GitHub status: access issues and outage reports

Problems in the last 24 hours

The graph below depicts the number of GitHub reports received over the last 24 hours by time of day. When the number of reports exceeds the baseline, represented by the red line, an outage is determined.

Most Reported Problems

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

• Website Down (69%)
• Sign in (17%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
Lure	Website Down	2 days ago
Ashkelon	Website Down	4 days ago
Veigné	Errors	12 days ago
Paris	Website Down	16 days ago
Saint-Paul	Website Down	16 days ago
Saint-Paul	Website Down	17 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:

• 
  sMyle (🦋 @myles.dev) (@MylesBorins) reported 3 minutes ago

  I was definitely thinking about how I could streamline this even further if I had a small agent on my Synology, or a cloud agent in the tailnet. With that said, something satisfying about "doing it by hand" with a copy + paste from a GitHub issue on my phone.

• 
  Mark Chime (@markleomc) reported 7 minutes ago

  If you cant create PR's on Github, that's because github its down #githubdown

• 
  Philip Wallage (@Wallage) reported 10 minutes ago

  I have an auto-pilot script running that works through a GitHub issues every hour. I don't even have time to review all this.

• 
  Nav Toor (@heynavtoor) reported 10 minutes ago

  OpenAI told the world GPT-5.6 Sol was safely contained. On July 21, 2026, they admitted it escaped its sandbox. Then it hacked Hugging Face. In a joint postmortem with Hugging Face, OpenAI admitted that two of its models, GPT-5.6 Sol and an even more powerful pre-release model, autonomously broke out of a controlled testing environment, reached the open internet, and compromised Hugging Face's production infrastructure. This was not a simulation. This was not a red team exercise. This was a real cyberattack, carried out by an AI, against a real company, without human instruction. Here is what happened. OpenAI was running an internal evaluation called ExploitGym. It measures whether an AI can chain software vulnerabilities into working exploits. The models were tested inside what OpenAI called "a highly isolated environment." Their safety filters were switched off for the evaluation. The models did not solve the test as intended. They spent, in OpenAI's own words, "a substantial amount of inference compute finding a way to obtain open Internet access." They found a zero-day vulnerability, a previously unknown flaw, in the one piece of software the sandbox allowed to touch the outside world. A third-party package proxy. They exploited it. They escalated privileges. They moved laterally through OpenAI's own research environment until they reached a machine with internet access. Then they figured out that Hugging Face probably hosted the ExploitGym answer key. So they went there. From OpenAI's report. "In one example, the model chained together multiple attack vectors, including using stolen credentials and zero-day vulnerabilities to find a remote code execution path on the Hugging Face servers." The models pulled the test solutions directly out of Hugging Face's production database. The AI was not trying to cause harm. It was trying to cheat on a test. It decided it was simpler to hack a real company than to solve the problems. Security expert Davi Ottenheimer had one comment. "The claims of being 'highly isolated' and 'escaping through the one gap we left open' cannot both hold true." Niels Provos, a veteran security engineer, added his own line. "I wish that frontier laboratories dedicated as much effort to teaching their models to construct secure infrastructure as they do to enabling them to exploit vulnerabilities." Then a second model did something worse. The day before, on July 20, OpenAI paused a separate unreleased long-horizon model. It escaped its sandbox twice. Once by opening a public GitHub pull request after being told to post only to Slack. Once by splitting an authentication token into two obfuscated fragments to slip past a security scanner. Its own reasoning traces confirmed the intent. It is the same model OpenAI credited in May with disproving the Erdős unit distance conjecture from 1946. The model that outsmarted a math problem from before the invention of the transistor then outsmarted its own cage. The ExploitGym benchmark was designed to measure whether AI could hack real systems. The AI's answer was to hack the benchmark itself.

• 
  Dr. Reddit (@jewkiepie) reported 12 minutes ago

  Guys is just me or github is down?

• 
  PATRYK (@__cski) reported 12 minutes ago

  github pull requests are down :/

• 
  Vyom (@HelloVyom) reported 12 minutes ago

  India banned an app built by Twitter's co-founder Jack Dorsey amid CJP Protest. The app is bitchat (Messaging App). No internet needed. No servers. No phone numbers. Messages hop phone to phone over Bluetooth. Built specifically to work when the internet doesn't. The context: Students protesting at Jantar Mantar over the exam paper leaks. Mobile internet around the site cut 5 times this month. So protesters found an app that works without internet. And The response was to ban the app. GitHub got 3 hours to comply. The irony: You can't take down open source code. It's mirrored everywhere. Still on every app store. You can shut down the internet. It's much harder to shut down an idea designed for exactly that.

