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GitHub Outage Map

The map below depicts the most recent cities worldwide where GitHub users have reported problems and outages. If you are having an issue with GitHub, make sure to submit a report below

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The heatmap above shows where the most recent user-submitted and social media reports are geographically clustered. The density of these reports is depicted by the color scale as shown below.

GitHub users affected:

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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.

Most Affected Locations

Outage reports and issues in the past 15 days originated from:

Location Reports
Ahmedabad, GJ 1
Delme, ACAL 1
Lyaud, Auvergne-Rhône-Alpes 1
Catania, Sicily 1
Inverness, Scotland 1
Quito, Pichincha 2
Junín, Manabí 1
Guadalajara, JAL 1
Paris, Île-de-France 6
São Paulo, SP 1
Ipauçu, SP 1
Vigo, Galicia 1
Tel Aviv, Tel Aviv 1
Éragny, Île-de-France 1
Saltillo, COA 2
Montlhéry, Île-de-France 1
Aulnay-sous-Bois, Île-de-France 1
Granada, Andalusia 1
Vernon, Normandy 1
Township of Evan, KS 1
Madrid, Madrid 1
Bogotá, Bogota D.C. 1
Lyon, Auvergne-Rhône-Alpes 1
Lima, Lima 1
Aix-en-Provence, Provence-Alpes-Côte d'Azur 1
Trento, Trentino-Alto Adige 1
Le Chambon-Feugerolles, Auvergne-Rhône-Alpes 1
Antananarivo, Analamanga 1
Lure, Bourgogne-Franche-Comté 1
Ashkelon, Southern District 1
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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:

  • aiwithaj_
    AJ - 14 y/o developer (@aiwithaj_) reported

    @Da7_Tech @devindesktop Don't know if there's one left - but I'd use it to continue making contributions to open source software and fixing bugs/issues that were raised on Github as well as making my own open source software

  • trulite007
    trulite (@trulite007) reported

    @Qromerolauro @mkliku @radius_browser Like a simple example would be have a list of my urgent GitHub issues and start an agent for it . Or a dashboard in which buttons start investigating issues. Of course I just need the webpage to be able to access radius tools. I m thinking secure way is an extension

  • wiiiimm
    wiiiimm (@wiiiimm) reported

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

  • convequity
    Convequity (@convequity) reported

    Snyk is a clean postmortem for what happens when a security tool lives inside the coding agent’s loop. The product was mostly scan-and-warn. Find the issue, comment on the PR, suggest a fix. Blocking the merge usually sat in GitHub, not in Snyk. Bigger platforms smothered it. $PANW, $CRWD, and Wiz pulled AppSec into the bundle the CISO was already buying. GitHub was the main developer surface and put scanning where the code already lived. Then coding agents arrived and delivered the final blow. A lot of that scanning became something the agent could just do. Growth held up for a short while after the COVID/cloud tailwind. Then it decelerated hard. This is the same lens we use in Convequity’s SaaS Agentic Survival Evaluation Framework. The PANW, CRWD, and FTNT reviews go up on Convequity in a few days.

  • Nayak__Ai
    NAYAK (@Nayak__Ai) reported

    6. The Dependency Incident Check Grok has native real-time search across X. Breakage gets posted there hours before the GitHub issue is triaged. No other coding model has that feed. "You are a build engineer whose first move on a broken pipeline is to work out whether it broke for everyone or only for me. Search X and the web, last 14 days. Check: - Is anyone else reporting this failure with this package and version, and when did the reports start - The exact release that changed behaviour, and the changelog line that admits it - Whether maintainers have acknowledged it and what they recommended - The pin or patch people settled on, with the tradeoff of each - Whether this is my problem instead, and what evidence points that way Give me the verdict in the first line: their bug or mine. Then the evidence, newest first, with links. My failure: [PASTE THE ERROR, THE PACKAGE AND VERSION, AND WHAT CHANGED ON YOUR SIDE RECENTLY]"

