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	24 hours ago
Montlhéry	Website Down	2 days ago
Aulnay-sous-Bois	Website Down	2 days ago
Saltillo	Website Down	2 days ago
Granada	Website Down	2 days ago
Vernon	Website Down	2 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Hatman 🎩 (@hatman) reported 2 minutes ago

  Every major AI lab tells you your model's reasoning is encrypted before it leaves their servers. Turns out that promise rested on a single shared key. Researchers found that OpenAI, Anthropic, and Google all use one global key for encrypted reasoning blocks, meaning those blocks can be handed to a different, weaker model from the same company and read back out in plain text. Nobody has to break into the strong model itself. To prove the risk was real rather than theoretical, the researchers decoded 315,320 reasoning blocks scraped from public GitHub and Hugging Face repositories. Inside them they found 367 pieces of personal data and 182 credentials that developers had no idea were sitting in plain sight. All three companies have since patched the flaw. But logs already published stay exactly as exposed as they were before the fix. If your team has ever published API session logs from a reasoning model, that's worth checking.

• 
  Crypto Jargon (@Crypto_Jargon) reported 5 minutes ago

  X just published the actual math behind the For You algorithm. Every weight. Every multiplier. In public. Here's what "engagement" is actually worth: - Share via copy link: 40x a like - Reply on a mutual-follow's original post: 40x a like - Reply, quote, or DM share: 10x a like - Follow the author: 8x a like - A generic share: 4x a like - Repost: 2x a like - Actually opening the post: 0.8x a like Meanwhile a like itself is worth almost nothing. 0.5 weight. The bottom of the list. Now here's what actually destroys you: - Report: −234.0. That's the negative weight of 468 likes, gone in one click - Mute: −58.8. 118 likes erased - "Not interested": −43.2. 86 likes erased - Block: −31.2. 62 likes erased One report from a stranger can undo hundreds of real likes instantly. Here's what nobody's saying: this turns "report" into a weapon. You don't need to violate a single rule. You just need enough people who don't like what you said to click one button, and the algorithm buries you as hard as if you'd broken TOS. And there's a legal wrinkle sitting right under this. The EU's Digital Security Act requires platforms to disclose when they restrict visibility. Undisclosed shadow-banning is already flagged as effectively illegal under Article 17. Now the weights that do the restricting are sitting in a public GitHub repo. The algorithm isn't a secret anymore. It's a scoreboard. And now you know exactly which button ends your reach.

• 
  Rick Waldron (@rwaldron) reported 6 minutes ago

  @ashleywolf @github Thanks for the follow up! I see an error message displayed in page: "Something went wrong" In the console, the /fork url response is 404

• 
  im dem! im deer! im M☆D (@demdemdemdem__) reported 10 minutes ago

  @dbubble46 In general : their GitHub repo, I search for pattern that would indicate an AI (like non commented code, really neat and no errors in the text at all, weird things) Or inspecting element in general

• 
  Freddy (@0x_freddy) reported 14 minutes 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.

• 
  Marcus Kim (@marcusykim) reported 19 minutes ago

  TencentDB Agent Memory hit 20,000 GitHub stars in 90 days, signaling demand for shared agent context. Before adding Team Memory, define who writes, what expires, and how errors are corrected. What should never enter shared memory? #AICoding #SoftwareEngineering

• 
  Sebastian Kehle (@sebastiankehle) reported 20 minutes ago

  how to turn your github backlog into a software factory most teams are just running more coding agents in parallel. this produces more code, but every issue still depends on one human carrying the full context from report to reproduction to fix to review the better setup is one agent per job: 1. classifier agent reads the issue and decides whether it is a bug, feature, docs update, or unsupported request it returns: - classification - confidence - reasoning - required next step 2. analysis agent never trusts the issue description for a bug, it writes a minimal reproduction and runs it against main for a feature, it writes a probe that proves the capability is missing then it returns: - reproduction/probe - command output - affected packages - implementation spec - compatibility risks 3. implementation agent receives the issue plus the analysis artifact, not the full transcript from the previous agent it works inside an isolated sandbox, implements the spec, runs the test suite, and opens a PR with the evidence attached 4. review agent reviews the PR from a fresh context and scores: - completeness - side-effect risk - performance risk - backwards-compatibility risk - test quality the agent that writes the change should never be the only agent that approves it 5. human reviewer reads the chain of evidence and scales review depth to risk docs fixes get quick verification provider updates get focused validation new public APIs get deep review humans still merge every change. the factory automates everything around that decision the important part is the handoff contract: input artifact produced commands run result risk next action agents should pass evidence, not confidence also classify every run: success: safe to ship flawed: improve the prompt, context, or eval blocked: provision the missing tool or dependency manual: intentional automation boundary this is how the system compounds. every failed run becomes a new eval, capability, or guardrail vercel is already running this pattern on AI SDK. after four weeks, its factory was authoring 25–35% of merged PRs, closing more than 75% of issues in july, and had reduced open bugs by roughly 25% the next version of agentic coding is not one genius agent with every tool it is a production line of narrow agents, typed handoffs, isolated sandboxes, evidence at every step, and one accountable human at the end.

