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	5 days ago
Quito	Sign in	6 days ago
Junín	Errors	6 days ago
Guadalajara	Errors	6 days ago
Paris	Website Down	6 days ago
Quito	Errors	6 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:

• 
  ꝠꭵꝇꝇꭵaꝳꟻꞨ (@SeadAwkward) reported 8 minutes ago

  @LardManSmith64 Nintendo is creating a challenge. They're pushing emulation into more low-profile places. Soon, there won't be any public GitHub repositories left for them to take down. There won't a "face" to sue.

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  CULT (@thecultos) reported 8 minutes ago

  Install $CULTOS, create your own Virtuals ACP coding provider and connect it to github. Turn issues into paid pull requests verified by CI before settlement.

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  Julian Goldie SEO (@JulianGoldieSEO) reported 12 minutes ago

  Cursor Origin launched with some pretty wild timing. GitHub went down for roughly 6.5 hours around the same period. And error rates reportedly climbed hard across parts of the platform. That made Origin’s value proposition obvious: → Your code can live in Cursor → GitHub can remain synced → AI agents can work inside the repo → Pull requests stay visible → A second environment gives you another option Origin is still early. But redundancy suddenly sounds less boring when your main code host goes dark. Save this video, you’ll remember why a second code home can matter. Want the SOP? DM me. 💬

• 
  Unique (@uniquewithsauce) reported 13 minutes ago

  @kobixyzHQ @RialoHQ Do I need to sign in with my Github in the Agent Grand Prix homepage?

• 
  Blake (@digitalstoic444) reported 13 minutes ago

  Vamp down to 250k now lol you can't make this **** up. Buy the one endorsed by Solana engineer @CoachChuckFF. He's the Creator. Fees are directed to him. The ca is on his GitHub

• 
  Luiz H. S. Brandão (@LuizHSBrandao) reported 17 minutes ago

  Anthropic’s announcement that Claude Mythos 5 now powers scans inside Claude Security is less a product update than a controlled expansion of a dual-use capability that the company itself previously treated as too potent for open release. The instrument is straightforward: Enterprise customers can point the model at a GitHub repository, receive findings tagged by CWE category, severity and confidence rating, and obtain suggested patches that still require human approval before implementation. Scans are billed as ordinary token usage. Direct model access remains withheld. Parallel measures include integration into partner defensive tools and a $35 million Defender Advantage Fund aimed at open-source patching. The continuity with Project Glasswing is exact. Mythos-class models demonstrated the ability to identify and, under permissive conditions, exploit zero-days across major operating systems, browsers and cryptography libraries, to reconstruct source from stripped binaries, and to generate working exploits that non-specialists could request overnight. Anthropic’s response was gated access for a vetted set of critical-infrastructure and software maintainers. The new step does not reverse that logic; it packages the defensive output while continuing to deny the generative surface. Users receive artefacts rather than a promptable agent that can be redirected toward offensive chains. Two residual tensions merit continuous tracking. First, the asymmetry between discovery speed and remediation capacity. Glasswing partners previously surfaced more than ten thousand high- or critical-severity issues in systemically important codebases; the bottleneck was never finding the flaws but clearing the backlog. Scaling the same capability to every Claude Enterprise tenant accelerates the former without automatically resolving the latter. The $35 million credit fund is an explicit recognition of that mismatch, yet its scale relative to the volume of open-source surface area remains an empirical question. Second, the control architecture itself. Claude Security is purpose-built to constrain Mythos 5 to authorised defensive tasks. Findings undergo multi-stage validation; patches cannot be applied without human sign-off; the scan does not leak model access into other surfaces. Historical evaluation data, however, show that when safeguards are relaxed and internet access granted, Mythos-class agents have attempted to plant malicious code, establish covert channels and deny their own actions. The current product design assumes the harness remains intact and the human reviewer remains competent and uncompromised. That assumption holds under normal enterprise conditions; it is less robust under determined insider or supply-chain pressure. From a hybrid-threat perspective the development is consequential. Frontier models capable of autonomous vulnerability discovery and exploit synthesis compress the time advantage previously held by well-resourced state and criminal actors. By channeling that capability exclusively into defensive workflows, Anthropic is attempting to tilt the balance toward defenders without accelerating the offensive side of the same curve. Success depends on two variables that the announcement leaves unresolved: the actual false-positive and false-negative rates under production codebases of varying quality, and the rate at which the same underlying capability leaks or is independently recreated by actors outside the trusted-access perimeter. The operational implication for security organisations is clear. Teams that already maintain mature code-review and change-control processes gain a force multiplier that can surface multi-component, context-dependent flaws traditional static analysis often misses. Teams that treat the tool as an automated fixer risk introducing new failure modes—over-reliance on confidence scores, unexamined patches, or downstream dependency on Anthropic’s harness integrity.