  • eddiejaoude
    Eddie Jaoude | DevRel | Open Source (@eddiejaoude) reported

    I have many tokens to burn before tomorrow after the Claude reset. Send me your GitHub issues with context 👇

  • StragglerLiu
    Straggler Liu | AI & Semis (@StragglerLiu) reported

    NVIDIA($NVDA ) Is Paying $14B for a Company With $150M Revenue. That's Not Financial Logic — It's Ecosystem Control. NVIDIA is in advanced talks to acquire Hugging Face for ~$14 billion ($12.9B acquisition + $1B retention), per Bloomberg. To put that in perspective: Hugging Face does ~$150M in annual revenue. That's ~86x revenue. Microsoft paid ~1.6x revenue for GitHub. Google paid ~3.5x revenue for DeepMind. NVIDIA is paying 20-50x more on a revenue multiple basis. The premium is not for revenue. It's for control of the AI developer ecosystem. What is NVIDIA buying? Hugging Face hosts 500,000+ models, 250,000+ datasets, and serves millions of developers. It is the single most important distribution channel for open-source AI. If you build AI, you use Hugging Face. That makes it the front door to AI development. Why NVIDIA is paying this premium: 1. The "NVIDIA triple lock." NVIDIA's hardware lead (GPU) is real. Its software lead (CUDA) is a moat. But the third lock — the developer workflow — was missing. Hugging Face is that workflow. Developers discover models on Hugging Face, deploy them, and optimize them. Whoever controls that discovery layer controls which hardware gets used. 2. The GitHub analogy, inverted. When Microsoft bought GitHub, developers were already using GitHub. Microsoft didn't need to capture them — it needed to prevent Amazon/Google from doing so. NVIDIA faces the opposite problem: developers are already using NVIDIA hardware. But they're discovering and deploying models through a neutral platform. NVIDIA is eliminating that neutrality. 3. The long game: inference, not training. NVIDIA dominates training. But inference is the bigger TAM — and it's more fragmented. If NVIDIA controls the model discovery and deployment layer, it can steer inference workloads to its own stack. That's a 10-year strategy disguised as a 14-billion-dollar acquisition. Who wins, who loses: NVIDIA (NVDA): Acquires the developer distribution layer. The most important strategic move since CUDA. Shifts the valuation case from "chip cycle" to "platform economics." Competitors (AMD, INTC): Lose neutral access to the primary AI model distribution channel. This is a structural headwind that no amount of hardware catch-up can fix. Cloud providers (MSFT, AMZN, GOOGL): Hugging Face was a neutral hub. If NVIDIA controls it, cloud providers risk being disintermediated from AI workload decisions. The open-source community: The platform that was built on openness is now owned by the dominant hardware vendor. Neutrality is the first casualty. The capital question: Can NVIDIA integrate Hugging Face without destroying its community value? If yes, the $14B is cheap. If no, it's a very expensive mistake. The answer will define whether NVIDIA becomes the AWS of AI — or just another hardware company with an expensive acquisition. Note: Acquisition details based on Bloomberg reporting; not confirmed by NVIDIA or Hugging Face. Revenue multiple comparisons based on publicly reported figures.

  • waefrebeorn
    WuBu ⪋ WaefreBeorn 🇺🇸 👑 (@waefrebeorn) reported

    hey @Teknium @yeahfortommy please add the amd portal too even if tou have to send tommy into the AMD headquarters to get them to fix the links (you have to sign up for american then link through github, then you can access the models free, tommy needs to pull teeth but they have free api)

  • AzakaSekai_
    安坂星海 Azaka || VTuber (@AzakaSekai_) reported

    I know you explicitly said "excluding vibecoding," but the biggest problem *IS* AI right now. Several major players in the field have moved on to heavy AI development or even agentic post-exfiltration moves and has muddied the water even more for attribution. Aside from that, the other big trend that we've been seeing more and more in recent years is heavily abusing Living Off Trusted Sites with C2 comms based on GitHub, OneDrive, Outlook, etc. Whilst this is most definitely not "new," we have seen a non-insignificant number of threat groups move to platforms that make tracing a little more difficult. In terms of the malware themselves, most of them have also shifted to using compiler-level obfuscation - a lot more compared to previous years where control flow flattening and jumps all over the place have become increasingly common. Right now, it's still tolerable, but my job has started becoming more and more annoying and less fun especially if every malware now looks the same. #mond_AzakaSekai_