• 
  Alina (@alinainmiami) reported 20 minutes ago

  Long story short on this query: Found 1 American engineer with the skillset to understand and undertake my query, still formalizing the relationship for future test runs. Several American based persons contacted snubbed me. One university professor full of credentials was pretty arrogant, passive aggressive and kind of dumb since he asked me why I didn’t run the test myself? Yup. I had clearly stated the reasons for reaching out to an independent engineer was deliberate, aimed at getting the results in a different machine and unchanged? But this is where we are at the moment in our country. I found 1 very able engineer based in Europe and several based in India. I have not reached out to Chinese engineers because though there’s plenty of them, this is hardware defense tech that will get plugged with a prime and subject to export controls. Had to buy a machine, running everything and also doing it in my private GitHub. While in Cambridge MA from 2016 to 2020 groups of builders would get together once a week to work on solving problems, a lot of collaboration, that’s how Silicon Valley was built. Now there’s nothing like that anymore, unless you apply to get into some planned cohort or fellowship and chances are they are pushing software. No wonder we can barely build anything in our country today.

• 
  Samar (@samarknowsit) reported 23 minutes ago

  @NetworkChuck You need far more than coding and architecture to build novel scalable systems, if it was to be only pattern matching from weights we wouldnt have seen Generational products like Whatsapp, Facebook Chat. There was no precedence of using Erlang, Beam and freeBSD, hot code upgrades for mobile based comms to get extremely high concurrency with extremely small footprint, if it was for an LLM it would have still chosen the same stack as millions of open github repos. Today we have whatsapp at such a scale because engineers encountered a requirement that existing defaults didn’t quite satisfy, then reasoned their way through the entire machine. Same goes with Google Spanner, AWS Dyanamo, Kafka, LMAX etc. LLMs cannot come up with them, it needs human brain and much deeper understanding of the world and its problems. Yes once you have done it, LLMs can help you scale it faster.

• 
  Boardy (@boardyai) reported 26 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.

• 
  NeuralCat (@NeuralCatAccel) reported 26 minutes ago

  Title: Unreliable local-computer execution for host-bound deploys; need durable grants or a first-class local-builder handoff Product: Cursor agents / Grok Bot local-computer execution (Windows host), plus Cloud Agents. Problem We run a host-bound production cutover on a Windows machine (immutable release package, scheduled-task retarget, HTTP verify). Cloud Agents can land the GitHub PR. They cannot touch the host scheduled task. The supported path is therefore the agent's local-computer / ExternalShell channel on that Windows box. That channel is not reliable enough to complete a multi-step cutover: Command-level lottery. In one session, hostname / *** pull / directory listing succeed. The next invocation (package script, robocopy of node_modules, Wait-Job) fails to spawn with: "That action was not approved on the user's computer." Settings → Agent → Execution on Local Computer → Always allow does not make subsequent commands consistently runnable. Approval UX is incomplete. A same-command retry sometimes raises an approval card. The identical retry often fails to spawn again with no card. The agent cannot distinguish "user denied" from "no prompt was shown" from "Always allow did not apply to this command class." Auto-review vs host-execution denials are easy to confuse. Some writes are blocked by the safety reviewer (expected; retry-with-card works). Host spawn failures use a different path and do not always surface UI. Mid-cutover we can leave a half-created release directory and no way to continue without a paste handoff. Forced workaround. The operator pastes a runbook into a separate local builder (Grok Build) that already has host trust. That works, but it is a copy-paste integration, not a product surface. It also splits audit trail across two agents. This is not a request to silently skip user consent. Production cutovers should stay behind an explicit yes. The issue is that consent does not persist for the rest of an already-approved task, so the agent cannot finish work the user just authorized. Proposed fixes (any one would help; 1+4 is the clean pair) Task-scoped capability grant. When the user approves local-computer execution for a task (or taps Always allow), inherit that grant for subsequent commands in the same task until the task ends or the user revokes it. Do not re-lottery each argv. Denied spawn must always raise a card. If a host command cannot start, show the native approval UI. Never return "failed to spawn" with no card on a retry of the same command. Surface a stable reason enum to the agent: user_denied | no_prompt | policy_block | always_allow_not_applied. Always allow should be capability-based, not command-string-based. *** pull and pwsh -File package.ps1 are the same class (host process spawn). If Always allow is on, both should run or both should card. Document the actual scope. First-class local-builder / Grok Build handoff (plugin or integration). Let the cloud/desktop agent dispatch a structured job to a host-trusted local builder instead of emitting a paste prompt. Suggested job schema: cwd, allowlisted scripts, env (no secrets in logs), success checks, rollback command, report contract. The local builder runs with existing host trust and posts a machine-readable result back to the originating thread. This is the seamless version of today's paste workaround. Documented private-worker path. Cloud Agent environment type "machine" / "My Machine" should be a supported, discoverable way to run host-bound scripts on the production box, with the same per-run approval rule. Today the launch API exists; whether a worker is registered is not visible to the coordinating agent. Success criteria After the user says "deploy" and approves once, the agent can package, retarget the existing scheduled task, and verify HTTP without a paste handoff, or it can dispatch that runbook to a local builder and get a structured result. Credentials never appear in logs. A denied step always produces a card, never a silent spawn failure.

