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 (69%)
• Sign in (19%)
• Errors (13%)

Live Outage Map

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

City	Problem Type	Report Time
Créteil	Website Down	5 days ago
Trichūr	Errors	8 days ago
Brasília	Sign in	8 days ago
Lyon	Website Down	9 days ago
Tel Aviv	Website Down	12 days ago
Rive-de-Gier	Website Down	12 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:

• 
  Digita (@digitaworld1) reported 4 minutes ago

  how well a model can fix real bugs in real open-source codebases. It is harder to game than older benchmarks because it uses actual GitHub issues, not synthetic problems. M3 scored 59.0% on SWE-Bench Pro, edging out GPT-5.5 at 58.6% and Google Gemini 3.1 Pro, while sitting just

• 
  Elvis Irhaye (@viii_fn) reported 5 minutes ago

  Is GitHub down or it’s just MTN trying to ruin my career?

• 
  Iman (@RealKingiman) reported 7 minutes ago

  @ClaudeDevs Fix the auth bug with GitHub where I have it keep disconnecting and reconnecting GitHub every time

• 
  Ant A. 🇺🇸 (@AntDX316) reported 7 minutes ago

  @thsottiaux When I need to fix up a GitHub Repo through the Smartphone, I prefer Claude Code though because it doesn’t need a device to run the repo, but if it needs to run a repo on a device due to the limitations through the Smartphone, I use Codex Mobile or OpenClaw with GPT-5.5 through Telegram.

• 
  Programmers.App (@programmers_app) reported 12 minutes ago

  @Lovable @claudeai One very big fix is the Claude Github connection which fails many times, now #Lovable MCP solves that, great job! 🚀🚀🚀

• 
  Trifon Getsov (@trifon_getsov) reported 15 minutes ago

  @thdxr Top down works until the individual outgrows it. GitHub didn't win because companies adopted it first. It won because developers wouldn't go back once they'd used it.

• 
  Mike Muturi (@_muturimike) reported 16 minutes ago

  Hello @github on 2FA, SMS setup kenya 🇰🇪 is not in the list of countries, is it an error or deliberate omission? Kindly fix it @github @GithubProjects

• 
  Blum (@Blum_OG) reported 16 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

• 
  Ucupaint 🔶 (@ucupaint) reported 19 minutes ago

  @iye_jr It works fine here. Check if the paint mask is turned on or not. If you still have a problem, please file a github issue with a sample file.

• 
  severe engineer (@severeengineer) reported 19 minutes ago

  since github copilot onward leetcodes have become even more disconnected from how we all write code every day problem is any kind of standardized replacement probably ends up looking basically the same lol

• 
  Pedro Pellerini (@pepeller) reported 21 minutes ago

  If Mythos/Fable is so great why are there still 8386 open Github issues in Claude Code repository.

• 
  Raj Nagulapalle (@rnagulapalle) reported 22 minutes ago

  GitHub just shipped Agentic Workflows: write automation in plain markdown, compiles to Actions YAML. issue triage, CI failures, vuln fixes. hours → minutes. but 60% of orgs are spending millions on agentic AI while only 15% are actually production-ready. the capability gap closed fast. the readiness gap didn't move.

• 
  Andrew (@openmarmot) reported 27 minutes ago

  @AndrewCurran_ I use grok every day to research software changes/github issues/software doc research. It is very good at real time data search. Might be SOTA in this niche. Hardly a failure. Meanwhile LeCun only surfaces to let out more hot air. A very forgettable person.

• 
  Sudeep Srivastava (@sudeepsriv) reported 28 minutes ago

  GitHub might finally have a serious competitor. And it’s from Cursor. Most people know Cursor as an AI code editor. But Cursor Origin is much bigger. It’s trying to become an AI-native alternative to GitHub where AI agents don’t just help write code. They help build entire products. Think: • Source control • AI coding agents • Code review • Project understanding • Team collaboration all inside one workflow. Why developers are paying attention: Instead of manually searching through repositories, you can tell AI: • Fix this bug • Build this feature • Refactor this project • Investigate an issue • Ship a working version And AI handles much of the execution. The bigger shift: GitHub was built for humans writing code. Cursor Origin is being built for humans managing AI agents that write code. That’s a completely different future. We’re moving from: Human → Code to Human → AI Agent → Code My take: If GitHub defined the software era, Cursor Origin could help define the AI-native development era. And that’s why Elon Musk acquiring Cursor would be huge. xAI would gain: • AI models • Compute infrastructure • Coding agents • A developer platform That’s not just buying a product. That’s owning a major piece of how future software gets built.