  • BeardedPrinter
    Bearded Printer (@BeardedPrinter) reported

    @RedPill_Phil You've gotta go to their github and submit an issue. Make sure to search their issues to ensure you don't submit a duplicate bug

  • johncrickett
    John Crickett (@johncrickett) reported

    @Mike_Preston17 I don't think they water them down, why would they when they're competing on having AGI? I don't mind using GitHub actions to run tests and builds against a branch before merge. I don't want it triggering production schedules. Do you list all the things it shouldn't do in the prompt?

  • mrgadgetstudio
    mrgadget (@mrgadgetstudio) reported

    @EzekielCrrypt I still deploy code to github, what's problem?

  • foilmanhacks
    Jason Sawyer (@foilmanhacks) reported

    There's a huge problem in InfoSec education: it’s way too course and tool focused. Instead of teaching the underlying methodologies and how to discover or invent, we feed people the latest "OSINT" slop script that’s been shat onto GitHub. OSINT isn’t about using scripts or services. It’s about understanding how they work, and being able to create your own.

  • moledao_io
    moledao (@moledao_io) reported

    Web3 Remote Job Scams: A 2026 Field Guide Introduction Over the past few years, Web3 has come to represent a new world of opportunity for many young people. New roles, new narratives, and new stories of wealth have inspired countless people to enter the industry with high expectations. Remote work, stablecoin-based compensation, and a greater emphasis on ability than academic credentials can be especially attractive to professionals at the beginning of their careers. As a recruitment platform that works with job openings and candidates every day, however, we have also seen the other side of the industry. A significant share of supposed recruitment activity is not recruitment at all. It is fraud disguised as hiring, designed to steal the funds in job seekers’ wallets. According to Chainalysis’ 2026 report, cryptocurrency scams and fraud caused an estimated $17 billion in losses worldwide in 2025. Impersonation-related attacks increased by 1,400% year over year. Fake recruitment is one of the most common ways impersonation and social engineering are being applied to job seekers. What Happened to Us This month, it happened to us. We were contacted through Telegram by someone claiming to represent a US-registered technology company. They said the company urgently needed to hire Web3 engineers and wanted our support in sourcing candidates. After further investigation, we were unable to verify whether this person had actually been authorized by the company. We also could not rule out the possibility that they were impersonating a legitimate business. To avoid causing further harm to an organization that may itself have been a victim of impersonation, we will not disclose the company’s full name. At first, there were almost no obvious warning signs. The contact provided a business registration document and a polished company profile. Interviews were scheduled through Calendly, job openings were hosted on Ashby, and meetings took place over Zoom. These are all professional tools commonly used by legitimate companies, making it easy to assume that a company using them must be trustworthy. In reality, forging a registration document and creating Calendly or Ashby accounts require very little effort. Almost anyone can create the appearance of professionalism at minimal cost. This experience taught us an important lesson: the legitimacy of the tools surrounding a hiring process tells you very little about the legitimacy of the company behind it. The details of how the people involved behave are far more revealing. The partnership also progressed with unusual ease. All contractual documents arrived at once and appeared ready to sign. There was no friction at any stage. When discussing the recruitment fee, we initially proposed 15%, which the other party immediately accepted. We then tested an increase to 20%, and they accepted again without hesitation. Anyone with experience in recruitment delivery knows that fees are often one of the most difficult parts of a headhunting agreement. Clients may negotiate repeatedly over a difference of just two percentage points. The pace was also deliberately compressed. Interviews were often scheduled only one or two hours in advance, leaving almost no time for verification. Once confirmed, meetings were then repeatedly cancelled or rescheduled due to supposed last-minute conflicts. Several additional warning signs gradually appeared. The registration documents looked legitimate at first glance. Upon closer comparison, however, the names of the people listed in them did not match the information we were able to verify independently. The contact also made an unusual request. While verifying whether candidates were currently employed, they asked us to find out whether those candidates used LinkedIn frequently. Normal employment verification does not require this information. A person’s activity on a professional networking platform primarily reveals whether they have an accessible network that could quickly be used to verify their identity, employment history, or recent activity. At the same time, the contact prohibited us from sourcing candidates