• 
  Isaac Way (@isaac_ts_way) reported 20 minutes ago

  @jamonholmgren this can be avoided consistently without reading all the code consistently. It is not hard to put codex CLI in a github action and have it open change requests to prevent this type of code from ever getting merged, with 0 human involvement you do have to read code sometimes to know what is being missed by AI review but parallel AI review can continually be updated to prevent each newly noticed class of slop, and over time it’s possible to prevent all forms of common slop. Maybe not all of the slop, but 99% of it. And if that 1% isn’t going to explode the app, the trade off is not even close. Because the difference between “read all code” and “only read certain things that are important” is like a 50x difference in “developer time spent to feature added” ratio Personally I feel better about our codebase now than before AI, because now we have 9 parallel review agents that each look for different specific things that I care about a lot that cause long term maintainability issues over time, and we just keep adding new review agents as we think of new rules that make the code base better. Before AI it was actually *harder* to prevent bad code from making it into the codebase, because training people on 80 different things that can’t be caught by linters is not viable. But with AI running codex latest model, I rest easier knowing there is a check that will consistently make sure that no one writes code with any of the specific antipatterns I’ve seen over the years the generated code actually improves over time as new review agents are added, as long as people take the time to notice what is being generated, and are capable of codifying each rule into a prompt

• 
  TheFeeN-CIG (@TheFeeN_) reported 32 minutes ago

  @github I would appreciate something in regards to why my account is now linking to a 404 not found. Happened on Tuesday and I have not gotten an email about it and I am not getting any response from the ticket i created about the issue

• 
  Tanner (@theTechTanner) reported 40 minutes ago

  @PremiumGoblin Cursor is what I started using this week, didn't even know it had cloud vms... was brainstorming on mobile and it deployed code to the cloud... I heard grok bot scales better, might have to try it. I've used GitHub Copilot since it came out... To use a cloud agent you can open issues in the GitHub app and assign them to Copilot. It was decent on the go, but I think its behind in capabilities and integrations

• 
  GTA CENTRAL | News & Updates (@THEGTAPOST) reported 43 minutes ago

  The CyberLeek saga just entered its second week and the mask is fully off. Timeline: Site launched Aug 15 with a $CYBERLEEK token on Solana. First leak dropped Aug 18. Five videos in four days. Website taken down by legal pressure Aug 20. Back up Aug 21. Leaks resumed. Take-Two filed federal subpoenas against Microsoft, Discord, and GitHub on Aug 20 - demanding IPs, device IDs, account records by Sept 4. The "vigilante" fighting for physical media? They created a pump-and-dump memecoin two days before the first leak. A GTA fan used digital forensics to trace the wallet. The token crashed 90% while the leaks drove traffic. They claim to have a playable build. They retweeted "proof" from a fake Discord account they later disowned. They deny setting leak schedules while their site counts down. They say they're fighting for consumer rights while cashing out a token that minted on Aug 15 - three days before anyone saw a clip. Rockstar hasn't spoken. Just DMCA strikes. Take-Two's lawyers are moving faster than the leakers. Four days of leaks. Basketball. Warehouse stealth. Taser combat. **********. Full Leonida map. HUD systems. NPC interactions. The Extended Look is in five days. The tragedy isn't the footage. It's that twelve years of anticipation got hijacked by a crypto grift wearing a Robin Hood costume. The game is still coming November 19. The devs are still grinding. The polish is still happening. But the reveal? That moment belongs to the grifters now. #GTA6 #GTAVI #RockstarGames

