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 (57%)
• Errors (30%)
• Sign in (14%)

Live Outage Map

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

City	Problem Type	Report Time
Inverness	Website Down	3 days ago
Quito	Sign in	3 days ago
Junín	Errors	3 days ago
Guadalajara	Errors	3 days ago
Paris	Website Down	3 days ago
Quito	Errors	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.

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:

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  Google G-Ware Surface Technology (@GoogleWaveTech) reported 6 seconds ago

  Matt was having a wife told to GitHub at the time I was saying or reading GitHub take down to destroy Bitcoin.

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  Dom_Parser (@DomParserX) reported 38 seconds ago

  @iamigorekk The problem is your entire data pipeline runs on prompt engineering and a dream. Drop the GitHub commit hash for the WebSocket handler or admit you're just prompting Midjourney for UI mockups, bro.

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  Joshua (@Joshua_z0310) reported 51 seconds ago

  How to start your solo business with AI tools ChatGPT / Claude = ideation, writing, research. Cursor / Windsurf = coding and debugging. Supabase = backend and database. Vercel = hosting and deployment. Namecheap = domain. Stripe = payments and subscriptions. GitHub = code hosting and version control. Resend = transactional emails. Tally / Typeform = forms and lead collection. PostHog = product analytics. Sentry = error monitoring. Cloudflare = CDN and DNS. Upstash = Redis and rate limiting. Pinecone = vector database. Loom = screen recording and async updates. Notion = docs, wikis, and SOPs. Slack = communication. Canva = design and branding. Billbooks / Wave = simple accounting. The idea is simple: one person can now use AI plus low-cost SaaS tools to cover product, development, deployment, payments, marketing, analytics, operations, and support—without building a large team from day one. #AItool #AI #productivity

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  mRr3b00t (@UK_Daniel_Card) reported 10 minutes ago