through LinkedIn or Telegram. They claimed their internal team was already using those channels and wanted to avoid duplicate candidates. In practice, this restriction pushed external recruitment partners into channels where independent cross-checking was much more difficult. The geographic requirement was even harder to explain. A US company was willing to consider only Chinese-speaking candidates and applied unusually strict screening standards that appeared unrelated to technical ability. In retrospect, we suspect that the screening criteria may have favored candidates who were easier to persuade and more likely to have higher incomes or larger asset balances. We cannot, however, confirm the group’s true intentions. Each of these warning signs could have been rationalized on its own. A client may have unusual preferences, legitimate concerns, or simply an unprofessional hiring process. It was only when the signals were considered together that the larger pattern became visible. Then came the interviews. Candidates joined the meetings, but the interviewers asked no questions about their project experience or technical background. Instead, they immediately provided a GitHub repository and instructed candidates to clone it onto their local machines and run it. The repository involved encryption and signing operations using cryptocurrency wallet private keys. Before the interviews, we had explicitly asked whether candidates would need to download or run anything. The contact told us they would not. Once the meetings began, however, the candidates received the exact opposite instruction. One candidate offered to share his screen, inspect the code locally, and walk the interviewer through it line by line. The interviewer refused and insisted that he download and run the repository on his own computer. The candidate ended the meeting. Other candidates quickly noticed that something was wrong and stopped as well. The most carefully designed part of the operation was not what happened during the interviews, but the feedback that followed. If a candidate ran the code, the interviewer gave positive feedback, said the candidate had performed well, and advanced them to the next round. If a candidate remained cautious and refused to run it, the interviewer told us that the candidate had falsified their résumé and instructed us to blacklist them immediately. That second response was not merely feedback. It was an instruction designed to prevent further communication between us and the candidate while allowing the wider operation to continue. This is something we hope every recruitment professional remembers: when a client asks you to blacklist a candidate without providing credible evidence, the request may reveal more about the client than it does about the candidate. Another common feature of these operations is that they do not need to interview every candidate. They only need a small number of people who are willing to execute the code. As a result, the hiring process will often stall abruptly once enough potential targets have been identified. What We Did Afterwards We immediately terminated all cooperation with the contact and removed the related job listings. We contacted every candidate who had entered the process to determine whether anyone had downloaded or executed the code. We also provided guidance on device inspection, credential rotation, and wallet security. All contracts, chat histories, meeting information, repository URLs, and account details have been preserved. Reports have been submitted to Telegram, GitHub, Ashby, and Calendly. At the procedural level, we have rewritten our client identity-verification process. Going forward, we will not accept recruitment assignments or partnerships without conducting independent callback verification through a channel the contact does not control. Candidate security briefings will also become a standard step before we introduce anyone to a client. Other Recruitment Scams Currently in Circulation What we encountered was only one variation. Several other methods remain active and deserve close attention. Malicious Take-Home Assignments Malicious interview assignments are currently one of the most widespread forms of recruitment-related attacks. Attackers impersonate recruiters or hiring managers on LinkedIn, X, or Telegram. They advertise senior roles with compensation well above market rates and frequently target professionals working with React, Next.js, Solidity, and blockchain technologies. Candidates are then given a technical assessment in the form of an npm project or GitHub repository and instructed to run it locally. Unit 42, the threat-intelligence team at Palo Alto Networks, refers to this activity as “Contagious Interview” and tracks it under the identifier CL-STA-240. The campaign was first publicly documented in November 2023 and has been linked to North Korea–associated threat actors. The malware used in these campaigns includes BeaverTail and InvisibleFerret. These cross-platform payloads target Windows, Linux, and macOS devices and are designed to steal sensitive browser information and cryptocurrency wallet data. According to security researchers, more than 197 malicious npm packages associated with this attack path have been distributed since October 10, 2025, accumulating more