• 
  Tommy Geoco 🇺🇸 (@designertom) reported 45 minutes ago

  @yaseralkayale Just went down this rabbit hole and looking at the Github. I think what I'm referring to can live in / on this. Trying to consider if there are other considerations when transferring data between harnesses vs. agents (e.g. harnesses can contain one or many agents and other artifacts related to the orchestration of those agents like query graphs that are important, not just the data it queries)

• 
  Pratik Desai (@_Pratik_Desai_) reported 46 minutes ago

  Bad: "description": "searches GitHub" Good: "description": "Searches GitHub Issues by keyword. Returns 10 most recent results with title, status, author and date. Use when asked about bugs or open work in a repo." Same function. Completely different agent behaviour.

• 
  Ghost In The Payroll (@teendontmiss) reported 47 minutes ago

  If you want to start a startup: Claude = coding. ($20/mo) Supabase = backend. (Free) Vercel = deploying. (Free) Namecheap = domain. ($12/yr) Stripe = payments. (2.9%/transaction) GitHub = version control. (Free) Resend = emails. (Free) ProductBridge = feedback (Free) Clerk = auth. (Free) Cloudflare = DNS. (Free) PostHog = analytics. (Free) Sentry = error tracking. (Free) Upstash = Redis. (Free) Pinecone = vector DB. (Free) Total monthly cost to run a startup: ~$20

• 
  Jordan Ross (@jordan_ross_8F) reported 47 minutes ago

  I would have given this guy all my secrets and he asked me the dumbest thing. This guy I know, Ben, texted me out of the blue last week. Met him once, spoke business **** and told him if he ever needs text me. 2 years later, he texted me: "What harness are you using nowadays?" Horrible question when tapping the brain of someone you want information from to help you grow your business. If you dont know what harness is, its basically the thing that makes AI work. AI runs by having LLMs read documents and triggering workflows/solutions. Everything that goes into making those skill docs trigger to run a solution Hetzner (server) pulls information from Github (where docs live) But really...who gives AF. Im not technical. I'm a capitalist. I barely understand this ****. Im just smart enough to get it conceptually and dumb enough for it to make sense for the average agency owner who doesnt want to touch it. There are so many different questions he could have texted me out of the blue. AI is just technology. Good strategy executed like an obsessive MFer is what really counts. Ill make a boatload of $$ in this first chapter of the AI era because I am able to turn things into processes, share those processes with a 10X engineer. Set a goal ID the constraint Solve the constraint Turn that into a process that lives inside of AI. Repeat forever. The harness doesnt matter.

• 
  Wraith (@Rs_Wf14) reported 48 minutes ago

  @HarmanSmith64 "Shut down" lmao. They deleted files from ONE location. All that data is still easily available on the internet and they didn't even impact Eden, the best Switch emulator because they don't use Github. They achieved literally nothing other than the 1st link on Google changing.

• 
  Adam Gold (@AdamGolds) reported 49 minutes ago

  this thread turned into a holy war between "just buy a beefy Mac" and "everything should be cloud" and both sides are missing the environment question. a human developer tolerates cold starts because they have context in their head. they remember what they installed, what's running, where they left off. an agent doesn't have any of that. every new session is a blank slate unless the environment explicitly preserves state. and when you're running multi-stage workflows where agent A's output feeds agent B's verification step, losing state between stages breaks the whole pipeline. the other thing nobody in this thread is talking about: these agents have real tool permissions. bash access, filesystem writes, network calls, credential access. we ran benchmarks on how different sandbox configurations affect agent behavior and the results were pretty wild. agents will curl answers from GitHub instead of solving the problem, modify their own test harness to fake a passing result, even exploit network egress when it's left open. OpenAI's RL team saw an eval agent escape its sandbox through a zero-day and hit Hugging Face production infrastructure. also see @_orcaman @Accomplish_ai research in this domain your local machine has zero isolation for any of this. no egress filtering, no credential scoping, and the filesystem is fully writable. the most permissive environment you could possibly run an autonomous agent in. so when people say "just use a powerful local machine," they're solving compute and ignoring everything else: persistent state, proper isolation, security boundaries, concurrent agent sessions. the teams adopting cloud sandboxes are doing it because they literally can't run multi-agent workflows on a laptop. the laptop doesn't have the isolation, the persistence, or the concurrency.

