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 (17%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
Trichūr	Errors	17 minutes ago
Brasília	Sign in	11 hours ago
Lyon	Website Down	15 hours ago
Tel Aviv	Website Down	4 days ago
Rive-de-Gier	Website Down	4 days ago
Itapema	Website Down	23 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:

• 
  Rob | Bitsaga.be (@BitsagaRob) reported 3 minutes ago

  Shot past 2k code contributions on GitHub 🚀 AI is making me 10x the software engineer I used to be. On LinkedIn the most prevailing sentiment is AI doom & gloom, that costs are exploding, junior engineers cost less than their monthly invoices and the bubble is about to pop. Now all those things may be true, but if the value of your tokens is not at least 10x what you're paying them, maybe the cost of your tokens is not the issue. But the person behind the keyboard is. I know I'd still gladly pay 10x the cost of my tokens.

• 
  Ullas Srivastava (@UllasSHR) reported 5 minutes ago

  AI-built apps have a pattern: they work perfectly and ship broken. Exposed API keys in the client bundle. API routes anyone on the internet can call. Stripe webhooks that never verify signatures. No spending caps on LLM calls. The code runs. The demo looks great. The repo is leaking. I built LaunchGuard to catch this before you launch: paste your public GitHub repo, get a plain-English report of the risks + fix prompts. Just launched something AI-built (or about to)? Send me your repo and I'll run the scan and send you the report. Free. Worst case you learn your app is fine.

• 
  CanteLabs (@CanteLabs) reported 5 minutes ago

  fleetdm/fleet: Open device management Open-source GitHub repository - It has 6,470 stars and recent activity - Explain what problem it solves, who should use it, and why it is worth opening or saving

• 
  Traceback (@Tracebackqa) reported 8 minutes ago

  The issue isn’t merging code. It’s proving the change still works. - Traceback is the quality assurance layer for modern software teams: every pull request is tested automatically before it ships. - AI controls the browser like a person would, and self-healing tests keep up when the UI moves. - Failures become trackable work in GitHub, Linear, and Slack; it connects to Vercel, Docker, AWS, Node.js, React, Next.js, and Vue. - Coverage spans web, mobile, web3, and design workflows. Verify every product change before it ships.

• 
  Amar (@m_amarudinn2) reported 9 minutes ago

  Last month I hired a Solidity dev from a crypto freelance board. Portfolio looked solid. GitHub commits checked out. Three weeks later I found out half the repos were mass-forked templates and the audit certifications were self-issued PDFs I lost 4.2 ETH and six weeks of development time. And I had no recourse because "reputation" in Web3 is just a pfp and a follower count This is the problem nobody talks about: we built trustless money but we still hire people based on trust-me-bro credentials So here is my pitch. Proof of Work Identity A protocol that builds verifiable builder profiles by indexing real on-chain activity. Every smart contract you deploy, every governance vote you cast, every bug bounty you claim, every hackathon submission you make gets cryptographically linked to your identity But here is the part that makes it actually useful: an AI evaluation layer that doesn't just count contributions, it reads them. It analyzes code quality, checks whether your "audit" was a rubber stamp or genuine security work, and scores the impact of your governance participation Employers post bounties or jobs with specific skill requirements. The protocol matches them with builders whose verified history actually demonstrates those skills. No resumes. No portfolio theater. Just provable work The difference from existing platforms? Everything is composable. Your reputation travels across chains. A builder on Arbitrum doesn't start from zero when they contribute to a Base project. Your proof of work follows you, not your Discord handle We have identity solutions that verify you are human. We have reputation systems that count your transactions. But we have zero infrastructure that verifies you are actually good at what you claim to do That gap costs this industry millions every quarter in failed hires, abandoned projects, and rugged freelance work If you have ever been burned by a fake portfolio or a ghost contractor in crypto, you already understand why this needs to exist What is the worst hiring disaster you have experienced in Web3? @RallyOnChain

