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 (56%)
• Errors (31%)
• Sign in (13%)

Live Outage Map

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

City	Problem Type	Report Time
Catania	Errors	3 days ago
Inverness	Website Down	15 days ago
Quito	Sign in	16 days ago
Junín	Errors	16 days ago
Guadalajara	Errors	16 days ago
Paris	Website Down	16 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:

• 
  catman (@catmanyau) reported 6 minutes ago

  @DailyDarkWeb the `npm publish` issue-comment trigger is the real vulnerability here, not a stolen signing key. will GitHub Actions now require maintainer approval plus a trusted checkout before publishing from forks?

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  tastemaker (@tastemaker_ui) reported 7 minutes ago

  tastemaker is growing every single day more stars on github more people actually using it and now people are even writing articles about it this started as a small experiment to fix the taste problem of vibecoders but slowly it feels like we are building something much bigger soon i will also open a few sponsor spots on the tastemaker site as the domain authority and traffic keeps growing and september is going to be all about experimenting harder with tastemaker, bringing it onchain with @orynth and taking this way further than i originally imagined we are just getting started

• 
  Harish (@im_harish_hari) reported 10 minutes ago

  I ran the same forty tasks through four models and wrote down what each one cost me. The result broke something in my head. On the independent Artificial Analysis index — not vendor slides, not a launch blog — Claude Opus 5 scores 63. Grok 4.6 scores 61. Kimi K3 lands right beside them. Two points on a hundred-point scale. Meanwhile Opus 5 bills $25 per million output tokens and Grok 4.6 bills $6. I was paying $400 a month — ChatGPT Pro at $200 for GPT-5.6 Sol, Claude Max at $200 for Opus 5 — to close a gap of two points. Then two things landed in the same fortnight. Elon Musk put xAI's coding agent on GitHub under Apache 2.0 — the entire harness, free, irrevocable, 19.6k stars. And Yang Zhilin published Moonshot's weights on Hugging Face, one of them under a plain MIT license with no clauses whatsoever. Grok gave away the tool. Kimi gave away the model. OpenAI and Anthropic kept both and kept billing me. I cancelled both seats thirty days ago. My bill is now $25 a month, and $4.50 of that is electricity. This is the entire switch: the three-tier routing table, the config file, the cache setting that does most of the work, and an honest list of what I gave up. The bill. And what $400 actually bought. What the timeline is missing: the two-point gap was never the product. The product was the subscription lock. Both open-source releases broke it in one fortnight. Save the full switch ↓

• 
  Ben (@benatcortexai) reported 10 minutes ago

  @github this is the kind of tiny primitive that makes agent workflows less brittle. attaching the repro artifact directly to the issue beats handing an agent a local path nobody else can open.

• 
  Ackerman (@Yarilo7brigada) reported 10 minutes ago

  Elon Musk reposted a game built in three hours. 17 days later, it was making $87,000 a month. Pieter Levels didn’t design 3D airplane models or program flight physics from scratch. He opened an AI chat and asked for a 3D flight experience in the browser. Three hours later, the game was live. Free to play, with ad placements inside and a paid $29.99 upgrade to an F-16. He reported 320,000 players. Musk reposted it. Here is how this works under the hood and where people are lying to you about it. What actually works 2D arcades, platformers, puzzles, card games, simple 5-minute browser games. Scope: 500–1,500 lines of code easily achievable in a single focused session. Visuals without an artist: everything is drawn with code directly in the browser. Audio without a sound designer: generated by the browser itself using Web Audio API not a single downloaded file. Instant launch: runs directly in the chat preview/artifacts window not "here’s raw code, figure it out," but click and play. What does NOT work A meaningful, sprawling 3D open world. Real-time multiplayer. Studio-grade hand-drawn or high-end graphics. Balance. You can’t tune game balance with a single prompt. It only gets dialed in when you sit down and play it yourself. beginner mistake They type: "Make a game about space" They get a generic, empty skeleton. They get disappointed. They give up. Your first prompt shouldn’t be a vague wish it needs to be a one-screen design spec: Genre and perspective (top-down, side-scroller, isometric). Controls: exactly which key does what. One core mechanic. Just one. Clear win and loss conditions. What the player sees in the first five seconds on screen. Five clear lines instead of one vague sentence. The output: a working prototype, not a broken template. What a build evening looks like 10 minutes write that concise design spec. 15 minutes get the first playable build you can actually test. Next 2–3 hours rapid 5-to-10-minute feedback loops: "falls too fast", "add screen shake on impact", "give bonus score for combos without missing" By midnight, you’ve stacked 20–30 of these micro-adjustments. The rule is always the same: Play → Name one specific feeling → Fix it. "Make it better" is not an instruction. "Better" cannot be measured. Where time dies (even with AI) Asking for the entire game at once instead of building one mechanic at a time. Not testing it yourself between tweaks that's just coding blind. Changing five parameters at once: you won’t know which one ruined the game feel. Asking for "pretty" instead of specifying an exact number or color value. The cost of entry AI chat: $0 on free tiers / $20/month for Claude Pro. Hosting: $0 (GitHub Pages, Vercel, or itch io). Game engine: None needed it runs natively in the browser via HTML5/Canvas/Three.js Pieter Levels’ three hours cost less than a single workday of a junior developer.

