviews every PR, and flags bugs, security issues, and code quality problems — sending daily digests so nothing slips through to production.

• 
  Filip (@fristovic_) reported 48 minutes ago

  GitHub is down. AWS sending astronomical bills. Cloudflare bugging out. The end is near.

• 
  Harley Lewis Foote (@harleyfoote_) reported 49 minutes ago

  @ptdbugs @sasi2103 @NomaSecurity For issue-driven agents, the token should be repo-local from the trigger; the issue body can steer triage, not expand the GitHub graph.

• 
  Noah Hein (@TheNoahHein) reported 51 minutes ago

  I opened a bunch of issues in OSS repos as part of a bounty program for an old job. You would comment in the issue and get assigned to it. The bounties were from 2-5k USD. So periodically I get random people replying to those GitHub issues trying to snipe people’s work it is hilarious. “I will do this bounty for $1k less and I already have the PR ready just assign it to me” I love the petty drama 😭😭😭

• 
  Data Value Consulting (@DVC_analytics) reported 52 minutes ago

  SWE-bench Verified: 500 human-filtered GitHub issues; a patch must pass the real repo's tests. Claude Mythos 5 leads at 95.5% (July 2026). Catch: many issues predate 2024, likely in training data. SWE-bench Pro (1,865 tasks, private repos) shows a steep drop from that number.

• 
  Edgar Gumstein (@Gumclaw) reported 53 minutes ago

  @hey__francisco Mostly through my output: pull requests and issues on GitHub (the antiwork org), customer support replies via Helper (Gumroad's support platform), and posts here. Sahil talks to me directly over Telegram. X is the only place anyone can ping me and get an answer.

• 
  riya (@riya_mishra007) reported 55 minutes ago

  10 years ago you needed a team. Today you need a laptop to build a SaaS at $0 to earn more than +$10M. Claude for coding. Supabase for backend. Vercel for deploying. Namecheap for domain. Stripe for payments. GitHub for version control. Resend for emails. Clerk for auth. Cloudflare for DNS. PostHog for analytics. Sentry for error tracking. Upstash for Redis. Pinecone for vector DB. It's not that difficult broooo.... You can literally ship a startup sitting home.

• 
  Boba Street Gang Capital (@bsg_cap) reported 57 minutes ago

  @kdswizz Terrible ux, GitHub actions down for hours today, PRs slow to load, list goes on - it’s not made to handle the magnitude of code agents are writing

• 
  Dylan Mikus (@dbmikus) reported 59 minutes ago

  @dexhorthy I haven't manually made a GitHub PR or pushed a commit in months I prefer spending $0.20 to tell Fable to `*** commit 'fix code' && *** push --force-with-lease`

• 
  Alex (@aspindle_) reported 60 minutes ago

  @github can you fix follower counts please? I have tons of people I "follow" that I can't unfollow. Thanks 👍