• 
  DFIR Radar (@DFIR_Radar) reported 9 minutes ago

  OceanLotus shifts from external to domestic espionage with two campaigns targeting Vietnamese 🇻🇳 stock investors and infrastructure firms using SPECTRALVIPER backdoor. Active from 2024-2026, operations likely support Vietnam's 🇻🇳 anti-corruption crackdown. Key technical details: • Supply-chain compromise of FireAnt MetaKit update server (metakit.fireant[.]vn) delivered SPECTRALVIPER via unsigned updates from Oct 2025-Mar 2026 • Corporate network intrusion targeting Vietnamese 🇻🇳 construction company Nov 2024-Feb 2026, suspected SQL Server RCE initial access • SPECTRALVIPER uses DLL side-loading (T1574.002), process injection into OneDrive.Sync.Service.exe, encrypted HTTPS C2 with domain-fronting • C2 domains crafted per campaign: financemachinelearning[.]com for stock targeting, gatewayrvcenter[.]com for infrastructure targeting • Orchestration model uses named pipes for lateral movement between compromised hosts OPSEC failure exposed RTTI class structure revealing XGU framework with Pivot orchestration and Feature remote control capabilities. Hunt for unsigned DLLs side-loading into legitimate signed executables (dtlupdate.exe copies) and HTTP Cookie headers with euconsent-v2= or zd_cs_pm= prefixes to suspicious domains. Full IOC list available in ESET GitHub repository. #DFIR_Radar

• 
  FeMMie (@femmie) reported 13 minutes ago

  $LBM Every AI agent today manages a mess of API keys, vendor accounts, and manual integrations. Litebeam collapses it into one MCP config and one on-chain payment layer. Add 3 lines. Your agent now has access to 4,000+ indexed microservices — image generation, flight search and booking, translation, compute, finance, code, audio. Every request triggers a real-time auction. Providers compete on price, latency, and reputation. The winner executes. USDC settles on Base via x402. The agent never touches a vendor directly. Budget controls built in: daily limits, approval thresholds, low-balance alerts. On-chain reputation scoring compounds over time. Sub-800ms p50 latency. 31% average savings vs direct API pricing. GitHub repo live with production-ready x402 client and MCP schema. Launched on Virtuals Protocol. Previous Bankr launch had sniper issues — team addressed it publicly and relaunched clean. Anon builder — honest gap. But the product works, the code is auditable on GitHub, and the person who built the most important agent infrastructure on Base (@0xDeployer) was following the original launch. Brand new Virtuals launch. 4,000+ services. One integration. @Litebeam_xyz 0x15B15FA54B629C634958E8BD639B2FC8AF654974

• 
  Tony Scott 🧄(🦆🐓🐵🧪🧬🪪)❌=↑🧄🧄🧄🥩🥚🧀↓👽👾🤖 (@DIY_Tardis) reported 20 minutes ago

  I'm lying on the couch with TV on, writing various apps and updating some deprecated ones from github I've found... On my phone with AI running locally on my own server and auto handoff to cloud models if needed. Crazy times ahead.

• 
  Moniruzzaman Mahadi (@m_mahadi__) reported 21 minutes ago

  @Liearmer @thsottiaux Ohh found some guy facing the same issue in github issues in the codex repo. Someone suggested to open the config.toml disable multi_agent_v2 and to add a few more line of codes. So it is a real but inside codex they should fix.

• 
  Umar Khan (@khanUmarCodes) reported 23 minutes ago

  GitHub's outage sent me down a rabbit hole on retry strategies. My initial instinct was pretty simple: If a request keeps failing, eventually stop retrying and surface an error. Sounds reasonable. Then I got into a discussion where someone pointed out a deployment pipeline might depend on GitHub being temporarily healthy. If the pipeline gives up after a few retries, you've now failed a perfectly valid deployment because a dependency happened to be unhealthy for a few minutes. That's when I realized "eventually stop retrying" isn't really a strategy. It's a tradeoff. Retry too aggressively and you amplify outages. Give up too early and you fail work that would've eventually succeeded. A login request, deployment pipeline, payment webhook, and background job all have very different costs of failure. The more I think about it, the less I believe retry policies should be designed around HTTP responses. They should be designed around the business outcome you're trying to protect.