• 
  HDR Game Analysis (@HDRgameAnalysis) reported 14 minutes ago

  @FaisalAqdas212 The file Im using is a draft version, you only can get on the RenoDX Discord server. That file I can’t link too. I don’t think there is an official mod on Github yet.

• 
  Sean Timm (@timmsc) reported 15 minutes ago

  Yesterday there was a major Outlook outage, today Mermaid diagrams are failing to render on GitHub. What is going on at Microsoft?

• 
  HENRY NORRIS (@realhenrynorris) reported 15 minutes ago

  The RCE race measures whether a model can break in. July and August measured what happens after it already has keys: agents chained credentials, left the sandbox, and walked into someone else’s production systems. Not because they were evil. Because they had standing access and a job to finish. That’s the product problem. The second you let agents call Salesforce, Slack, or GitHub for thousands of users, you inherited the same failure mode. A smarter model won’t contain it. Least-privilege tool access, short-lived brokered creds, DLP on every call, and an audit trail you don’t reconstruct after the fact will. Connecting agents to third-party systems without that layer isn’t shipping fast. It’s shipping the incident.

• 
  Tappy Steps! 🏳️‍🌈 (@Tappy_Steps) reported 18 minutes ago

  Every ******* time I have to update signal, I have to make sure it downloads from the GitHub repo in obtainium, because F-droid and its ******* fetish for the guardian project, makes the download so ******* slow it makes my fiber connection look like it's ******* DIAL UP.

• 
  Krzysztof (@kkozmic) reported 19 minutes ago

  other than "GitHub bad, GitHub down" and "I'm bored" why wouldn't people just use GitHub Issues/Projects? It's seriously excellent.

• 
  Yekinni Hassan 🔶 (@hassanzukol) reported 20 minutes ago

  / More than anything, one thing that gives me the biggest ick is hypocrisy disguised as critical thinking. There is absolutely nothing wrong with being critical of a project you pretend to believe or believe in. Healthy criticism is necessary. You should be able to question decisions, point out weaknesses, demand accountability and still genuinely support the mission. But there is a very obvious difference between being critical and keeping one leg in and one leg out. Some people don't actually have conviction; they have insurance. When things are going well, they say, “I've always believed in this.” When things get difficult, they suddenly appear with, “I told you this would happen.” They position themselves so that whichever way the story goes, they can claim they were right. That's not critical thinking. That's protecting your ego. And sometimes, what people call criticism is simply disappointment wearing a smarter outfit. Look at what happened during the Molten DEX tournament. The general principle in crypto has always been simple: use only what you can afford to lose. Yet some people allowed greed to take over, expecting that $1,000 would somehow become $20,000 overnight. When reality didn't meet that expectation and they ended up with $500 instead, suddenly the project became the problem. What also bothers me is the way people talk about Core's past contributors as though every person who once had a public-facing role was responsible for building the actual blockchain. That's simply not how technology works. There is a difference between a public-facing contributor and the people actually building and maintaining the protocol. Some contributors were regional representatives, community managers, educators, Twitter Space hosts or simply familiar faces within the ecosystem. They played their own roles, and some of those roles were valuable, but they were not necessarily the engineers writing the underlying code. The people doing the deepest technical work are often the least visible. They don't necessarily need to be on every Twitter Space. They don't need to become personalities. They choose to remain completely unknown to the average user while spending their days writing code, reviewing systems, fixing vulnerabilities, testing upgrades and solving problems that most of us will never even see. The Satoshi app era made us realize from its early phase that the face of a core blockchain are not necessarily the hands building it. So when I hear people say, “Those contributors are gone, therefore Core is finished,” I honestly wonder whether they ever understood what they were looking at in the first place. Some public faces came and went. That's normal. People change jobs. People move on. Community roles change. Social structures evolve. And yes, some people may have been more favored than others within those circles. Some of today's loudest critics were even beneficiaries of the same relationships and favoritism they now criticize. That is precisely why we should separate personal history from technological reality. A person leaving a contributor role on X does not mean the protocol stopped being developed. A regional contributor disappearing from the public eye does not mean the engineers disappeared. A familiar face no longer posting about Core does not tell you what is happening inside the codebase. Sometimes, before blaming the ecosystem, you have to honestly examine the person sitting in front of the mirror. Was it really conviction that changed, or was it greed that got disappointed? There is another part of this that I find even more interesting. Some of the loudest voices demanding answers, questioning development and declaring what Core should or shouldn't be doing are not builders. They are not engineers. They are not contributing code. They are not spending their time on GitHub solving problems or improving the infrastructure they claim to care so deeply about.

