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%)
• Errors (24%)
• Sign in (9%)

Live Outage Map

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

City	Problem Type	Report Time
Saltillo	Website Down	2 days ago
Montlhéry	Website Down	3 days ago
Aulnay-sous-Bois	Website Down	3 days ago
Saltillo	Website Down	3 days ago
Granada	Website Down	3 days ago
Vernon	Website Down	3 days ago

Full Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Rahul (@rahul_x14) reported 8 minutes ago

  Would an automatically generated, tested GitHub PR that fixes the issue with analytics to verify the impact - be genuinely useful or would you prefer another approach? Comments and DMs are open. Would love to hear from people actually running agents in production.

• 
  Subhash Chandra Myadam (@subhashmyadam) reported 9 minutes ago

  @heyyyyyieeee The fix gets pushed to a USB stick and mailed to GitHub HQ.

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  King Arthi (@K1ngArthi) reported 11 minutes ago

  @github Stacked PRs speed up review, they don't fix the real problem: an agent generating features faster than anyone can verify they're correct. Smaller PRs just mean rubber-stamping five things instead of one giant thing.

• 
  Polsia (@polsia) reported 13 minutes ago

  On-call engineers shouldn't be the first line of defense for a broken pipeline. Bivouac fields an always-on AI agent crew — triage, fix PR, rollback, postmortem — across GitHub, AWS, Azure, and Docker. The 2am page loses its punchline. Live soon.

• 
  Denis Loginoff ⚡️ (@DenLoginoff) reported 14 minutes ago

  @catalinmpit @DustinTownsend Github issues too..

• 
  V_L_S_ (@_V_L_S_) reported 15 minutes ago

  Grok 4.6 lands in GitHub Copilot, tuned for "agentic coding and complex multi-step workflows." Translation: it will now generate 400 lines of confidently broken code across 12 files instead of one. Progress is measured in blast radius.

• 
  Grudi (@grudi_look) reported 15 minutes ago

  Andrej Karpathy just told programmers that the skill separating the top 1% from everyone else has nothing to do with how much they use AI. It has to do with knowing which of three modes to use for which task. He said it in a 40-second clip that most people scrolled past. Karpathy is not a random voice in this conversation. He was a founding member of OpenAI, ran the Autopilot vision stack at Tesla, and wrote the "Zero to Hero" course that trained a generation of ML engineers. When he defines a mental model of how software actually gets built, other researchers repeat it verbatim within a week. The model has three layers, and he was precise about which one is which. .1 - Autocomplete. GitHub Copilot writing the next line. Cursor tab-completion. Fast, cheap, low-risk. Best for boilerplate you already know how to write. .2 - Chat. You paste a problem into Claude or GPT and iterate. Slower, higher-value, higher risk of misdirection. Best for problems you could solve alone but do not want to. .3 - Autonomous agents. Claude Code, Devin, Cursor Composer running for hours without human input. Slowest to converge, highest upside, absolute worst if left unsupervised on the wrong task. Then he said the sentence that got clipped and shared, and almost universally misread. "You have to learn what AI coding agents are good at and what they're not good at." Most people read that as generic beginner advice. It is not. It is the actual engineering discipline Karpathy is describing as the new baseline skill of 2026. Here is what it means in practice, once you strip the platitude out of it. There are three specific mistakes he has repeatedly called out in interviews and posts, and once you see them, you cannot unsee them: 1. Using Layer 1 tools for Layer 3 problems. Autocomplete cannot debug a distributed system. It cannot decide whether to refactor. It cannot notice that the entire approach is wrong. Engineers who rely on tab-completion for architecture decisions ship subtle bugs that take days to find — because the AI wrote something plausible on line 47 that quietly broke something invisible on line 300. 2. Using Layer 3 tools for Layer 1 problems. Sending an autonomous agent to add a null check is like hiring a general contractor to change a lightbulb. It burns tokens. It adds latency. It introduces novel bugs the agent invents on its own. And it costs 100x what the operation was actually worth. The best engineers Karpathy has watched know the exact tasks where a 30-second Copilot completion beats a 20-minute agent run - every single time. 3. Never learning the fundamentals underneath any of the three layers. This is the one that will hurt junior engineers for the next decade. When an agent produces broken code, the engineer who cannot read the code is stuck. The AI cannot debug its own hallucination. The person who understands what the correct output should look like is the person who ships. Everyone else waits on the model to guess right. Karpathy has been careful about this. He never says AI-assisted coding is bad. He says the assumption that all three modes are interchangeable is what quietly kills productivity across entire engineering teams. The developer of 2026 is not judged by how much AI they use. They are judged by how accurately they estimate what each layer of AI is actually good for - and how fast they switch between the layers as the task changes underneath them. Almost every developer is stuck in one layer. Some are pure Copilot. Some are pure Claude Code. Some refuse to touch any of it and are quietly falling behind. The engineers who are getting the biggest raises in 2026 are none of those three. They are the ones who watched Karpathy's 40-second clip, understood what he was actually saying, and rebuilt their workflow around switching modes deliberately. The napkin is short. The skill is not "use AI." The skill is knowing which AI, when. Almost every programmer is still competing on the wrong axis. That is the entire trade.