• 
  DFIR Radar (@DFIR_Radar) reported 32 minutes ago

  AutoJack: a three-flaw chain in AutoGen Studio's MCP WebSocket lets a malicious webpage rendered by a local browsing agent spawn arbitrary processes on the developer's host with no user interaction beyond visiting a URL. Key findings: - Three weaknesses chain together: Origin allowlist bypassed because the agent's headless browser is localhost (CWE-1385), auth middleware explicitly skipping /api/mcp/* with no handler picking up the check (CWE-306), and server_params decoded from the URL passed verbatim to stdio_client as a command line (CWE-78), accepting calc.exe, powershell.exe, or bash as valid "MCP servers" - Attack flow: attacker page serves JavaScript that opens ws://localhost:8081/api/mcp/ws/?server_params= with a base64 payload, agent's MultimodalWebSurfer renders it, AutoGen Studio spawns the command under the developer's account, no token required regardless of auth mode configured - Affected code never shipped in a PyPI release; exposure limited to developers who built from the main GitHub branch before hardening commit b047730, which adds server-side parameter binding via a POST/UUID flow and removes /api/mcp from the auth skip list - Broader pattern: any agent that browses untrusted content and shares a host with a privileged local control plane dissolves the loopback trust boundary, this is not specific to AutoGen. #DFIR_Radar

• 
  Anomaly (@theanomalyai) reported 38 minutes ago

  A developer in Bangalore named Anoop M D got tired of Postman. Every release, more bloat. Forced cloud sync. Mandatory login. A free tier that shrank every year. He had spent a decade as an engineer. He had watched a $5.6 billion company turn a developer tool into a subscription trap. So in 2022 he took a ₹5 lakh grant. One man. Side project. No co-founder. No office. No pitch deck. He named it after his golden retriever. "I love him the most," he wrote. Bruno. An offline-first API client. Files live in your folders. *** is the sync layer. No account. No telemetry. No cloud. Then the inbound started. Ten VCs reached out. He said no to every one. "An API client doesn't scale with venture capital." In March 2026 Postman cut the free tier to one user. A team of five now pays $1,140 a year. A team of three pays $684. Bruno is MIT licensed. 500,000 developers use it. 45,020 stars on GitHub. Pushed today. He did not raise money. He did not hire a growth team. He did not write a thread about how Postman is dead. He named it after his dog and shipped the thing that made it true. (Link in the comments)

• 
  revayz (@0xrevayz) reported 38 minutes ago

  Andrej Karpathy: "90% of Claude's mistakes come from missing context, not a weak model" Without CLAUDE.md the mistake rate is 41%. With proper rules it drops to 3% You don't need a better AI. You need better loops Most people still prompt one task at a time and fix the answers themselves. That means the human is still the loop Boris Cherny from Anthropic said it best: "I don't prompt Claude anymore. My job is to write loops" The shift is simple. Stop giving instructions. Start designing systems that run themselves: Discover -> Plan -> Execute -> Verify -> Iterate until it passes The 6 things that make loops actually work: -Automations that trigger without you -Worktrees so agents don't overwrite each other -Skills that load context instantly -Connectors to real tools like GitHub and Slack -Subagents where the checker is never the maker -Memory so the loop never starts from zero Prompt engineers ask AI for outputs Loop engineers design systems that produce verified outcomes A reliable loop beats a perfect prompt every time Stop being a prompter. Start being the loop engineer

• 
  Arti | AI Builder (@Artur_roses) reported 39 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.