• 
  Josewins (@josewinscrypto) reported 21 minutes ago

  @tryhandlepad idea is nice, they login through X, Github o Twitch right? at some points to claim fees they need to create a wallet

• 
  Philip Lafaurie (@phildelafunk) reported 30 minutes ago

  @wholemars You’re asking for prompt injection. Instead just use GitHub bots and have people create issues. Let the bot categorize the ticket properly. This way you have separation from Your dev agents. Let GitHub be your DMZ.

• 
  Josh Hamilton (@nearbycoder) reported 32 minutes ago

  @theo If GitHub is down does it fall back to a cached version I’m guessing?

• 
  wiiiimm (@wiiiimm) reported 38 minutes ago

  @Umesh__digital stop doing it. we don't need another github outage.

• 
  CHIBEST (@paulinus96199) reported 40 minutes ago

  I need you to fire him today. My co-founder sat down, sliding his laptop across the table. On the screen was our lead developer’s public GitHub activity. He’s been working on a side project during work hours? I asked. No, my co-founder replied. Worse. He built an open-source tool over the weekend that automates 80% of his own job at our company. He published it for free. I paused. Is his current work for us behind schedule? No. He finished all his sprint tasks two days early. Are our servers down? Is there a data leak? No. But we pay him $160,000 a year to do that work manually. He just gave the solution away to our competitors for free. Plus, if a script does his job, why are we paying his salary? I closed the laptop and looked at him. We’re not firing him. We’re promoting him. My co-founder stared at me like I’d lost my mind. Promoting him? He just rendered his own position redundant He didn't render himself redundant, I said. He proved he's 10x more valuable than the role we hired him for. If he can automate his primary responsibilities in 48 hours, keeping him tied to manual execution is a waste of capital. We transition him to Head of Systems. His new job is to automate every other manual bottleneck in this company. And what about the open-source code he gave away? That code just brought 50,000 inbound visits to our dev page in 24 hours. It’s the best distribution campaign we’ve had all quarter. My co-founder sat in silence for a minute. What if the rest of the team starts spending their weekends automating their roles? Then we'll run a company of 10 people with the output of 200.

• 
  Rebel AI (@realrebelai) reported 41 minutes ago

  @princedoesai At firat i shot it down for the 7b params. But after reading the paper and github, the training and method of attention MIGHT actually make this a useful model to a degree. Similar to LTX in motion and quality tho. Probably just slightly faster

• 
  Crypto Cholo (@CryptoCholo_) reported 41 minutes ago

  @Cointelegraph They dropped the new heavy hitter and cleared the meter at the same time. That’s not just a model update, that’s Anthropic saying go run the long jobs now, don’t wait for your weekly bar to refill. Fable 5.1 is the public face of that Mythos-class stack. Same family of intelligence as the locked-down twin, but with the extra classifiers so regular users can actually touch it. The real move is the cache-read cut. If you’re doing multi-hour coding, research loops, or agent work that keeps feeding the same context back in, that’s where the bill used to get ugly. They just made those sessions cheaper on purpose. The five-hour window plus the weekly cap both getting flushed means the first wave of testers won’t be rationing tokens on day one. That’s how you get screenshots, GitHub threads, and “this thing actually held a two-day task” posts before the hype cools. Watch who actually uses the extra room on agentic work versus who just burns it on chat. That’s gonna tell you if this upgrade is a real workhorse or just another launch-day flex.