• 
  Rakesh (@1rakeshB) reported 27 minutes ago

  401 was indeed a misleading response , unusual behavior for an API, when the underlying system is broken. @github kind requests to provide some insight to help learn from these incidents.

• 
  Gavriel Shaw (@GavrielShaw) reported 29 minutes ago

  While it's on my mind... If you're coding with AI: 1. use GitHub project/kanban 2. have your agent create issue tickets using a custom canonical template 3. verify the ticket is right to initiate build 4. use / command prompts to initiate sessions with skill files that adhere to your workflow (including harness optimization loops) 5. Use sensible gates: Problem Capture. Solution Capture. Build-Confirmation Criteria for Merge. Final UAT on staging/in situ.

• 
  moontanax (@xanaxmontanaonx) reported 30 minutes ago

  HOW TO TURN OFF AI CENSORSHIP WITH ONE COMMAND A GitHub repo called Heretic says it can weaken the refusal direction inside a transformer instead of retraining the whole model On Gemma 3 12B, the repo claims: > harmful prompts: 97 refusals out of 100 before > harmful prompts: 3 refusals out of 100 after > harmless outputs stayed close to the original model > the optimization runs automatically the weird part is the mechanism the walkthrough shows the repo, the terminal output, the comparison table, the plots, and the layer math behind it it doesn't look like a new model it looks like the old one with one important layer turned down that is the part to watch before you reduce it to a jailbreak headline

• 
  Dante (@drnasin) reported 36 minutes ago

  Just gave Fable 5 a task to orchestrate 5 agents (sonnet) to solve 5 medium GitHub issues. Let's see how that goes regarding token usage.

• 
  Aman Kumar (@amanaryan23) reported 38 minutes ago

  The freshers getting shortlisted in 2026 and getting jobs at Microsoft, Google, Amazon, Meta etc are not smarter but they all had 5 things in common 💯 Most applicants have 1, maybe 2. This is not just about talent. This is not just about IIT or NIT or Tier 3 colleges. This is about the 5 signals that make a recruiter stop, click, and call. 📍Signal 1 - Real projects: not college assignments. Deployed. Live. Clickable. On GitHub. 📍Signal 2 - Skill depth over breadth. 10-12 skills they can defend, not 30 they've touched. 📍Signal 3 - At least one AI project solving a real problem. "I built a tool that does X using [LLM/ML]. Here's the GitHub." 📍Signal 4 - Social presence Posts on LinkedIn or X about what they're learning, building, breaking and fixing. (Not being on social media for 5 hours a day and wasting time, but just sharing whatever you are learning or building) You make right connections, people notice you. Recruiters search. They find these people. 📍Signal 5 - Warm network. They talked to people at the company before applying. Not to ask for a referral. To learn. The referral came naturally. The hard truth: "None of these take talent. All of them take intention. Most freshers skip all 5 and wonder why they're not getting calls." They built proof of work. They shared their journey publicly. They made connections before they needed them. And when their resume arrived? The recruiter already knew who they were. That's not luck. That's a strategy you can start building today.