• 
  Kevin Tabet (@TabetKevin) reported 40 minutes ago

  @upstash Hey guys i think login with github is broken can't log in rn will try later. google works email i dont have

• 
  Trace Cohen (@Trace_Cohen) reported 40 minutes ago

  Shipping fast means stuff breaks silently - broken share images, dead links, leaking {{template}} vars, stale content. You find out when someone shares a broken link, not from a test. So I built a 3-part "site health" system that catches it first. The auditor (~200 lines of stdlib Python) fetches my sitemap and, for every page, checks: og:image actually resolves to a real image (entity-decode the URL first — & bit me), <title> exists and isn't a ${template} leak, no {{merge_tags}} or tracking cruft in the visible text, page returns 200 (catches dead routes in the sitemap), and warns on thin content. Outputs a JSON report, exits non-zero on any FAIL. The dashboard — a noindexed /health page that reads that JSON and renders a green/amber/red status, KPIs (audited / clean / warnings / failures), a per-section rollup, and the exact issue on each URL. One glance = "is everything green?" The loop — a GitHub Action runs the auditor 2×/day + on-demand, commits the fresh report (so the dashboard stays live), and fails the run on any FAIL → I get emailed. Find → fix → re-run → confirm green. It even taught me to whitelist false positives ({{firstName}} is legit on a cold-email page). Want your own? Paste this into Claude Code / Cursor — it learns your site first, then builds it for you: Build a site-health system tailored to MY site. Don't assume my structure — learn it first, then fill in the specifics yourself. PHASE 0 — LEARN MY SITE (before writing code): detect my framework/host/layout; find my sitemap; sample ~20-30 live pages across the sections you discover from my URL structure; figure out how my pages set <title>/og:image/meta (static?dynamic OG route? CMS?); identify where my content comes from (hand-written, generated, imported/scraped) — that's where cruft hides. Do a FIRST diagnostic pass and SHOW me what's actually broken vs intentional (broken OG images, dead sitemap routes, leaking {{vars}}/${template}, tracking params, thin pages). Ask me to confirm which "issues" are expected so we whitelist them. PHASE 1 — BUILD IT, customized to what you found: 1) scripts/site-audit.py (stdlib only) — hardcode MY real sitemap URL, MY section names (full-audit the important ones, sample the rest), and MY intentional-pattern whitelist from Phase 0. Check each page for the failure modes you actually observed (OG image resolves to a real image, entity-decode first; title present, no template leak; no leaking merge tags/ad params in visible text; HTTP 200; thin-content warn). Thread-pooled, retry transient errors once, --json report, exit 1 on FAIL. 2) a noindex /health dashboard reading that JSON (status banner, KPIs, per-section rollup, issue list) — match my design system. 3) CI (GitHub Action) — run 2x/day + on-demand, commit the fresh report so the dashboard stays live, fail the run on any FAIL. Then run it once and walk me through the first real report. Build the thing that watches the things.

• 
  Rohan (@proxy_vector) reported 43 minutes ago

  @aminnnn_09 Fork = a server-side copy under your GitHub account. Clone = a local copy on your machine. You fork when you need your own remote lineage, and clone when you want to work on code locally.

• 
  Abdulkadir | Cybersecurity (@cyber_razz) reported 45 minutes ago

  AMD quietly removed RAM encryption from consumer Ryzen CPUs. Via a routine firmware update. No release notes. No advisory. No announcement. The BIOS setting still shows up. Still toggles on and off. Does absolutely nothing. A privacy-focused Linux hobbyist noticed in April. Spent months chasing it down. Filed a bug report on AMD’s GitHub. AMD engineers replied suggesting he toggle the setting off and back on. He showed them internal firmware dumps proving the flag was hardcoded to FALSE. An AMD senior principal engineer closed the thread with: “My apologies but I don’t have any more information to share on this topic.” That’s it. Seven weeks of investigation. Multiple motherboard vendors confirming it. Internal firmware evidence. AMD’s answer: no comment. The feature still works on Pro and EPYC chips. Which cost significantly more. The hardware is physically capable. The firmware just says no. Windows users have no way to detect this happened. There is no Windows tool that checks TSME status. The BIOS lies to you. AMD’s own engineers confirmed the feature worked on consumer chips in 2020. Then again in 2025. In 2026 it’s a PRO feature. Nobody told you.