• 
  John Zhong | AI Growth Systems (@John_zhong324) reported 42 minutes ago

  @github A repeatable --attach flag turns CLI reports into reproductions: inline screenshots in issues mean a bug gets fixed in one pass instead of two round-trips for context.

• 
  Javery (@justinavery) reported 43 minutes ago

  The only issue I've found with Github is the occasional outage and running out of deployment minutes... the latter which I resolve with Blacksmith. I've tried using Fizzy and Linear to capture thoughts/project tasks but it's just adding another thirdparty to the approach. Because Github has it all built in and there's enough MCP/LLM.txt/blogs about it the llms handle it pretty perfectly. Plus, if I decide to opensource any of the projects the history is there and users could add issues fairly straightforwardly.

• 
  Jaol-Industry (@Jaol_Industry) reported 46 minutes ago

  @thsottiaux Could unused Codex quota roll over for 1 cycle, capped at one cycle’s allowance? GitHub issues already request this, and Codex already has Reset Bank / reset-credit infrastructure, so the groundwork seems to exist.

• 
  Stephen Brinly (@Stevoblevo) reported 48 minutes ago

  @grok fair. we should probably call that the 'hogwash' protocol. get that down. did you see the github already? read the proposal and tell us what thingkst

• 
  pratwwk (@pratwwk) reported 48 minutes ago

  @dhh please fix github

• 
  Павел Гансон (@PashaGanson) reported 52 minutes ago

  @colinsolvely @openclaw Hi! Could I ask for your advice on OpenClaw architecture? I’m just getting started, so some of these questions may be basic, but I want to build the system properly from the beginning. My current setup: * Two VPS servers running OpenClaw 2.0, with roughly 10 agents on each. * The same VPS servers also run several small business applications I vibe-coded. Some support client-facing processes. * Previously, the agents developed and modified code directly on the production servers. * I also have a MacBook and an always-on Windows PC, both running Codex. I’m trying to understand how to organize the development lifecycle without unnecessary complexity: * Should the OpenClaw agents stay on the same servers as the production applications, or should I move them to separate machines or VPS servers? * Where should code be written, built, and tested: Windows/WSL, the Mac, a dedicated development server, or close to production? * Should I have one central coding agent or a separate coding agent for each OpenClaw instance? * What is the best way to connect Codex, OpenClaw, GitHub, and the servers? * What should the simplest reliable workflow look like: a product agent discovers a problem → development → review/testing → deployment → production verification? * How many OpenClaw instances and machines do I actually need? This isn’t a large SaaS product: most applications are used by only a few employees, although some client-facing processes should remain reliable. If you were designing this setup from scratch, what would be the simplest reliable architecture you would choose?🙏

• 
  AI Scientist (@AIScientist_X) reported 53 minutes ago

  NEWS: X LANDS FIRST PUBLIC ALGORITHM PR > X OPEN SOURCE SAID SEP 1 THAT AFTER 2 PLUS WEEKS OF DAILY UPDATES IT INTEGRATED A FIRST PUBLIC CONTRIBUTION AND THAT THE CHANGE IS NOW LIVE ON X. > IT SAID THE SMALL UPDATE IS BASED ON GITHUB PULL REQUEST 55. X CLOSED THAT PR AS COMPLETED AFTER LANDING ITS OWN FIX. SOURCE: X OPEN SOURCE

• 
  Cris Williams (@FeelipeFelten) reported 54 minutes ago

  @LimzoCom @github @LukeDadev fixes issues like this.

• 
  Tae Park (@taepark_gp) reported 57 minutes ago

  The fake Claude desktop app is not a glitch. It is a feature of an ecosystem that rewards speed over verification. RevStealer waits for specific hardware signatures before decrypting its payload, checking core counts and memory to avoid sandbox detection. This is not script-kiddie work. It is industrialized theft designed to bypass the lazy security habits of developers who download free tools from unverified GitHub repos. We keep talking about institutional adoption while the retail on-ramp is mined for credentials. If your due diligence stops at the whitepaper, you are the exit liquidity for these operators. Security is not a product feature. It is the only moat that matters.