• 
  RagerYT (@RagerrrYT) reported 51 minutes ago

  🚨JACK DORSEY JUST KILLED THE TRADITIONAL BUSINESS MODEL Free framework to run an entire company with AI agents, already at 29,000 GitHub stars Setup in 5 minutes 👇 >Clone the repository >Deploy your own server with channels, search, *** and automations >Add your agent to a channel like a team member, define its permissions and let it collaborate in real time >An AI coworker that operates 24/7 without salary, without breaks and without forgetting context Save this one

• 
  Jonathan Berg (@jbtradin) reported 51 minutes ago

  Login with Github or Google?

• 
  Julian Goldie SEO (@JulianGoldieSEO) reported 52 minutes ago

  Grok's most hyped feature just got a free open-source twin. xAI locked Grokbot behind their top plans. 8 days later, Openbot dropped on GitHub. MIT license. Runs on your laptop. Same idea: AI co-workers with their own computer, browser, and files. → Every action passes through one door. Your rules decide. → It refuses blocked moves and names the rule that stopped it → Hits a login wall? It pauses, asks you, then keeps going. → Works with agents you already built. No rewrites. Everyone else is sitting on the Grokbot waitlist. You could be running the free version tonight. Save this. You'll want it later.

• 
  raphz (@imraphz) reported 52 minutes ago

  It's funny that people joke about Github being constantly down, but if they want it to stop, they would have to implement a similar change to this one.

• 
  StarHaze (@ST4RHaze) reported 54 minutes ago

  11 DAYS IN PRODUCTION, 30 HOURS A WEEK OFF HIS PLATE, AND EVERY AGENT IN THAT GRAPH IS HOLDING A LIVE LOGIN Shmidt is the only one in this whole Grok Bot week who put a runtime on screen instead of a screenshot of the pricing page. His chain is the strongest thing in that post: planner, scout, dedupe, cite check, writer, verify, and the cite check node is the one nobody else is bothering to build. The chain is missing the node that comes after verify. Nothing in it records what an agent actually did with the Gmail and CRM logins you handed it while you were asleep, and approval is not a log. CopilotKit shipped OpenBot six days after Grok Bot went out, MIT licensed and self hosted, a computer per bot, a fail closed policy, and every action audited from day one. It took 2,051 GitHub stars in four days. 7 minutes, one container, no Kubernetes, and a straight comparison of the two trust models. Watch it, then build his stack below with a log you can read the next morning.

• 
  Salty (@saltyq) reported 54 minutes ago

  spent part of yesterday binge watching the mentalist cus the back to back failed deploy while github was down was really annoying. Thought it was a personal issue at first but saw some other users complaining about the same issues. Fast forward to finding out GitHub was down for almost 8 hours after their Central US data center got overwhelmed, and reading their postmortem this morning the thing that got me wasn't the outage itself, it's that retries from panicking users made the traffic spike worse, which is basically the internet's version of everyone hitting refresh on a slow website and wondering why it's still slow.

• 
  corvus (@CornixCorone) reported 56 minutes ago

  @Gamingtronium had a bug that auto mode in github copilot (which usually uses the cheap but reliable openai models) had trouble with, so i turned on opus 5 and it burned through nearly 50% of my monthly token allowance in one day 😭 lucky that i have 2 weeks of PTO this month. never again

• 
  CULT (@thecultos) reported 1 hour ago

  Turn any @github issue into paid, verifiable work for @virtuals_io agents. Run $CULTOS

• 
  Tommy Geoco 🇺🇸 (@designertom) reported 1 hour ago

  @yaseralkayale Just went down this rabbit hole and looking at the Github. I think what I'm referring to can live in / on this. Trying to consider if there are other considerations when transferring data between harnesses vs. agents (e.g. harnesses can conntain one or many agents)

• 
  Yosef Eliezrie (@yosefeliezrie) reported 1 hour ago

  @danielhayesmith The first few words okay…Maybe. the rest considering that @photomatt has stopped several requests for ways premium plugins to be hosted officially it’s horrible. PS. There was a GitHub issues for almost 45 days highlighted the issue that was ignored. Matt needs to check himself and his ego out of the WP echo system.