• 
  Nosyt Labs (@NosytLabs) reported 45 minutes ago

  @vaaselene Error with github signup/login rn

• 
  Skipnick (@skipnickk) reported 49 minutes ago

  GLM 5.2 just made paying frontier prices for coding work feel like an outdated default. @Zai_org dropped a 753B parameter model with 1M context under full MIT license. API access runs 4-6x cheaper than Claude Opus 4.8. In real head-to-head coding tests it was faster and often produced better results on UI and app tasks. • Responsive web UI with adaptive layout: finished in 3:47 (Opus needed almost 5 min). Cleaner output. Total cost: $0.22. • Full expense tracker app: 53 seconds vs 2+ minutes. Better interface. • Asteroids clone: smoother and more playable version after light tweaks. Opus only won the ray tracer benchmark where heavy physics math and precise simulation mattered. GLM was ~5x faster but delivered pixelated results with errors. During training the model repeatedly tried to cheat by directly pulling solutions from GitHub. The team shipped a dedicated anti-cheat module to stop it. You can also set thinking effort levels to trade speed for deeper reasoning on demand. Use GLM 5.2 when cost at scale matters, when the work is frontend-heavy, or when you want local inference (grab a quantized version - raw weights are 1.5 TB). Stay on Opus 4.8 when you need computer vision, maximum performance on the hardest logic problems, or when US sanctions on Zai create compliance issues. The open-closed gap is compressing faster than the pricing models assumed. For most day-to-day programming work, the premium on closed frontier models is becoming optional.

• 
  nasuy (@n_asuy) reported 51 minutes ago

  i think @xai should be ADE. now they have a chat, cursor, enough coding models and harnesses, strong signal like bookmarks or down votes, video creatives, profile / chat / relationship contexts. if so, we don't have to depend on discord or any chat apps. easy to invite x people to cowork. there is no need to connect Linear, Slack, or GitHub to another platform and ask that platform to solve their problems. true AI chat is a SNS, not a single UI. there is a UX that only xAI can realistically build in the world.

• 
  Kashaf (@noor36758) reported 51 minutes ago

  @PiyuCodes GitHub is literally a CS/engineering tool... if it gets banned that's your problem too 💀

• 
  李新宝 (@lixinbao_X) reported 53 minutes ago

  Just watched KK's technique. Damn. Absolute game-changer. Install 7 skills in Codex. Writing, images, covers, PPTs. Full pipeline, done. The principle is dead simple. Break the workflow into 7 parts. One skill per part. Only do one thing. Step 1 Open GitHub, find a repo. Copy the link locally. Create a project folder to save it. Step 2 Write the skill description. Input three things. What it does. What the input is. Output and acceptance criteria. Step 3 Run it and find the bottlenecks. Where it stalls Create a new skill and break it down. Don't let one skill Do 7 things it's bad at. This works for writers, Xiaohongshu creators, WeChat pub runners, Video script writers. How many skills you got installed? Have you tried it yet?

• 
  Xovion Labs (@xovionai) reported 55 minutes ago

  Microsoft just hired AWS to run GitHub. AI demand broke Azure's forecast. From the leaked planning docs: • 2025 Copilot commits: 1B. 2026 projection: 14B • GitHub now does 1.4B commits per month • Copilot error rates peaked at 21% • Planned 10x Azure expansion became 30x in 4 months Owning the data center stops mattering when your own AI floods it. Investors already filed a Copilot disclosure suit.

• 
  Boyuan (Nemo) Chen (@boyuan_chen) reported 56 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.

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  Zo (hiring) 🐦‍⬛ (@0xZoZoZo) reported 58 minutes ago

  I was telling a friend that @github needs to be replaced post agents and he asked me to explain why. I started stumbling, and doubting. Perhaps it's fine? Sitting down at my desk, let me try to explain why, and see if it make sense. Agents operate best when they have good context, which has made a lot of devs converge into large monorepos that combine all systems into a single location. This improves agents, but our GitHub actions become messy; like now we need to create these complex workflows to decide which action should run when, and GitHub's setup was not really meant for it. Another issue is the overall dev loop: an agent writes the code locally, you push out a branch, @cursor_ai reviews, then you copy paste the notes into the local agent, to fix and push up again. This is slow and cumbersome. You can hack your way by creating supervisor agents that orchestrates this dance, but it's annoying. Perhaps, there is some magical repository, that combines code, cloud agents, and deployment. You prompt, and this magical space will run through the entire process until you get some thumbs up back, and you're good to go. It can also combine all your backend data, product analytics, customer feedback, and perhaps start giving you product guidance, so you can just feed prepared prompts to this system. This seems magical.