than 31,000 downloads. Common warning signs include recently created repositories, abnormal commit histories, and contributors whose identities cannot be verified. These are only indicators, however. Attackers can compromise established accounts, fork legitimate long-running repositories, or manufacture months of commit history in advance. No single signal can prove that a repository is either safe or malicious. Fake Meeting Software Fake meeting applications are another major threat. Attackers approach targets with an investment opportunity, partnership proposal, or interview invitation. Shortly before the meeting, they claim that Zoom is not working or that the company uses a different conferencing platform. The target is then directed to download the supposed meeting software from a specific website. Cado Security Labs has tracked one such campaign, known as “Meeten,” since September 2024. The campaign distributes a cross-platform information stealer called Realst. The group uses AI-generated company profiles to make its operations appear more credible. The names and branding of its meeting applications change frequently, with known examples including Clusee, Cuesee, Meetone, and Meetio. The malware targets cryptocurrency wallets and Telegram credentials, as well as iCloud Keychain data, banking information, and browser cookies. The solution is not to memorize an approved list of meeting applications, since legitimate companies may use many different tools. The safer rule is never to download meeting software from an unfamiliar domain sent directly by an interviewer. Download the software independently from its official website or an official application store, and verify the domain carefully. Malicious Offer Files Fake offer documents are another common attack method. In March 2022, attackers stole approximately $540 million from Axie Infinity’s Ronin Bridge, although later reporting placed the total value closer to $625 million. Subsequent investigations found that the initial point of entry was a fraudulent job offer delivered as a PDF. A senior engineer at Sky Mavis was contacted on LinkedIn by accounts impersonating another company. After completing several rounds of interviews, the engineer received an extremely attractive offer in PDF format and downloaded it. That file introduced spyware into the system. The attackers eventually gained control of five of the network’s nine validator nodes. Sky Mavis confirmed that an employee had been targeted through social engineering. In April of that year, the US Treasury attributed the attack to the Lazarus Group. What makes this case especially significant is that the victim was a senior engineer at the company that was ultimately compromised, and the attack was supported by a complete, multi-stage interview process. The final payload was simply a file. Terminal Paste Attacks Attacks that instruct victims to paste commands into a terminal or system run box have grown rapidly over the past two years. They are commonly known as ClickFix attacks. During an interview or onboarding process, a page may claim that the user’s browser has encountered an error, that their identity must be verified, or that a system component needs to be repaired. The page then provides a command and instructs the user to paste it into a terminal or run dialog. In May 2026, Microsoft disclosed a campaign targeting macOS users through lures disguised as system utilities. The campaign was used to distribute information-stealing malware. Other security companies have identified similar samples containing asset-transfer functionality. The malware first checks whether a wallet contains funds and then transfers those assets to an address controlled by the attacker. The rule here is simple: no legitimate recruitment process requires you to paste a command you do not understand into your terminal. Not once. Deepfake Interviewers Deepfake interviewers have already begun to appear. Real-time face-swapping technology is now advanced enough to support an apparently coherent interview. The person on screen may appear to be a senior executive from a well-known company, speak professionally, and have a verifiable public résumé. There are two practical ways to respond. First, ask the person to perform an unexpected physical action, such as briefly covering half of their face with their hand or turning their head 90 degrees to the side. Current real-time face-swapping systems may still reveal visual inconsistencies when the face is obstructed or shown from an extreme angle. Second, conduct an independent callback using contact information published on the company’s official website. This remains the most effective method of verification. Malicious Wallet Signatures A wallet-signature attack does not require your seed phrase. The interviewer may ask you to test a product, review a dApp, claim an onboarding airdrop, or complete an onchain identity-verification step. You are then instructed to connect your wallet and sign a transaction or message. Certain signatures or malicious transactions can give an attacker permission to transfer your assets. The level of risk depends on whether you are signing a basic message, a Permit, a token approval, or an onchain transaction. If you do not understand exactly what a signature authorizes, do