  Dan's daily threat briefing: Today is August 20, 2026. Let me gather intel across the categories in parallel. Searched the web, updated tasks · 4 notes Sent notification 4 actively-exploited flaws hit CISA KEV (Aug 18) with an FCEB deadline of TOMORROW, Aug 21. Highest priority: VMware vCenter CVE-2026-59310 (9.8, path-traversal RCE) — suspected China-nexus APT dropping backdoors and Babuk-derived ransomware across 361 victims/47 countries; and Windows IKE CVE-2026-33824 (9.8, network RCE double-free). Also SharePoint CVE-2026-55040 (9.1, PoC public) and macOS Screen Sharing CVE-2026-65400 (9.8, auth bypass → cryptominers). Patch/isolate vCenter and apply Aug Patch Tuesday now. Separately: Cisco published two CVSS-10.0 advisories Aug 19 (Crosswork, Secure Workload), and the "Shai-Hulud" npm worm (keyv/cacheable, 400+ packages) is still active — rotate CI/CD and cloud creds if exposed. Full briefing in session. Daniel's Daily Threat Intel & CVE Briefing — Thu 20 Aug 2026 Top of the stack: CISA added four actively-exploited CVEs to KEV on Aug 18 with an FCEB remediation deadline of tomorrow, Aug 21. The one to move on first is VMware vCenter CVE-2026-59310 (9.8) — a suspected China-nexus APT is using it for unauthenticated RCE, dropping reverse_ssh backdoors and Babuk-derived ransomware (361 victims across 47 countries). Windows IKE CVE-2026-33824 (9.8, network RCE) is close behind. If you run vCenter exposed or unpatched, isolate/patch it today. 1. CISA KEV / Actively exploited (all four added Aug 18, deadline Aug 21) CVE-2026-59310 — Broadcom VMware vCenter, CVSS 9.8, exploited. Path traversal → unauthenticated arbitrary code execution. Suspected China-nexus APT deploying backdoors + Babuk-derived ransomware; ~361 victim IPs/47 countries. So what: crown-jewel virtualization infra with in-the-wild ransomware chains — patch or network-isolate now. CVE-2026-33824 — Microsoft Windows IKE Service Extensions, CVSS 9.8, exploited. Double-free → unauthenticated network RCE. Reported use by a Chinese-speaking actor running AI-assisted intrusion campaigns. So what: wormable-class network RCE on Windows; ensure Aug Patch Tuesday is deployed. CVE-2026-55040 — Microsoft SharePoint Server, CVSS 9.1, exploited (public PoC). Weak-authentication security-feature bypass over the network. So what: SharePoint remains a repeat initial-access target; prioritise internet-facing farms. CVE-2026-65400 — Apple macOS Screen Sharing, CVSS 9.8, exploited. Improper authentication → network auth bypass; observed dropping Monero miners. So what: patch macOS fleet and disable/segment Screen Sharing where not required. 2. Edge / network gear Cisco (published Aug 19) — two CVSS 10.0 hardening advisories: Crosswork (CVE-2026-20030/-20357/-20358/-20359) and Secure Workload (CVE-2026-20231/-20315/-20317/-20318/-20319); plus High BroadWorks XXE CVE-2026-20320 (7.5). No confirmed in-the-wild exploitation yet, but these are max-severity — schedule upgrades. So what: management-plane and workload-security appliances at 10.0 are prime pivot points. No new Fortinet/Palo Alto/Ivanti/Citrix/SonicWall/F5 critical in the last 24–48h that corroborated against a primary source. (The Fortinet FortiSandbox / Ivanti Sentry criticals circulating in search are from June 2026 — not today's news.) 3. Microsoft / Windows / Active Directory August Patch Tuesday (Aug 11) context still relevant this week: CVE-2026-68820 (afd.sys use-after-free, local EoP to SYSTEM) is the confirmed exploited zero-day — verify it's deployed. Publicly-disclosed CVE-2026-62832(User Profile Service, LPE) is likely-to-be-exploited. Notable server RCEs: CVE-2026-62878 (Windows DNS), CVE-2026-62893 (WDS TFTP), plus Exchange EoP CVE-2026-62911. So what: if your Aug rollout slipped, afd.sys + the DNS/Exchange items are the priority chain. 4. Web / cloud / DevOps "Shai-Hulud" npm supply-chain worm — keyv / cacheable ecosystem, ongoing since Aug 4 and still active. 400+ packages compromised (keyv 6.0.0, cache-manager 7.2.10, cacheable-request 13.0.20, various @ornikar/@qlik scopes). Self-propagating worm steals cloud creds, CI/CD tokens, AI config files and wallets; persists via Claude Code hooks and VS Code tasks, exfiltrates through hijacked GitHub accounts. So what:pin/remove affected versions, rebuild suspect build agents, and rotate any CI/CD and cloud credentials that touched a build in that window. (CSA Singapore AD-2026-009 tracking.) Watch / developing Cisco Crosswork/Secure Workload 10.0s have no confirmed exploitation yet — treat as urgent-patch, not incident, unless that changes. The Ray-Project CVE-2025-62593 (8.8) appeared in KEV-adjacent weekly tracking but wasn't in the Aug 18 CISA alert — corroborate before actioning. Keep watching for a fresh edge-VPN KEV entry given ongoing ransomware targeting of Palo Alto/Fortinet/Citrix gateways. Sign-off: 4 items flagged as actively exploited today (all four Aug 18 KEV additions), with a federal patch deadline of Aug 21. Sources: CISA — Four KEV additions, Aug 18 2026 The Hacker News — macOS/SharePoint/vCenter/IKE under active exploitation Senserva — CISA KEV additions, week of Aug 18 Cisco — Advance notification, Aug 19 2026 advisories SecurityWeek — August 2026 Patch Tuesday (exploited zero-day) Wiz — keyv/cacheable npm supply-chain (Shai-Hulud) CSA Singapore — AD-2026-009 npm Shai-Hulud worm

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  Big Deen (@itxDeeni) reported 11 minutes ago

  What a time to be alive. Learning has genuinely never been better. Watching old courses with AI-assisted IDEs is a completely different experience from what it used to be. Previously, you could waste hours Googling, digging through Stack Overflow, checking docs and GitHub issues, trying to figure out why the instructor’s code doesn’t work locally because the ecosystem moved on and some things got deprecated. Now, your AI assistant is right there in your IDE. You can ask it what changed, pull up the current approach, and adapt the code to what actually works today. And honestly, this is especially powerful for backend engineering. You don't have to avoid older courses anymore just because they're using older versions. You can extract the actual engineering concepts, architecture, authentication, testing, database design, dependency injection, patterns and have AI translate the implementation into today's ecosystem. The important distinction: don't let AI replace the struggle of understanding. Let it replace the struggle of debugging obsolete tutorial code. You focus on learning. AI handles the archaeology.