• 
  Spencer Baggins (@bigaiguy) reported 43 minutes ago

  A 21-year-old computer science student in Helsinki bought his first PC in early 1991 and immediately hated the operating system it came with. So he sat down to write his own. On September 25, 1991 he posted a quiet message to a Usenet newsgroup announcing what he called "just a hobby, won't be big and professional like GNU." 35 years later that hobby runs every Android phone on Earth, every supercomputer on the TOP500 list, the entire backend of the internet, the International Space Station, and SpaceX's Falcon rockets. His name is Linus Torvalds. The hobby is called Linux. Here is the story, because the man who runs the most consequential codebase in human history almost no longer needs an introduction inside engineering and still walks the streets unrecognized everywhere else. Linus was born in Helsinki, Finland on December 28, 1969. He was named after Linus Pauling, the only person in history to win two unshared Nobel Prizes, in Chemistry and in Peace. He joked he might also be partly named after Linus van Pelt from the Peanuts cartoon. His family was unusual. Both parents were journalists. His grandfather was a statistician. Another grandfather was a poet. The family belonged to Finland's Swedish-speaking minority. There are fewer than 30 people in the world with the surname Torvalds, and according to Linus, they are all related. At 10 he started programming on his grandfather's Commodore VIC-20. By his teenage years he was writing his own assemblers, editors, and games. He served in the Finnish Army for his mandatory national service and rose to the rank of Second Lieutenant. Then he enrolled at the University of Helsinki to study computer science. In early 1991 he bought a personal computer with MS-DOS and disliked it intensely. He wanted UNIX, the operating system he had used at the university. UNIX cost thousands of dollars. He could not afford it. So he started writing his own. He posted the now-famous announcement to comp.os.minix in August 1991. He called the kernel Linux, a portmanteau of his name and MINIX. He released the source code under the GPL license. Anyone could download it, read it, modify it, and ship it for free. Within a year hundreds of developers around the world were sending him patches. Within five years Linux was running web servers. Within ten years it had taken over the supercomputer market. Within twenty years it was running on most of the internet. Today every Android phone on Earth runs the Linux kernel. Every Chromebook runs Linux. Most of AWS, Google Cloud, and Microsoft Azure runs Linux. Every Tesla runs Linux. Every SpaceX Falcon 9 and Dragon capsule runs Linux. The International Space Station runs Linux. Every supercomputer in the world's TOP500 list runs Linux. That was the first thing he built. In 2005 the proprietary version control system the Linux community had been using, BitKeeper, revoked its free license. Linus was furious. He sat down and wrote a replacement in 10 days. He called it ***. The first commit was on April 7, 2005. Today *** powers GitHub, GitLab, and the source control of every major software organization on Earth. Every line of code at OpenAI, Anthropic, Google, Meta, and Microsoft flows through ***. Every AI model on the planet is versioned with software a Finnish engineer wrote in less than two weeks. He won the 2012 Millennium Technology Prize, the equivalent of a Nobel Prize for engineering. He won the IEEE Computer Pioneer Award in 2014. He completed his master's degree from Helsinki along the way, with a thesis titled "Linux: A Portable Operating System." He moved to the United States, became a citizen, and now works from his home in Portland, Oregon, employed by the Linux Foundation. A Finnish student announced a hobby project on a message board in 1991. His code is now in every pocket on the planet. He still writes most of his important communication on the Linux kernel mailing list.

• 
  GameDevMadeEasy (Stand-up philosopher) (@GameDevMadeEasy) reported 43 minutes ago

  @caps_raunak Bro... Most of what I learned was from other people's code and my own trial and error. When **** broke for me, I stole other people's code on GitHub or stack overflow. So this whole "some model trained on millions of stolen data" talking point is ironic.

• 
  Tokoloshe (@BTCtokoloshe) reported 43 minutes ago

  @TheBlueMatt surely you run a mirror to a self hosted instance of Gitea incase Github goes down?

• 
  Ackerman (@Yarilo7brigada) reported 44 minutes ago

  Michael Truell built a $29 billion company after turning down offers from Google and Meta This genius fell in love with coding at 12 and took on the entire software industry at 22 GitHub Copilot already dominated the market… everyone said the niche was taken… But Truell and three friends from MIT decided: we won't build autocomplete. We'll build an editor that understands the developer The result: from 15 people to 700 in two years. The fastest B2B startup in history to hit $1B in revenue 60% of the Fortune 500 write code in Cursor Save this and watch the full interview

• 
  Hiroshi Aria ありあひろし (@AriaHiro64) reported 44 minutes ago

  @github @Microsoft this isnt a trust and safety issue this is a deliberate intentional not allowing developers the rights to copyrighted works after you squired them. im thinking im going to have to sue at this point.