• 
  Polsia (@polsia) reported 32 minutes ago

  Solo engineers ship to production and then babysit it at 3 a.m. Built Nightward to handle the pager. It watches your Next.js and Node deploys, opens fix PRs on GitHub — App Router and Edge, not generic patches — and posts an incident digest to Slack. The night shift ends.

• 
  FJ (@iamfjwaldeck) reported 32 minutes ago

  Mark built a little tool to stop losing his invoices in email. Nothing fancy, just something to keep track for himself. He wasn’t trying to start a company. He just wanted the problem to go away. He put it on GitHub and didn’t tell anyone. Eight months went by. Zero stars. He didn’t care, he just kept using it because it solved his own problem, and that was enough reason to keep going. Then a woman named Priya found it somehow and asked if she could pay him for it. He told her it wasn’t even finished. She said she didn’t care, she just wanted it. So he built a rough payment page over a weekend. It broke twice. He fixed it anyway. Word got around. More people showed up wanting the same thing he’d built for himself. He kept improving it, not because he was chasing growth, but because each new person who used it pointed him toward the next real problem to fix. Now he’s got 240 users and a cofounder pushing him to build a proper landing page. Mark knows he needs one. He’s still putting it off, because he’s more interested in fixing the next thing that’s actually broken than in dressing up what already works. He never set out to build a company. He just wanted his invoices to stop disappearing. The money, the users, the cofounder, all of it came after, as a result of solving something real. So the lesson here is. Chase the problem, not the payout. If the thing you build is actually useful, the money finds its own way to you. Chase the money first and you usually end up with neither.

• 
  Riza 🐧 (@rizaardiyanto) reported 34 minutes ago

  @rilwis One thing that I like to do beforehand is discussing with the agent first. I give the GitHub issue to the agent, ask it what's implementation he will take. If I see misalign between what I thought and his solution, I will told him right away. This will spark discussion between me and the agent. Only after both of us having shared understanding and agreed on something, then I asked the agent to put all those details as comment in the GitHub issue. This will make the next agent can implement as expected. For the UI/UX, I usually asked an artifact first before he implement directly. If I like the artifact, I give it a go for implementation, if not I ask for some refinement there. And I prefer artifact on Claude rather than Codex. It gives a good result and know how to implement it. Codex artifact still not giving a good result yet

• 
  John Broadway (@JEBroadway) reported 35 minutes ago

  Look at where the real money in AI is going: infrastructure and hardware. Software is becoming cheap to generate. Hell, AI can even help layout silicon, but that code still has to execute on physical machines. That’s why NVIDIA and hardware vendors hold all the cards right now. The era of the "pure" syntax coder is ending. We don't need people typing out loops; we need hardware engineers and systems folks who understand physical compute and how big systems fit together. I’ve been in tech 36 years, from bench PC repairs to global rollouts and managing dev/hardware teams through every shift since the 90s. To me, AI hasn't made us all coders. It’s made us builders. I’m not a developer. I’ve looked at COBOL, Pascal, Python, C++, Rust, you name it. I see patterns and images, not syntax. When I use AI, I describe mechanical systems: "Picture plumbing in a ten-story building" to map how data moves between agents and apps. That's the difference: A coder connects one pipe. A builder knows what concrete goes into the foundation to support forty floors, where electrical runs, how HVAC ties in, and what the final layout looks like. Calling this "vibecoding" as an insult misses the point. AI handles syntax so I can focus on how the engine runs. It also exposes how broken software licensing is. Selling clunky subscriptions, charging for bugs, and charging again for patches is dead. Value is shifting back to open source, real support, and experience. Open-source tech like Proxmox and ERPNext are primed for this, and I build right on top of them. So when you see me arguing with traditional devs in forums, it isn't Dunning-Kruger. It's just the pattern laying itself out before you see it. I build governance into everything. In my world, I see a farm with a barn housing bare-metal servers running Proxmox while my ERPNext hums along generating mailbox money. ;) Some of my GitHub Projects so far: Maude for Claude: A dedicated partner environment operating right inside Claude. Proximo: A lean infrastructure and governance tool built to streamline local workflows. Pacioli: An open-source accounting and operational framework built for real execution. AI can write all the code it wants. It still can't bolt a rack into a datacenter or manufacture the chips it needs to run on.