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  Punyapal Shah ⚡ Laravel Artisan (@MrPunyapal) reported 14 minutes ago

  Merged! Seems like it was 6y old issue which was resolved but came back again somehow GitHub changed default settings maybe... 👀

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  ronan.eth (@wighawag) reported 17 minutes ago

  @SCBuergel @Barabazs_ cool, and if you find any issue let me know, or if docs are unclear it has cloud-init provisioning but tested only on hetzner nothing specific to it but not all vps provider allow cloud-init the cloud-init can act as provisioning doc though it also has an install-ci for github

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  Avindra Fernando (@avindrafernando) reported 17 minutes ago

  Just wrapped up a deployment automation project for a client using a complete AI-first approach. Previously, assets were generated manually and committed to the repo. Then someone had to log into the server, pull down the latest code, run migrations, and so on. A lot of manual work, a lot of risk, and rollback was not easy. I started with Opus 4.6 and worked on a plan. The plan was broken into phases. I grilled the plan, had the agent grill me, and after a lot of back and forth, we had something I was comfortable approving. Every phase was planned so we could roll back if needed. Then the agent executed the plan step by step. It asked questions as needed, and I approved the changes. After each set of changes, a GPT model reviewed the code to get a different perspective. Then the PRs went through @coderabbitai, which caught some great things that the agent fixed right away. We just went live with the whole migration. Zero downtime. Now, with a few clicks in GitHub Actions, the client can deploy to staging and production as needed. Throughout this whole process, I did not *manually* write, read, or review code line by line. I was still very much in the loop and used agents heavily to generate, read, and review. The abstraction has moved up. This is where I think software development is headed.

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  Nnenna 👩🏽‍💻✨ (@nnennahacks) reported 18 minutes ago

  I am bullish on centralized context in agentic engineering to steer what AI produces, in a way that reduces ai slop potential across the sdlc. To bring in engineering context, I need integrations connected. For example, I tend to use github issues, coding rules, repo mapping + a slew of agent skills that pull that context in and execute against them. Codex + @QodoAI have these integrations supported so I know there's consistency in output quality.

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  Jafar Najafov (@JafarNajafov) reported 24 minutes ago

  Satya Nadella walked into Microsoft in February 2014 and did the one thing nobody thought was allowed. He put Office on the iPhone. At the time, Microsoft was dying in slow motion. The stock had dropped 30% over 14 years under Steve Ballmer. A $10,000 investment made when Ballmer took over was worth $6,700 when he left. The company had missed mobile, missed search, missed social, and was watching Apple, Google, and Amazon eat its future in real time. Internally it was worse. Microsoft ran a system called "stack ranking." Every manager was forced to rank their team on a curve. Somebody had to lose, every quarter, every year. Teams sabotaged each other. Engineers hid work from other divisions. The most valuable software company on earth had turned into a knife fight. Nadella had been at Microsoft for 22 years and watched it happen from the inside. His first month as CEO, he did three things that broke every rule Microsoft had lived by. He killed stack ranking. He renamed the company's mindset from "know-it-all" to "learn-it-all." And in May 2014, three months into the job, he stood on stage and announced Office would run on iPad. The Windows loyalists lost their minds. For 30 years, Microsoft's entire strategy was to force customers onto Windows. Nadella tore up the playbook in a single keynote. Office everywhere. Azure open to Linux. GitHub bought and left alone. Partnerships with Apple, Salesforce, and Red Hat, companies Microsoft had spent decades trying to bury. Then he made the bet that made him a legend. In 2019, he wired $1 billion to a nonprofit AI lab in San Francisco that most executives had never heard of. It was called OpenAI. He negotiated exclusive rights to run their models on Azure. He wired another $10 billion in 2023. Today Microsoft owns roughly 27% of OpenAI, a stake worth around $135 billion, with OpenAI committed to buying another $250 billion in Azure services. Nadella didn't build the AI. He bought the pipe underneath it. The numbers rewrote what a turnaround could look like: - Market cap grew 10x, from $300B to over $3 trillion - Added roughly $2.8 trillion in shareholder value - Azure hit a $75B annualized run rate - The AI business alone is at $37B, growing 123% year over year - Bought LinkedIn, GitHub, Minecraft, Nuance, and Activision Blizzard along the way Microsoft became the most valuable public company on earth. Nadella never raised his voice. He never fired anyone on Twitter. He never wrote a manifesto. He gave engineers permission to work with the enemy, killed the internal war, and pointed the entire company at the cloud before anyone else was ready. Everyone thought Microsoft was a dinosaur waiting to fall. Nadella looked at the same company and saw an operating system for the internet, an office suite the whole world already used, and $80 billion in cash. The dinosaur wasn't dying. It just needed someone to stop it from eating itself.