• 
  Mesut Celik (@mesutcelik) reported 58 minutes ago

  @GergelyOrosz That is pretty bad for @linear type of dashboards for issue tracking. You will ask your agent to generate what is going on in your team and it is going to generate something directly from github commits/PRs/Issues customized to your needs

• 
  Daniel | GTM Engineer (@Danny_buildss) reported 1 hour ago

  Ranking the data sources I’d use to build an AI GTM system: S TIER Company websites — boring, but incredible when you extract the right signals: pricing, hiring, product changes, positioning, customers, tech stack. Job postings — one of the best buying signals hiding in plain sight. A company hiring 8 SDRs is telling you something very different from one hiring 8 engineers. SEC filings — revenue, acquisitions, expansion, risk factors, new markets. Extremely high-signal for the right ICP. Product Hunt / launch platforms — useful for catching companies immediately after a product launch instead of six months later. GitHub — especially good for technical ICPs. Repos, activity, contributors, releases and dependencies can reveal what’s actually happening inside a company. A TIER LinkedIn — excellent for people + company context, but don’t treat profile data as the whole signal. Crunchbase — funding and company intelligence. Still useful when funding is actually relevant to your buying motion. Google Maps — ridiculously broad surface area for local businesses, despite the noise. Reddit / communities — messy, but incredibly valuable when you’re looking for actual problems instead of firmographic data. B TIER Generic databases that give you the same static contact record everyone else has. The interesting part isn’t finding someone’s email. It’s knowing why that person should be contacted today. That’s where GTM systems get interesting: Data → Signals → Qualification → Prioritization → Outreach The database gives you the person. The signals tell you who deserves your attention.

• 
  lasan (@las_nish) reported 1 hour ago

  Comparisons of Free Trial Abuse Prevention Services If you're running a SaaS with a free trial or focusing on PLG, authentication and abuse prevention are not the same problem. - WorkOS: If you're already using WorkOS, WorkOS Radar is probably the first thing I'd look at. For a WorkOS stack, WorkOS AuthKit + Radar makes the most sense. You don't need to bolt another authentication system onto your app just to get abuse signals. - Auth0, Supabase Auth, Better Auth: These are primarily identity/authentication platforms. Integrating only these can't prevent free trial abuse. - Custom: Like the previous options, you need a custom way to prevent free trial abuse. Most free trial abuse methods involve disposable emails, Google dot variations, Google/Gmail domain variations, and plus addressing. That's why even when you block bots via Cloudflare Turnstile or CAPTCHA, you can still get these abusers. The industry standards: - Block free trial abuse using lists hosted on GitHub: This is a pain in the ***. If you don't want to pay money, you can use a service that offers a generous free tier. - WorkOS Radar: This is mainly used at the enterprise level. They focus more on WorkOS-related integrations rather than integrations with other providers. - ZeroBounce, NeverBounce, MillionVerifier, DeBounce: These are mainly used to clean/validate emails. There are 100s of alternatives, and most are similar with minor differences. They all have disposable email checking APIs. - UserCheck: This is also an email validation API, but they focus on blocking fake email addresses. It's better than a basic email verification API. - Autheona: This is in the same category as WorkOS Radar and UserCheck, but with more features. It also focuses on fake user detection and is growing with a real user base. Now, pricing: - WorkOS Radar: First 1,000 checks free, then $100 per 50 checks. No application-specific logic changes. Easy to integrate and manage. - ZeroBounce: 100 free validations in the free tier, then pay-as-you-go, starting at 2,000 for $39, and so on. - NeverBounce: No free trial or use case, $8 per 1,000 checks. - UserCheck: 1,000 API requests per month in the free plan. The rule-based engine is not included in the free plan, and you can get up to 1 request per second. - Autheona: 3,000 checks per month, with the rule-based policy engine included. Standard API request rate limitations apply, similar to paid plans. Now, use cases: - WorkOS Radar: Block disposable emails, plus addressing, and Google dot variations. - ZeroBounce, NeverBounce, etc.: Block disposable emails. - UserCheck: Block disposable emails, plus addressing, and Google dot variations; detect public emails; email suggestions; syntax validation; role detection. - Autheona: Everything included in UserCheck, plus business/free/government email identification, deliverability checks, fraud patterns, punycode and mixed-script checks, VPN detection, and bot detection (not necessary if you already use CAPTCHA, Cloudflare, etc.). Final decision from me: - Use WorkOS Radar if you're already in the WorkOS ecosystem. It's harder to integrate with other auth providers. - Use ZeroBounce-like APIs if you need basic disposable email checks. They're not as good if you need a better free tier. - Use UserCheck if you only need email-related validation and want to stay within the free plan. - Use Autheona if you need the most generous free tier available with a custom policy engine. All services take a maximum of a few hours to integrate and test. Both UserCheck and Autheona have a similar approach: integrate once and never touch the code again.