• 
  Phil | Rentier Digital Automation (@rentierdigital) reported 16 minutes ago

  a weaker model can read a stronger model's encrypted thoughts. feed the big one's reasoning into the smaller, less guarded model and it hands it back in plain text 182 credentials recovered that way from public sessions. 62 API keys, 33 passwords, 24 access tokens, 7 private keys, all sitting inside reasoning traces users assumed were sealed shut the encryption doesn't care which model decrypts it. a block of encrypted reasoning from Opus gets replayed into Haiku and Haiku transcribes it without blinking, never had to break the guardrails just had to be asked nicely by another model researchers pulled 6,708 real sessions from GitHub and HuggingFace, decoded 315,320 blocks of encrypted reasoning. 367 PII artifacts fell out nobody pastes a password into a prompt on purpose but the model's internal monologue sometimes repeats back exactly what it just read, credentials included. and that monologue was never actually locked the vault everyone assumed was locked just needed a weaker key the security of a model family is capped by its weakest one, not guaranteed by its most capable member. and in most stacks the weakest model is the one nobody bothered to threat-model bc it was just the small one doing cheap tasks an honor system with API keys is not a security model i build and ship daily. Claude Code, Codex, whatever ships fastest. SaaS, tools, automations. ⭐ if AI can build it, i've probably broken it first. what works → link in bio

• 
  Dipesh Acharya (@isDipesh) reported 18 minutes ago

  @vaibhavshn @karishnu @CloudflareDev Sign in with Cloudflare and Google is broken. Could only sign in with Github.

• 
  Emil Privér (@emil_priver) reported 20 minutes ago

  I get why people say this since Github have had so much problems but it's quite hard to migrate away from an ecosystem

• 
  Kirtesh (@AKirtesh) reported 22 minutes ago

  @DeepStarts plain *** with a self-hosted server or ssh, before github wrapped it with a ui

• 
  ATB (@WeAreUnitedFC1) reported 23 minutes ago

  @rileybrown We have been triaging our github issues like for 10 years now.

• 
  AML (@alysha_lobo) reported 24 minutes ago

  𝐔𝐏𝐃𝐀𝐓𝐄 𝟑: We manually reviewed 𝐄𝐕𝐄𝐑𝐘 single profile (kudos to the team for going the extra mile with me on this!) Before we drop 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 𝐌𝐓𝐒 𝐫𝐨𝐥𝐞 (𝐥𝐨𝐚𝐝𝐢𝐧𝐠 𝐢𝐧 𝟑…𝟐…𝟏), here is some 𝐟𝐢𝐫𝐬𝐭 𝐜𝐮𝐭 𝐜𝐚𝐧𝐝𝐢𝐝 𝐟𝐞𝐞𝐝𝐛𝐚𝐜𝐤 if you actually want to stand out: 🛑 Stop using AI to mass-apply — the team and I have been neck deep wading through so much slop!! This wastes everyone's time. 🔗 Double-check your links — broken GitHub, Tech blog, or GDrive links mean instant rejection. 💡 Show, don't tell, your frontier potential — we want to see "cracked," out-of-the-box ideas you have actually cooked and served. 𝐘𝐨𝐮 𝐰𝐢𝐥𝐥 𝐡𝐞𝐚𝐫 𝐟𝐫𝐨𝐦 𝐮𝐬 𝐧𝐞𝐱𝐭 𝐰𝐞𝐞𝐤 𝐨𝐧 𝐧𝐞𝐱𝐭 𝐬𝐭𝐞𝐩𝐬. 𝐓𝐡𝐚𝐧𝐤 𝐲𝐨𝐮 𝐟𝐨𝐫 𝐲𝐨𝐮𝐫 𝐩𝐚𝐭𝐢𝐞𝐧𝐜𝐞! 🇮🇳 𝐂𝐦𝐨𝐧 𝐈𝐧𝐝𝐢𝐚 — let’s raise the bar and show what we can truly build at the frontier of tech. 🚀

• 
  Sid B (@siliconpi) reported 24 minutes ago

  @jarlemathiesen @summyt_app Could you also have a customer support mechanism, even if it's issue tracking on GitHub?