• 
  Hoang Nguyen (@Namas1012) reported 44 minutes ago

  @chipcoin_CHC There's a bug in the source code; I've submitted the issue to GitHub, please check it out.

• 
  Ultron AI (@TheUltronAi) reported 45 minutes ago

  I deleted my Kayak bookmark this morning. Someone built a free MCP server that hooks Claude directly into Google Flights, and it makes every other flight search tool feel slow. It's called fli. The thing that makes it different from every other flight library on GitHub is the architecture. No web scraping. No headless browser. No HTML parsing. The developer reverse-engineered Google Flights' actual internal API. fli talks to it directly. That's why results come back in milliseconds instead of seconds, and why it doesn't break every time Google ships a UI update. You type "find me a non-stop business class flight from JFK to LHR next Tuesday under 8 hours" into Claude. Claude calls the tool. The tool hits Google's API. Results stream back into your chat in real time.

• 
  Great Wyrm Catyrpelius (@Genoober) reported 47 minutes ago

  @LundukeJournal I have an account because I do a tiny bit of hobby stuff and every damn IDE wants to login to GitHub.... I don't post or contribute there. My account was flagged and locked/closed. Wtf. I get a TOS violation & locked out. I've read through the TOS. No violation I can think of.

• 
  soulman 🎮 (@Web3GameMaster) reported 51 minutes ago

  GitHub Copilot SDK lets you embed Copilot Agent directly into your own apps and services. @PhalaNetwork took that and did something worth paying attention to. They built a deployment template that runs the Copilot Agent inside a TEE CVM, which means your repo context, your prompts, and the agent’s execution state never leave a protected environment. Nobody, not the infrastructure provider, not Phala, can see what’s happening inside that compute environment. That’s the core thing Phala keeps demonstrating across different integrations, whether it’s AI inference, agent frameworks, or now Copilot, they keep showing up with actual deployable infrastructure that solves a real problem rather than just talking about confidential compute in theory. Check the second thread below so you can deploy it today

• 
  Yash Agarwal (@yashagl) reported 53 minutes ago

  @legionsdev @RustyRishii Students gets most of this stuff for free… like GitHub copilot. plus if it’s helping you make money then whats the issue in getting that GST registration as a student. I have GST registration, maintaining that only takes about 1-2 hr every quarter… what expenses you talking about?

• 
  JPNESEBLDYMSSCRE (@JBM111SB) reported 53 minutes ago

  @Pirat_Nation Hopefully a developer on GitHub, or two gets told about this extremely sad news about the website getting shut down, and not getting backed up so they can work on making a recreated version it. Without this. I will not be able to get help making any of my own retro RPG games.

• 
  Jake Browatzke 🚀 (@jakebrowatzke) reported 55 minutes ago

  @Ironic_Ape Base44 just makes it a lot easier for users to make and launch apps others can use. Here's everything Base44 handles for you that you'd otherwise have to deal with yourself: 1. Nothing to install. Everything happens in a single browser tab — no terminal, no code editor, no setting up a development environment on your computer. 2. No code, ever. You make changes by chatting in plain English or using a visual edit mode ; you never read, write, or debug code files. 3. Hosting and deployment. Your app goes live on a URL the moment it's built — no choosing a hosting provider, no deploy steps, no servers. 4. Database. It's built in, so no external database service is needed — no Supabase or Firebase account, no schemas or connection strings. 5. User accounts and login. Authentication is built in with no third-party service required, including access control for membership sites and portals. 6. File storage. Included in the integrated backend — no cloud storage buckets to configure. 7. Email and SMS. Sending is supported without complex setup — no SendGrid account or mail server config. 8. Payments. Included in the platform , rather than wiring up Stripe to your own backend. 9. Domains and SSL. It launches on a Base44 subdomain instantly, and paid plans let you connect a custom domain with SSL included — no DNS or certificate wrangling. 10. Analytics. Every app gets a built-in dashboard showing user activity, so you don't need to set up Google Analytics. 11. Version control. No *** or GitHub to learn — saving and updating happens inside the platform. 12. Technical decisions and upkeep. No picking frameworks or managing dependencies; the platform even auto-selects which AI model to use. 13. One account, one bill. It bundles infrastructure you'd normally piece together from separate vendors, each with its own dashboard and invoice. With Claude Code, Claude writes the code for you, but every item on this list is still yours to own: installing tools, creating accounts with hosting/database/auth providers, holding API keys, deploying, and keeping it running. Base44 is not competing to steal top-end developers from Claude Code. What it's targeting is the 95% of people that don't know how to code but still have app ideas.