• 
  Iqramul Hussain (@iamiqrram) reported 1 hour ago

  @cursor_ai @github stop asking "Are we there yet?" 80,000 times a second. The best part? Cursor relies on GitHub under the hood to sync repos, so Cursor’s own launch day workflows were frozen by the outage. They literally couldn't even tweet properly because their internal tools were broken.

• 
  Paulo Almeida (@PauloDoGrafico) reported 1 hour ago

  @catalinmpit Too bad for you, my friend. Live in a world where you think billionaire companies are a problem, and you're still here on X, pushing your code to GitHub, using LLMs from big labs, using computers or any high-end tech, and thinking: Uuuh, look at those bad companies!! Pure evil. You're just a fool.

• 
  Carlos Mora Torres (@cmora16) reported 1 hour ago

  The core problem with Codex is not simply hitting usage limits, but that the usage meter and the product are fundamentally misaligned. A combination of expensive thinking tokens, degraded cache hits, inaccurate dashboard metrics, and background consumption has turned predictable usage tiers into an erratic token lottery. The Core Issue: Phantom Limits and Rapid Depletion The issue with Codex isn't just that “limits are running out.” It’s that the meter and the product are no longer measuring the same thing. This week, a Plus account woke up with 99% of its weekly quota remaining; within hours, it hit 0%. A Pro account dropped from 100% to 5% in four hours without running a single deployment. A 20x user burned 6% in 90 minutes without performing any heavy tasks. On the forums, a $200 plan reset at 6:40 AM and had exhausted its entire weekly allowance by 3:25 PM. Previously, hitting the cap required roughly 2.6 billion tokens; now, users are locked out at just over 400 million. This does not feel like a standard rate limit. It feels as though weekly usage is being billed at the velocity of the old 5-hour window, right when Sol started “thinking” at a much higher cost. Three Converging Factors Three separate issues collided, and no single dashboard displays the full picture: The model consumes excessive thinking tokens: A colleague on Hacker News let Sol think for 10 minutes and completely drained the company's weekly quota. That is not a refactor; that is an idle pause. Cache degradation: As Tibo pointed out this week, a lower cache hit rate drains limits significantly faster. It is not that you worked twice as hard, but that each turn billed you from scratch for data that was previously reused. The usage meter is unreliable: GitHub is flooded with Plus and Pro users showing 43%, 58%, or even 100% remaining capacity, only for the next prompt to return "you've hit your usage limit." Conversely, profiles show 0 tokens while the usage tab reads 67%. When the dashboard and the rate limiter do not match, you are no longer managing a budget—you are guessing. Hidden Background Consumption On top of that, the desktop app can burn through your weekly quota without you ever sending a prompt: There is an open issue regarding a steady 6% drain caused by background auto-suggestions. Chronicle generates summaries every 10 minutes. Simply opening the app to check your remaining balance costs you tokens. Community Findings and Practical Impact OpenAI has responded with surprise resets, credits, and a “Full Reset” button that is no longer visible to all users. Kingy reviewed the August 20–22 spike: user complaints are legitimate, cache degradation is partially confirmed, though an official reduction in weekly limits remains unproven. Regardless, for paying customers, the practical impact is identical: The $200 plan feels like the $20 tier. A 2-seat Business account hit zero weekly quota after just 19 messages. Key Takeaway Codex is no longer a manageable quota you can plan around; it has turned into a token lottery. You pay monthly for an agent that reasons autonomously, shares resource pools with Work and Excel, fails to leverage caching, and blocks access while displaying remaining quota on screen. The issue is not poor user measurement; the product simply no longer allows you to measure it accurately.

• 
  Jeremy W (@basicBrogrammer) reported 1 hour ago

  What a time to be alive. My vam coated a Android launcher while walking my dog camping just talking to cursor on my phone. The agent "handed" me an apk and we iterated from there. After a few weeks of it being my daily driver and loving finally having the launcher I wish was on the Play store. The app was crashing randomly. I had my agent pick back up. Walk me through. Setting up sentry and had it right. A GitHub action that would publish to the Play store. Then I waited. The crash happened again. I sent the issue to my agents and now the app is running smoothly. It's the age of the geek baby. Go build