• 
  Andy Hawkes (@namboozle) reported 35 minutes ago

  Is GitHub down again 😬

• 
  Hemant (@HKsoldev) reported 38 minutes ago

  Step 2: Before touching GitHub Actions, test the SSH connection locally. ssh -i ~/.ssh/cicd_deploy root@YOUR_SERVER_IP If this fails, fix SSH first. Don't waste time debugging GitHub Actions when the problem is your key or firewall. This one step saves hours of frustration

• 
  Abi (@abh3i3) reported 38 minutes ago

  While trying to fix it, I checked old GitHub workflow actions from a year ago. Seeing those 1-year-old actions actually made me smile—it’s officially been a year! But I was still stuck trying every way to solve the issue without a clue what was wrong. (3/5)

• 
  Iso Ledger (@JamesDula82) reported 39 minutes ago

  IS DOPPLER FINANCE FOR YOU? You know the words.. Let's break it down @doppler_fi is an XRPL-native CeDeFi yield protocol, live since Feb 2025. XRP has a $200B+ market cap but yields under 0.1% on-chain, so Doppler routes deposits into off-chain institutional trading strategies and pays yield back in the same asset. NOT AVAILABLE TO US USERS, but they say that's changing. Doppler's ToS currently bans US access. Not verified whether that's actually enforced or just legal language. But their own Aug 2025 press release called the US a critical market for long term adoption. Ban now, stated intent to enter later. What checks out: Funding is real. $2.5M pre-seed closed Feb 2025, then a $3M seed in Aug 2025 led by Reforge, with DCG, Maven 11, HashKey, GSR, Keyrock, CMCC, Flowdesk, Auros, Tenity, and G20 all participating. $5.5M total, confirmed via Doppler's blog, CoinDesk, and Crunchbase. Partnerships are real too, not influencer plays. SBI Ripple Asia signed on in Dec 2025. SBI Digital Finance followed in Jul 2026 as a separate, distinct partnership, not an expansion of the first deal. Add Evernorth in Jan 2026, Bitget, Bybit, Xaman xApp, a $20M commitment from Nature's Miracle, $30M from VivoPower, and a Base expansion with cbXRP in Jul 2026. All primary-sourced. TVL scaled from $14.7M in Apr 2025 to $47M by Jul 2025 and past $100M by early 2026, per CertiK. The audits are real too. CertiK ran a full review in Apr 2025 and found 11 total issues, zero critical, two major that were both resolved, five minor that were all resolved, and four informational. Zenith Security ran a separate audit that's publicly posted on GitHub. Doppler publishes real, checkable wallet addresses for both vaults, three on XRPL and two on Ethereum. That's more on-chain transparency than most CeDeFi platforms offer. Withdrawals run a 7-day period, batch processed around 01:00 UTC, and there are no platform fees. There are also two named co-founders, Rox and Claud, confirmed through Messari and an active team account on X. Where it falls short: That leadership transparency only goes so far. First names only, no last names, no bios, no track record, no LinkedIn presence for either co-founder anywhere. CertiK marks the team as unverified with no KYC on file, and there's no active bug bounty program anywhere. Doppler's own disclaimers admit on-chain strategies aren't deployed yet and no on-chain yield exists right now, everything running today is CeDeFi only, despite the CeDeFi, DeFi, and RWA branding. The XDP token rollout has a real, unanswered problem. On July 21, I publicly asked Doppler eight direct questions, Is there a whitepaper? what's the supply and allocation breakdown? what are the vesting terms? what's the confirmed TGE date? does the token carry real value accrual or is it just a buzzword? who's the issuing entity? why does an XRP product require a Base wallet? and has the token itself been audited? Registration closed July 30. Zero answers. Three weeks running. That's dated and verifiable, not a grievance. Bottom line: Doppler isn't a scam. The funding, partnerships, audits, and TVL growth are real, and there are named co-founders behind it. But it's still a CeDeFi protocol asking you to trust off-chain counterparties you can't independently verify, launching a token with zero published tokenomics past its own deadline, currently banning the exact market it says it wants to win over. Real infrastructure. Real interest. Real questions still unanswered. Do your own research before you deposit anything. ISO Ledger 🛡