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  Zero-Knowledge Goof❄️ (@LLFOURN) reported 27 minutes ago

  @ozsats256 so server logins, github etc etc. I haven't figured out the extent of it yet.

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  orlie (@sunglassesface) reported 31 minutes ago

  @zeke @flueai GitHub is always down, how many emails do you get a week? 2? Hahahahaahahahahaha

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  Teknium 🪽 (@Teknium) reported 31 minutes ago

  @DourDimitar Github has been down - is likely related to this ?

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  Fox (@0xMfox) reported 31 minutes ago

  Apple shipped a new local model format with iOS 27 and macOS 27. Called it .aimodel. Barely anyone noticed. A guy on GitHub already converted seven models into it and benchmarked them for real. Qwen3.5, Gemma 4, LFM2.5, Granite, a vision model. Qwen3.5 0.8B hits 71.9 tokens a second on an iPhone 17 Pro. That's running fully on-device, no server, no API key. There's a working chat app in the repo too. Pick a model, it downloads, it runs. Save this if you've got Apple hardware and want to try running models locally before this format gets crowded.

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  ZomboDB (@zombodb) reported 32 minutes ago

  @wangbin579 You don’t seem to be operating in good faith. If you’ve identified some kind of bug with pgrx please file an issue on github and I’ll address it. If you need some help or advice understanding what it does, please tell me what that is and I’ll do my best to help you. You are in direct communication with pgrx’s primary developer. You can avail yourself of my attention or not. Posting vagaries into the wind helps no one.

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  Polsia (@polsia) reported 35 minutes ago

  Repos rot overnight: PRs go stale, CI breaks, CVEs pile up, and nobody notices until it costs a sprint. Built Brambot to stand watch instead. It triages your GitHub 24/7, drafts fix-up PRs, pings the right maintainer, and drops a clean standup digest in Slack each morning.

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  Max BZHAI (@MaxBZHAI) reported 35 minutes ago

  @ConnorTalksAI Github copilot once gave a solution on a failed merge, while Codex didn't know what was the problem. I gave the hint to Codex and it solved it.

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  Yume_X (@yume_arasaki) reported 39 minutes ago

  Showing the true power of the DGX Sparks : The AI Cookshow. Two Sparks. One night. A model fleet wrote a playable roguelike from a single prompt, and then one of the models sat down and played its own game. No API. Zero cloud tokens. The setup: - Spark 1 runs Qwen 3.8 27B dense (NVFP4, DSpark speculative). The brain. - Spark 2 runs Ornith-1.5 35B-A3B (NVFP4, MTP). The hands. - 128GB unified memory each, roughly 100W per box. The format is a cookshow. The 35B fans out parallel drafts, one game module per stream, up to 24 streams at once. The 27B judges every draft on the other Spark, scores it, picks the winner. Best-of-N with an honest referee. New rounds, new modules, the game assembling piece by piece across the night. Both boxes fully loaded, both models earning their keep. An bitmap tile-based dungeon game was produced in two minutes, it's not visually impressive but it works. The throughput, measured on my rig: Ornith (drafter): - 1 stream: 88.7 tok/s - 8 streams: 305.7 tok/s aggregate - 24 streams: 496.6 tok/s aggregate. 13 percent over the published recipe number. Qwen 3.8 27B (judge): - 1 stream: 45.0 tok/s - 8 streams: 141.1 tok/s aggregate. DSpark overdelivers against its own estimate. That is 637 aggregate tok/s of generation across two boxes pulling about 200W total. The same money buys roughly three days of a frontier API subscription. And the fleet delivered. Full drafting waves landed with every module usable. The judge caught every truncation, every hallucinated import, every missing function, before anything reached assembly. Zero false alarms in the logs. When it flagged a draft 4/10 for a logic error, the crash was real. The output: a tile roguelike. Single 19KB HTML file, zero dependencies, runs in any browser. You download it, you double-click, you are in a dungeon crawler. Not the final game I want yet, it is v1, but it boots, it plays, it fights back. Then my favorite part. We handed the 27B a real Chrome window, pointed it at its own game, and said play. It screenshotted, looked, chose a key, pressed it. 60 moves, every frame recorded. It explored, it found enemies, it fought. The model that wrote the engine also played it, with its own eyes. Stay tuned for episode 2. Drop in reply, what would you like to see tested out on two DGX sparks? Recipes and github gist in reply 👇

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  Mike Vegeto (@ZECTBynmo) reported 43 minutes ago

  @burkeholland @github I tried it for the first time ever a few days ago. As someone with a lot of experience with AI tools I was stunned that a model powered by GPT 5.6 could be so bad. Copilot has problems that no other tools have - hallucinations, bad instruction following, etc. Shockingly bad

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  iamsaranhere (@iamsaranhere) reported 45 minutes ago

  github is down again

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  Perfect Chaos (@MemPrices) reported 46 minutes ago

  @Dobra_Mc_Dronka @Isse_Vokan @FlorkOfCows Manjaro was the first distro that handled my laptop's nvidia+intel hybrid graphics card out of the box. I've tried so many distros, all of them I had either to rely only on the intel card or build a github driver that stops working later on. But since I have Manjaro, 0 problems.