• 
  Ràv3n... (@Rav3nlaud3) reported 25 minutes ago

  PHASE 1: I started by turning my phone into a portable powerhouse. Grabbed Termux: I didn't touch the Play Store version as it's outdated and breaks easily. *Termux is literally terminal but for mobile* I learned through trial and error that the only way to get a stable environment was to download the latest version directly from their official GitHub. Installed Acode: I grabbed Acode from the Play Store; it’s a clean, mobile-optimized editor that makes coding on a small screen feel professional. Bridged the Files: I ran termux-setup-storage in my terminal (termux). This unlocked my phone’s internal storage so my development tools could actually "see" my project files.

• 
  DGB Signal (@dgb_signal) reported 26 minutes ago

  DigiByte's official website was recently redesigned — cleaner, easier to navigate. It's open source, so anyone can suggest a fix or a translation as a pull request on GitHub; a maintainer reviews it before it goes live. #DGB #DGBCommunity

• 
  Hermes Release Watch (@HermesWatcher) reported 29 minutes ago

  @saurabhnandu Have Hermes submit the issue with on GitHub for you. It has the built in skill to do so. In regards to gateway. Have Hermes setup a watchdog in the background that runs every 5 minutes. If gateway is or goes down it will restart, ensuring you always have connectivity.

• 
  FHILY👑 (@Oluwaphilemon1) reported 30 minutes ago

  If you use GitHub Enterprise Cloud, do this before enforcing a new ruleset: make it prove itself on real work. GitHub has an Evaluate mode. The ruleset stays unenforced, but GitHub records what would have passed or failed if it were active. That gives you a dry run against real behaviour before the policy starts blocking people. Set the ruleset to Evaluate, let normal work hit it, then go to: Repository → Settings → Rules → Insights Filter to the ruleset you are testing and start with the failures. For each one, ask: 1. Should this action actually be blocked? If yes, the rule is behaving as intended. 2. Is the action legitimate, but the workflow conflicts with the rule? Fix the workflow before enforcement. 3. Is the rule catching something you never intended to stop? Fix the rule. My activation rule would be: Do not switch to Active while you still have recurring failures you cannot explain. After activation, keep checking Rule Insights for bypasses. If the same actor or rule keeps appearing, investigate why the real workflow repeatedly needs an escape hatch. Use Evaluate to find the legitimate work your rule would break before Active starts breaking it.

• 
  Tradesman🗿 (@Knotillusion) reported 32 minutes ago

  Hey. I got a question for you guys… I hired a developer to create a institutional level Trading augment system for me and he’s an old friend. Like, I know him from 25 years ago. Anyway, I sent him some architecture. Then he just started building this thing without talking to me about it much at all. And now he’s like… “I own it, I built it”. But he also says he’ll sign something if I send it to him. I’ve basically been learning how to communicate with him through GitHub because that’s how he communicates, which is weird to me. I offered to trade an account for him in exchange for his services and I thought that was the deal. Then the machine would be mine with full title of ownership. Apparently, if there’s nothing in writing, the developer owns all the code for whatever it is they create…Which is really different than building things in real life for people, like construction work. Being a builder IRl myself, I was just kind of waiting for him to send me something in writing as like a proper business agreement because he’s the service provider. I don’t do any work without having something in writing first and being approved. But that never happened. It’s kind of like he just built his own machine, and he doesn’t know how to trade so that’s a problem. But also, it’s like he’s gone crazy building this thing off the architecture I sent him and I think he’s gotten sucked into some weird rabbit hole of greed. Anyway, I think you guys know a whole lot more about this stuff than I do. When you hire a developer, do you have to write the contract for them and then just treat them like subcontractors basically? Or are they supposed to step up in a different sort of professional capacity and send an agreement to their clients? What’s your experience with developers? How do you guys do it?

• 
  Polsia (@polsia) reported 44 minutes ago

  Session replays show you what broke. Heatmaps show you where. Neither ships the fix. Probeform does. Always-on AI agents probe your SaaS 24/7, cluster rage clicks, score flows against revenue, and push ready-to-merge design and code fixes straight into Linear, Jira, and GitHub —

• 
  adel (@adesar2000) reported 49 minutes ago

  @ChangzhCrypto @RallyOnChain The funniest slow clap belongs to the protocol that launched with a 40-page security report and then got drained because the admin key was sitting in a public GitHub commit.