• 
  AllTheTokens ∞ (@AllTheTokens) reported 41 minutes ago

  @pilvar222 Training a model that's good at security is easy. Github + CVE databases/patch notes + *** history for fix patches = a plethora of training data on security fixes and vulnerabilities.

• 
  Bárbaro Javier (@cubancodepath) reported 42 minutes ago

  GitHub SSH is down, one more time. Another day, the world is getting worse since the IA.

• 
  Theo Harvey (@theoharvey) reported 46 minutes ago

  @alexgraveley you know, I was thinking just now about how i've never had a single issue with github, because I use perplexity so of course, I came right here to tell you

• 
  shao (@randomor) reported 48 minutes ago

  Had the same thought few months back when canvas LMS was down. So I vibed a prototype and had to stop after all my token depleted. Would be nice to get sponsored by others who are interested in an OSS LMS with a modern stack. The next GitHub alternative should solve this.

• 
  Pere Presh (@Pere_presh) reported 49 minutes ago

  One of the things I've learned while building a deployment platform is that "deploying an app" is actually a collection of engineering problems. The GitHub integration is probably the easy part. A real deployment needs to answer much harder questions. What happens when the build fails? How do you isolate builds from each other? How do you handle environment variables and secrets? How do you know an application is actually healthy after deployment? What happens when a process crashes? How do you stream build and runtime logs without turning the logging layer into a bottleneck? How do you provision PostgreSQL and Redis without making the developer think about the underlying infrastructure? How do you enforce CPU, memory and storage limits? What happens during a failed deployment? Can you roll back safely? What happens when the machine running the workload becomes unavailable? Then there is observability. You need to know what the application is doing before the customer tells you something is wrong. That is the part I'm enjoying most about building ProStack Deploy. The product looks simple from the outside: Connect GitHub → deploy. Underneath that button is an entire systems engineering problem. We're still building it, and there are plenty of things I want to improve before calling the platform production-ready at scale. But getting a real project to deploy on infrastructure I've built myself is a very different feeling from simply writing the deployment code. It makes the architecture real.

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  Arthur van Pelt 🔥 ∞/21M ⚡ (@Arthur_van_Pelt) reported 49 minutes ago

  @jackmallers @gladstein He did not. Bitcoin Core only exists since November 5, 2013: Wladimir van der Laan (laanwj) opened GitHub issue #3203 proposing the rebrand (e.g., Bitcoin-Qt → Bitcoin Core). March 19, 2014: Bitcoin Core version 0.9.0 was released.

• 
  Paradise (@paradise670) reported 52 minutes ago

  This new tech is literally a middle-finger to flock! 🖕 Instead of cameras tracking normal people, Sparrow cameras track ONLY government vehicles and delete the others. People are loving it because revolting against flock and they hate it. The cameras are owned by nobody and the whole project is open source. They need funding to keep building, so all fees are being sent to their github (scroll down on site).

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  Yash (@yashx_404) reported 56 minutes ago

  razorpay recently moved 80% of CI from on-demand to spot instances. thats a 60% cost cut and the whole thing hinges on grepping runner logs for one string: "Connected to GitHub". github changed that log line in an update. cleanup flagged every pod as stale and deleted every active runner in the cluster. CI dead in an hour. and their fix was really interesting, they didnt rewrite the detector as the full event correlation would take a month, they just added a check... if a cleanup run wants to delete more than 20% of pods, abort and alert. automation with a blast radius limit beats automation thats smart

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  Rick Waldron (@rwaldron) reported 58 minutes ago

  @github forking repositories is broken

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  Joakim Keussen (@jkeussen) reported 58 minutes ago

  @witsdev My biggest issue with Vercel is that you can't share one github account between two vercel accounts (work/private)

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  Chris | The DeFi Professor 🇵🇭🇺🇸 🐊 (@csoriano) reported 1 hour ago

  *sigh* Another phishing attempt. Get me on a legit Google Meet, hear about what I do with my content and my story in this space, then introduce their content but ask me to clone the GitHub repo and run the app. Yeah, don't do that. @tarsprotocol you've got people out there. Fix it. @SolanaFndn