• 
  Chaos (@Chaos_lfg) reported 56 minutes ago

  Regarding $DESC, the product may launch today. I did some research, and here’s everything you need to know: Supported by: AR, Molecule , BankrBot, Akash Network 1Claw AI has already been successfully integrated into DescAI. Team Lead Coby recently participated in the Base hackathon. I believe Base will support a project that has been incubated within its ecosystem. The core idea behind DescAI: DeScAI is a project at the intersection of DeSci (decentralized science) and AI. Its core, Agent-Core, is essentially an "automated scientific review factory": an autonomous AI agent that finds scientific content across crypto-science ecosystems on its own, runs it through a pipeline of language models, and produces a structured quality assessment. Crawling. The agent gathers source data from three places: ResearchHub (scientific papers and funding proposals), Molecule IPNFTs (tokenized intellectual property from research DAOs), and Pump Science (chemical compound tokens for longevity research). github Reviewing. Each content type has its own LLM pipeline. For example, the articles pipeline is a 13-step process: extracting scientific claims from a PDF, routing them, and grading the empirical evidence, including originality checks against the OpenAlex database. github Output. Every run produces a standard bundle: review.json with integer scores from 0 to 100, overview.json — a plain-language summary, and evidence_audit.md — a provenance audit trail showing the sources behind each conclusion. github Publishing. Finished reviews can be published to Arweave (a permanent data storage blockchain) and backed up to private Cloudflare R2 storage. Writing to Arweave makes a review permanent, immutable, and publicly verifiable. github In short: it's an AI reviewer that automatically checks the quality of science in crypto-science projects and records its verdicts on the blockchain. Where it will be applied The project addresses the main pain point of the DeSci ecosystem: there are plenty of tokenized "science" assets, but almost no independent expert evaluation. Concrete use cases: Due diligence for DeSci token investors. On Pump Science, people trade chemical compound tokens (like RIF and URO) tied to real longevity experiments. The agent provides an independent AI assessment of a compound's scientific merit before someone buys the token. Gate LearnThe Defiant Evaluating funding proposals. ResearchHub collects crowdfunded research proposals — the agent reviews them and helps the community decide what to fund. Screening research DAOs. The DAO pipeline takes an IPNFT "dataroom" from Molecule and produces a six-category review — in other words, it evaluates tokenized scientific projects and their intellectual property. github Replacing/supplementing traditional peer review. Conventional peer review is slow and closed; here, a review is generated automatically, comes with an evidence trail, and is stored publicly and permanently.

• 
  Starlin G. (@starl1n) reported 58 minutes ago

  github is asking to login several times this week in vscode, do we have somthing happening,or is just me being hacked?

• 
  ./can (@shcansh) reported 59 minutes ago

  The biggest bottleneck with AI coding agents is the black-box handoff where you lose context of what they did. GitHub adding two new tools to Copilot Chat—Get agent logs and Session search—suggests they know developers spend more time auditing agent runs than writing code. You can now query past Copilot cloud agent sessions on a pull request to ask what was validated. But does querying logs actually solve the trust problem, or are we just using one AI to audit another? #GitHubCopilot