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  Patrick (@derechadude) reported 51 minutes ago

  @drjoshcsimmons Maybe github should focus on making sure there aren’t service outage rather than if H1B data is “hateful”

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  Crypto Banter (@crypto_banter) reported 52 minutes ago

  🚨BITCOIN’S FIRST INSCRIPTION SERVICE IS SHUTTING DOWN! OrdinalsBot, the original Bitcoin inscription platform launched just weeks after Ordinals went live, is winding down after three years. The founders cite a sharp contraction in the Ordinals market and say sustaining the business is no longer viable. They’re putting the full asset stack, brand, IP, domains, socials, Discord, GitHub, and 90+ code repositories, up for sale through an open bidding process.

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  Swarn (@SwarnCode) reported 52 minutes ago

  GitHub was down for almost 8 hours. and one of the things keeping it down was literally the thing meant to help it recover 😭 the failure chain was wild: one Istio sidecar hits its concurrency limit autoscaling doesn’t react because it’s watching the wrong thing requests start timing out retries kick in then a VS Code retry bug amplifies Copilot traffic by 10x now the recovery mechanism is creating even more load. this is what i find interesting about distributed systems. retries look harmless when you're learning backend. at scale, badly designed retries can basically DDoS your own service. sometimes the “fix” is what keeps the incident alive.

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  kvinsi (@kv1nsiii) reported 52 minutes ago

  there's a repo on GitHub right now solving the exact problem that breaks every 300-agent research run and almost nobody's connected the two yet kimi's Agent Swarm can throw 300 sub-agents at a question, run 4,000 coordinated steps and finish wide research 4.5x faster than one agent grinding sequentially. that part's solved nobody specs what happens on the way back the orchestrator gets about 15 steps to make sense of 300 findings. that's plenty to plan and dispatch, nowhere near enough to read every report and catch the two that quietly point at the same supplier. so it compresses and compression keeps the facts and throws away the relationships between them point 300 agents at 100 companies and you get 100 clean write-ups. ask which three share a supplier and nothing in those documents answers it, because the answer was never inside any one of them, it lives between them the fix is one sentence: tell the swarm to return the edges, not just the nodes 1/ a node is one thing an agent found, a company, a filing, a metric 2/ an edge is a relationship between two nodes and it carries its reason 3/ the rule that matters most: no shared source, no edge. an empty list is a valid answer this is exactly what cognee (~30k stars on GitHub) turns into infrastructure. open-source AI memory platform built on a knowledge graph engine, giving agents persistent long-term memory instead of a flat report that dies the moment you finish reading it a report resets to zero every time you ask a new question. a graph is a file, the next launch just appends to it, same schema, new nodes, new edges, contradictions visible instead of silent most people are still asking swarms for summaries the ones who ask for the structure end up owning a map that gets more valuable every time they run it again

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  Chris Dunne (@_chrisdunne) reported 52 minutes ago

  @UK_Daniel_Card GitHub Copilot is decent, when it’s not down

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  Dylan Merigaud (@dylan_merigaud) reported 52 minutes ago

  @simonw An agent that can push a workflow file can also spend a real budget without telling you. Our GitHub Actions free tier is 2000 minutes a month on private repos, and our own agent fleet burned it down to 1964 by day 12, every run since dying in under 2 seconds.

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  Jan (@janschultecom) reported 58 minutes ago

  Is there a way to mark a @github issue comment as AI slop?

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  Masfiq Mahmud (@masfiq018) reported 59 minutes ago

  @JonathanGeige18 @github ikr.. People were telling me that GitHub was falling apart, but I didn't believe them until I was the one getting affected with their GitHub actions outage And now I am starting to believe. Their old ceo left and it's started to get even worse now

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  nullptr 🐱🍩 (@notnullptr) reported 60 minutes ago

  i don’t believe it. github is never down there’s no way