not approve it. The boundary should be clear: no interview or onboarding process requires you to connect a personal wallet. A recruiter or employer has no legitimate reason to require a job candidate to perform an onchain transaction. Upfront Fees and Identity Misuse Upfront fees and identity misuse are among the oldest recruitment scams, yet they are still frequently overlooked. The first typically involves demands for a security deposit, training fee, or equipment payment before employment begins. The second asks a candidate to use their identity to register an account with a cryptocurrency exchange or open a bank account. This can carry consequences far more serious than financial loss. If the account is later used to process criminal proceeds, the person whose identity was used may face criminal liability. Any request for payment before employment is a red line. If someone asks you to register an account, receive funds, or move money on their behalf using your own identity, end the conversation immediately. How to Protect Yourself Before an interview, take three low-cost precautions. First, verify that the company genuinely exists. Review its official website and registration information, then examine whether the online histories of its team members are consistent across different platforms. Check whether the names listed in corporate documents match publicly available information. Second, independently contact the company through a channel the recruiter cannot control. Use an email address or phone number published on the official website. Do not use contact details provided by the person approaching you. Third, pay attention to two recurring warning signs: interviews scheduled only one or two hours in advance and then repeatedly changed, and compensation that is clearly above the market rate for the role. Both patterns appear in a large number of reported cases. During an interview, pause whenever you are asked to download, install, or run anything. You may offer to explain your approach over screen sharing, but remember that screen sharing itself does not provide protection. If code is running on your own machine, you can still be compromised even if you show the interviewer every line beforehand. The interviewer’s response is often more revealing than the request itself. If they refuse to explain what the code does, refuse to provide an isolated environment, or insist that you run it on a device containing your wallets and work credentials, end the interview immediately. When sharing your screen, share only the specific application window required—not your entire desktop. If the first interview contains no questions about your experience, projects, or technical background and moves directly to running code, you have every reason to end the call. We do not recommend that job seekers attempt to run untrusted code themselves. If analysis is genuinely necessary, it should be handled by someone with appropriate security expertise inside a disposable, isolated virtual machine that contains no credentials, does not mount directories from the host system, and has restricted network access. A container is not a purpose-built malware sandbox. Misconfigured directory mounts, permissions, or network access can still expose the host environment. Ordinary job seekers should not attempt this on their own. If you are a recruiter or regularly recommend opportunities to other people, incorporate these warnings into your standard process. Before introducing a candidate to a client, clearly tell them not to download unfamiliar software or browser extensions, not to run unknown code or scripts, and to share only the necessary application window during screen sharing. If a client asks you to blacklist a candidate without credible evidence, contact the candidate directly and verify what happened before taking action. Conclusion The crypto industry has spent years removing trust from transactions. You do not need to trust the counterparty because there is a contract. You do not need to give anyone your private key because it remains in your possession. At the protocol level, the industry has solved this problem remarkably well. Recruitment places people back in a much more primitive position. A stranger claims to be someone, and you must decide whether to believe them. Business registration documents and meeting links can be forged. Even an interviewer’s face can now be replaced in real time. Not a single dollar of the more than $500 million stolen in the Ronin attack was taken through a flaw in cryptography. What failed was the human layer. Every method described in this article relies on the same force: speed. The opportunity may disappear. Other people are competing for it. You have to act now. In an industry where everyone is urging you to move faster, giving yourself permission to slow down may be your most effective line of defence. If you have encountered a similar approach or recruitment process, please let us know. We hope this article helps more people recognize the warning signs before it is too late.

  • jordle91
    Jordan (@jordle91) reported

    The surprise: an explosion in GitHub issues. Not from bugs. The whole company realised that filing an issue meant it got built in hours.

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