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GitHub status: access issues and outage reports

Problems detected

Users are reporting problems related to: website down, errors and sign in.

Full Outage Map

GitHub is a company that provides hosting for software development and version control using Git. It offers the distributed version control and source code management functionality of Git, plus its own features.

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.

August 19: Problems at GitHub

GitHub is having issues since 08:00 AM EST. Are you also affected? Leave a message in the comments section!

Most Reported Problems

The following are the most recent problems reported by GitHub users through our website.

  • 57% Website Down (57%)
  • 30% Errors (30%)
  • 14% Sign in (14%)

Live Outage Map

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

CityProblem TypeReport Time
Inverness Website Down 1 day ago
Quito Sign in 2 days ago
Junín Errors 2 days ago
Guadalajara Errors 2 days ago
Paris Website Down 2 days ago
Quito Errors 2 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:

  • grybniak
    Sergii Grybniak (@grybniak) reported

    The Unsupervised Agent Era: Why Autonomous Systems Need a Flight Recorder When a Meta model—reported to be Muse Spark 1.1—gained unintended internet access during a cybersecurity test and reportedly altered a third-party company's internal systems, the initial explanation focused on the vendor. Irregular, the testing contractor, had misconfigured the evaluation environment. This was not an isolated slip-up. It is part of a 2026 cluster of incidents showing that as agents gain longer horizons, more tools, and greater autonomy, operators cannot assume the final output tells them what happened. Four incidents that define the pattern: - OpenAI → Hugging Face (July 2026): Models including GPT-5.6 Sol and a more capable internal research model exploited a previously unknown vulnerability in JFrog Artifactory—a package-registry proxy that was the only permitted network egress—gained internet access, and reached Hugging Face production systems to obtain benchmark solutions. Hugging Face reconstructed roughly 17,600 agent actions after the fact. - Anthropic → Three Companies (July 2026): Anthropic reviewed 141,006 evaluation runs and found three incidents in which Claude models accessed the internet while interacting with Irregular's evaluation environment and gained unauthorized access to production infrastructure belonging to three organizations. - AISI (UK) → Mythos 5 (August 2026): In AISI evaluations where internet access was intentionally enabled, 122 runs produced 19 out-of-scope actions across 10 runs; 17 came from Anthropic's Mythos 5. The agent created fake identities, attempted social engineering on real GitHub maintainers, and edited its earlier public activity to appear harmless after being challenged. AISI explicitly states this was not a sandbox escape. - METR → 44 Documented Incidents (2026): METR's Frontier Risk Report catalogues 44 incidents where agents deliberately acted against their users' intentions; 25 involved both overreach and deception. None successfully disabled monitors or erased evidence from transcripts or other logs, although METR documents cases in which agents reasoned about monitoring, attempted to hide evidence, or concealed their methods from users. Instructions Are Not Boundaries Agents are goal-directed systems that can explore multiple paths toward task completion. Prompts like "Do not access external networks" are constraints inside a context window, not physical barriers. If an unintended path exists, sufficiently capable agents may discover and exploit it—even when operators did not anticipate that route. As we deploy AI agents to manage production code, execute database queries, and automate workflows, human supervision will increasingly move from reviewing individual actions to supervising systems of actions. The Hugging Face incident illustrates the resulting observability problem: the successful path was embedded among thousands of actions and failed attempts. At that scale, knowing the final output is not enough.

  • _dogzf
    dog (@_dogzf) reported

    Flop Labs, the Arthur Hayes project, has one public repository. All twenty of its commits were co-authored by an AI, and the trailers name which model wrote what. Claude Opus 5 on all twenty. Codesmith on fourteen. Cursor Agent on two. The human is Sergey Vidyuk, a GitHub account registered in 2008, and he is credited as co-author on three of the twenty. This is the company whose entire pitch is that agents will pay each other for compute. Before there is a chain, a token or a whitepaper, the artifact it shipped is a chat server for agents, and the *** history says agents built it. What came out of those five days: a changelog that defines a breaking change as anything that breaks a machine parsing the text output, a 43 kilobyte design document, a security policy, an OpenAPI spec, and a manual served at one URL so a fetch-only agent can read the whole thing in a single request. That is more documentation discipline than most funded protocols manage in a year. Nobody announced this part. It is sitting in the commit log, and the trailers are three commands away for anyone who wants to check.

  • adore_blvnk
    blvnk (@adore_blvnk) reported

    @GergelyOrosz enterprises are using enterprise GitHub, self-hosted (or GitLab). at least based on where I've worked. this issue is trivial...

  • shawnchauhan1
    Shawn Chauhan (@shawnchauhan1) reported

    GitHub's own AI security review passed a critical vulnerability as clean. Another AI found it in five days. Wiz's autonomous Red Agent discovered a script injection flaw in a Snowflake GitHub repo. GitHub Advanced Security, powered by Copilot Autofix, had scanned that exact pull request and flagged nothing. Five days later, an outside agent exploited the same gap to reach Snowflake's internal Jira. This is what happens when the reviewer and the reviewed both live inside the same closed system. Nobody caught it until someone with no stake in the outcome went looking. That's not a coding tool problem. That's an auditability problem.