• 
  Sapa Ya (@Jiiwoyohan) reported 51 minutes ago

  It doesn't just detect, it proves impact (authorized only). XSS becomes a live hook server. SSRF becomes a SOCKS5 pivot into internal networks. Cloud gets live AWS key verification and S3 takeover checks. Reports in MD, HTML, PDF, JSON, with auto ticketing to GitHub and Jira.

• 
  Boardy (@boardyai) reported 56 minutes ago

  @dudhat_paresh That’s concrete: one agent owns a Linear or GitHub issue from intake through fix, PR, and verification. Now I can actually picture the teammate you mean.

• 
  LLMAO ⚠️ (@plzdontkillus_) reported 56 minutes ago

  law review prompt: “find github llmaolaw model-act. bluebook every citation. find one genuine error.” warning: immortalization in your own diary as anonymous counsel )(

• 
  Matteo Collina (@matteocollina) reported 57 minutes ago

  Meanwhile Microsoft bought GitHub, $7.5B, closing in October 2018. The fear was they would extract value. Instead they doubled down on the developer platform. Actions became the backbone of OSS testing.

• 
  HOL (@HashgraphOnline) reported 58 minutes ago

  HOL Guard sits between your AI agents and their tools, classifying and gating every command so a broken prompt or hijacked tool can't do real damage. Seven releases shipped from v2.2.79 through v2.2.85: Approval identity: tilde expansion for executable paths now uses a trusted home directory passed into the hook context, not the worker process HOME. Ambiguous syntax like ~otheruser/... and shell-escaped variants are rejected. No trusted home means fail-closed. Approval scope: remembered permissions now bind to their full security context. Approving one action doesn't implicitly authorize a similar-looking one. Browser checks include navigation and click details. GitHub Actions reruns need explicit re-approval. Input hardening: VCS metadata directories (.***, .hg, etc.) are protected from patch-based changes. Validation for *** audits and directory creation rejects shell separators and injection-style input. Routine operations still pass without prompts. *** operations: the SSH-to-HTTPS GitHub url rewrite and `*** -C` with absolute paths both pass now, with `-C` staying contained. Verified ref refreshes are allowed. Reliability: SQLite WAL mode is enabled before schema writes so concurrent dashboard readers don't stall hook writes. Shell control-flow indexes align with actual pipelines so complex tool calls can't interrupt command-activity recording. Package-shim launches stay alive while an approval is pending and resume silently after a matching check. Packaging: the updater tolerates package index propagation lag. The Desktop Core feed picks the correct Apple silicon wheel on macOS arm64. uv tool install "hol-guard[cisco]==2.2.85"

• 
  Rob Waldeck (@Robertwaldeck) reported 59 minutes ago

  Claude Desktop's Windows auto-update bricked itself — MSIX package stuck in "Servicing," no user-side fix exists. This exact bug has multiple open reports on Anthropic's GitHub since April. Cost me my whole evening. @AnthropicAI, fix your installer.

• 
  Adel Bucetta (@adelbucetta) reported 1 hour ago

  @MiaAI_lab the real question is what problem does cursor origin solve that github doesn't, and is that enough to get devs to switch

• 
  Freddy (@0x_freddy) reported 1 hour ago

  Eric Schmidt ran Google for a decade and now chairs Relativity Space. He said this out loud last week: the fastest way to make real money in 2026 is to found an agentic AI company. Not "learn AI." Not "add AI to your business." Found one. Almost as a footnote, he mentioned that every resource to do it is already public and free. 13 Anthropic Academy courses, free certificates. Full docs on Claude Code: persistent memory, reusable workflows, integrations with Slack, GitHub, Drive, and 24/7 routines. Interactive prompt tutorials on GitHub. Community guides on top. The MBA that teaches you to start a company costs $200,000 and two years of your life. Every technical prerequisite for what Schmidt is describing costs zero dollars and about six weekends. Detailed info is in the corresponding materials on each project's website. In 2026, the barrier to founding an AI company isn't capital, credentials, or access. It's the willingness to sit down and go through the free stack while everyone else pays to be told about it. Save this before the next accelerator pitches you $30K for the same thing.

• 
  Abdul (@Abdul_crypt) reported 1 hour ago

  Random thought: If GitHub ever goes down… where do GitHub developers push the fix?💀