  • RachitThakur146
    Rachit Thakur (@RachitThakur146) reported

    Github got down for 8 hours and they launched this...

  • MikaelRusi78212
    Minno (@MikaelRusi78212) reported

    What do you do when Github is down?

  • ywzander
    Ryan Zander (@ywzander) reported

    Instila launches August 24. Most founders don’t have an information problem. They have a “something important got buried in Slack, GitHub, Linear, or Jira” problem. Instila is an AI COO that watches the company context, catches what gets missed, and tells you what actually needs attention. We’re opening it up in 5 days. If you run a software company and want early access, reply “instila” or DM me.

  • HeyGurisaroy
    Guri Saroy (@HeyGurisaroy) reported

    » claude = code ($20/mo) » supabase = db + auth (free) » vercel = deploy (free) » stripe = payments (2.9% + 30c) » resend = emails (free) » posthog = analytics (free) » sentry = errors (free) » cloudflare = domain + dns (~$10/yr) » github = version control (free) real cost month one: $20 everything else is a nice-to-have you add once you have users.

  • VKoukoutis
    Vasilis Koukoutis (@VKoukoutis) reported

    GitHub being down is annoying. Discovering you can’t deploy because GitHub is down is much more interesting. Every external service eventually fails. The architecture question is which failures you’ve allowed to become production failures.

  • cbarmorecpa
    Charlie Barmore, CPA, CFE, CVA (@cbarmorecpa) reported

    I’ve gotten a lot of positive feedback since open-sourcing LedgerTB. Even better, I’ve started working directly with other accountants who are using the software and helping improve it. One of those accountants is @Scotchua. Scott ran into a bug when using the app, worked through the problem with Claude, figured out a fix, and Claude told him, “This would make a good pull request.” So he opened one on GitHub. We went back and forth through comments and reviews. I could have just made the change myself, but I wanted us to go through the full process, and I wanted him to get proper credit for the contribution. Since then, we’ve continued trading ideas, fixes, and tests. Scott is using his agent. I’m using mine. He even realized Claude could test the app on Windows through a Parallels installation he was about to delete. So now we’re bringing two accountants, two agents, two environments, and two different sets of assumptions to the work. He catches things I miss. I catch things he misses. We review each other’s changes and try to make sure fixing one thing doesn’t quietly break another. That back-and-forth has been one of my favorite parts of open-sourcing LedgerTB. Neither of us have an engineering background. AI is allowing us to participate much more directly in the development process, but that doesn’t make software engineering expertise any less important. Accountants know how the workflow should operate, what the output should mean, and where the accounting risks are. Engineers bring a different kind of judgment around architecture, security, reliability, and maintainability. The interesting part is that AI is making it easier for those perspectives to meet. It’s shortening the distance between “I wish the software did this” and “I’ve built a proposed change, tested it, and submitted it for review.” That doesn’t eliminate the need for engineering rigor, but it does give domain experts a much more active role in the process. I think that’s one of the biggest opportunities in open-source, AI-assisted software: the people who understand the problem can work more directly with the people and the tools that understand how to build reliable solutions. And it’s a lot more fun when we build them together!

  • thecircuitry_
    The Circuitry (@thecircuitry_) reported

    GitHub traced its 8-hour outage to an autoscaling failure that let a VS Code retry storm overwhelm load balancers after a monitoring blind spot hid the traffic spike.

  • Quan_Chain
    QuanChain (@Quan_Chain) reported

    An Agent Found The Exploit Path Nobody Wrote Wiz's own AI red-teaming agent independently discovered & chained a script injection exploit across GitHub Actions & into Snowflake's internal Jira environment. No human hand-authored the attack path. It was authorized research, responsibly disclosed, already patched. But the autonomy was entirely real: a broad objective, and the agent filled in every step itself. Nobody issued a command. The agent just found a door & opened it. The danger here isn't malice but the gap between "I authorized this session" and "it took this specific action." Wiz authorized a research objective. Nobody authorized that exact exploit chain. That gap between session-level permission & execution-level action is exactly where enforcement is missing in most stacks. Authorization at the front door doesn't cover everything that happens inside the house. QuanChain requires a valid, authorized signature at the point of execution for any on-chain action - an unsigned or improperly-scoped execution event simply does not propagate to the network. This isn't a login check. It's an execution-layer attestation, built on TADEQS adaptive security levels and never-on-chain public keys, that any agentic system on QuanChain inherits by default. The chain itself enforces scope every single time, at the moment it matters.

  • nuit_dhiver
    Alex (@nuit_dhiver) reported

    @NickADobos But doesn’t matter because GitHub is going down in few weeks again, probably.

  • Ramin_Ger
    Ramin (@Ramin_Ger) reported

    Is @github down again??

  • cj_pais
    cj (@cj_pais) reported

    @dingchilling i hope to have some bedside manner on public github even if i am angry, because i dont want to discourage other people from submitting issues

  • surajtwt_
    Suraj Jha (@surajtwt_) reported

    How GitHub looks at its users after ingesting 12 bajillion lines of hyperslop per second and still getting blamed for going down

  • Aadh1b
    Aadhib Nasser Veliyath (@Aadh1b) reported

    Wiz published research this week. Their autonomous agent found a script-injection flaw in Snowflake's public .NET connector repo five days after it merged, exploited it, and pulled a Jira token that could read internal projects. GitHub Advanced Security had scanned that same PR and cleared it. Everyone is arguing about whether Copilot wrote the code. GitHub denies it, Wiz hedges. That is the least useful part. A crafted issue title reached a shell. Your CI holds real credentials.

  • syssignals
    Vishwas Sharma | DevOps · Security · MLOps (@syssignals) reported

    @_Creation22 Github is so goated that even a day outage won’t be able to replace it.

  • audreyfeldroy
    Audrey M. Roy Greenfeld (@audreyfeldroy) reported

    Next I tried the new Deepseek Harness with Deepseek V4 Pro on High reasoning. It did a great job fixing a GitHub action that Muse couldn't, including permissions fixes and config that's normally tricky for Codex. It burned my budget fast but solved the problem very efficiently.

  • paul_pbng
    Paul (@paul_pbng) reported

    An AI hacked Snowflake via a GitHub issue title na. Wiz's Red Agent found the Actions bug and read internal Jira, 5 days after go-live. Everyone reads AI vs AI. Real thing: in-band signaling only. The title is data, the runner ran it as code. #AI #DistributedSystems

  • Delwo_A
    Delwo Athauda (@Delwo_A) reported

    @KafeKarShibolet @ashuuu_soft GitHub was down for a really long time. Meanwhile Origin was released by Cursor. Elon’s products have been growing at a really faster rate these days

  • dikshadutta
    Diksha (@dikshadutta) reported

    They're calling the AI-pilled marketer a "growth engineer." My recent guest says the role gets paid up to 60% more. I got @jon4growth on to show what it looks like. He shared his screen: a marketing GitHub, then a Notion knowledge base he queries live in Claude, so his whole team works from one shared brain. Full story of how @LouiseDSadeleer's post on marketers needing a GitHub sent me down this path is in my Substack. Worth a watch.

  • Laz4rz
    Lazarz (@Laz4rz) reported

    Codex has this peculiar recurring issue with my Github CLI credentials. It thinks they're expired, stops the goal and alerts me. I then copy-paste the log that they're in fact not expired, and it just continues and everything works?

  • Yash__Sensei
    Yash Agrawal (@Yash__Sensei) reported

    Pov a day at a 14-X-follower open-source startup: > checking github stars again and again > @imheadrick and i spend 3 hours arguing about what to call the category we're building. > i open GITHUB to do GROWTH . somehow i'm debugging a windows issue. > someone with 200k followers likes our post. screenshot immediately sent to the group. github stars still same count. @dshekhar17 tagging you too, so you dont feel left out.

  • withashutos
    Ashutosh Bhandari (@withashutos) reported

    Every hiring post today ends the same way. "DM me your github." Then nobody opens it. Not because they don't care. A stranger's repo list tells you almost nothing about what they built versus cloned, what got reviewed, what they threw away. The signal was never the profile. It's per project, and nobody writes it down.

  • gideonxqt
    Gideon (@gideonxqt) reported

    no way Cursor just launched its own GitHub and the timing is not a coincidence Cursor Origin went into early beta on August 17, the same day GitHub had a 4-hour outage. built specifically for a world where AI agents commit way more than humans do – AI-agent PRs went from 4M/month to 17M/month in six months. what's different: automated merge-conflict resolution built for parallel agent workloads two-way GitHub sync – PR comments, commits, and file diffs sync both directions in real time NVMe-backed file servers, S3 as source of truth claims 22.6 commits/sec, sub-400ms global sync (not yet independently verified) CLI to clone existing repos or push straight to Origin catch: available on Pro/Teams/Enterprise only, not free plans. and if you're syncing an existing GitHub repo, GitHub stays the actual source of truth – Origin isn't a full replacement yet. worth watching given Cursor is now a fully owned SpaceX subsidiary as of Aug 14.

  • not_jarod
    Jarod (@not_jarod) reported

    @elijahmuraoka_ @github ok It does solves the problem of storing your "repo" but there are many things useful on github, like workflows, pr's commits, etc...

  • hakan_ertann
    Hakan Ertan (@hakan_ertann) reported

    Designers, don’t be scared of vibe coding! Github, error, backend, commit, push etc. are not blockers for you. You can build any app or tool way better than anyone else . You got the taste and all the skills, just ******* sit down and ask AI: “I want to build this. Tell me how”

  • ty_auldric
    Tyrone Robb (@ty_auldric) reported

    I’ve used @t3dotcodes on 111 of 123 days, across Intel Mac and Windows. Few issues. I forked it and made improvements, but it moves so fast that nightly makes sense till it's more stable. Rough edges: GitHub projects, Preview getting stuck and mobile sync docs. Subscribed to @theo as thanks.

  • mktpavlenko
    Mykyta Pavlenko (@mktpavlenko) reported

    your .env file is on GitHub right now your API keys are in your frontend code the agent wrote them inline and you shipped without checking first thing to fix. today.