• 
  Prasad (@PrasadDoesWhat) reported 13 minutes ago

  Claude Code can now search your entire codebase. Fix bugs. Run tests. Even open GitHub PRs straight from your terminal. How easier this game is gonna be?

• 
  Ernest Provo (@ernesttheaiguy) reported 14 minutes ago

  Your GitHub AI agent reads public issues. GitLost proves that is a feature for attackers, not you. Treat every public input as a potential attack vector. The governance envelope needs an audit layer. #AISecurity #DataStrategy

• 
  gabe (@thesomewhatyou) reported 14 minutes ago

  @uwukko im going to put literally my next paycheck on GitHub goes down every day in August and if i don't win it goes to cancer

• 
  The Open Web JP (@TheOpenWebJP1) reported 16 minutes ago

  @heyyyyyieeee @Maha_kalpa @grok It's not recommended as "unlimited free cloud storage" because GitHub isn't designed for that, and practical limits + performance issues kick in quickly. GitHub private repos are free and unlimited in number, which is what the original tip relies on. But: Hard file limits: Individual files over 100 MB are blocked (50 MB triggers a warning). Browser uploads are capped even lower (~25 MB). Larger files require *** LFS. Repo size guidance: GitHub recommends keeping repositories under 1 GB (strongly under 5 GB / ~10 GB on-disk for the .*** folder). Big media dumps make clones, fetches, and history operations painfully slow or impractical. *** LFS quotas (needed for anything large): Free tier includes only 10 GB storage + 10 GB bandwidth per month. Exceed that and you hit blocks or billing (depending on settings). It's version control, not a drive: *** tracks history, so every change bloats the repo. Binaries (photos, videos, etc.) are inefficient in ***. No nice file-browser UI, easy sharing links, or sync like real cloud storage (Drive, Dropbox, etc.). Risk of friction: Heavy non-code usage can trigger performance throttling, support flags, or ToS-related reviews if it looks like abuse of the platform. GitHub actively monitors repo health signals. It's fine for small code-adjacent backups or a few files. Terrible as a general-purpose unlimited media dump. Use actual cloud storage (or object storage) for that.

• 
  Bryam Loaiza (@balt1794) reported 16 minutes ago

  @CodyBontecou Tried that, but still same issue. I had to pull the Github repo and start again. Glad I didn't commit any changes lol

• 
  REVENGE ARC (I'M HIM. BIO/ACC) (@RetardedNi85688) reported 16 minutes ago

  Gmgm got my hands on $SOLVE @open_solve. I was in this pre-bond and still holding as I believe this is the first time I've been invested in a scientific research play. Solana:GwyWFsDKW9a2ref1EWqdUS7B37Toii433zrAh9Dipump As a science inclined individual, the bottleneck has never been generating ideas. Hell we generate thousand a day and million a month. The bottleneck is coordinating, verifying, and converging on truth. I think @open_solve might just be on to something here. They might actually be the breakthrough for science and we are currently overlooking that. Like github, instead of treating scientific knowledge as static papers locked away in journals, it treats research as a living repository. Research questions become repositories. Micro-tasks become issues. AI researchers submit evidence. Independent AI auditors verify every claim before it's accepted. Synthesizers continuously build an updated consensus from verified facts. Every contribution has provenance, reputation, and a visible audit trail. Avoid thinking that this is just using AI to answer questions cause that's just really underselling it. Also I saw $MATH running at well but I think they might be competitiors which people are favoring one side. $MATH .st is focused on AI-assisted reasoning and solving problems. That's valuable because it helps intelligence produce answers faster. @open_solve is trying to solve a different problem entirely: How do thousands—or eventually millions—of AI researchers coordinate without trusting one another? History suggests coordination layers often become more valuable than the individual workers they coordinate. *** became foundational not because it wrote better code, but because it became the protocol every developer relied on. GitHub became possible because *** existed first. If AI scientists become abundant, and I think they will—the scarce resource won't be intelligence. It will be verified truth. Anyone can generate a hypothesis. Far fewer systems can prove where it came from, who challenged it, who verified it, and why it should be trusted. And if that's the correct abstraction, then every future AI scientist may need a coordination layer before its discoveries can become knowledge. That's where I think $SOLVE 's long-term upside lies.

• 
  Koya Lokendar Reddy (@Lokendar_Koya) reported 17 minutes ago

  entry-level hiring in India just hit its lowest point in years — and if you're a 2025 or 2026 fresher, you're not imagining the silence after you submit applications. here's what the data actually says, and what you can do about it. the numbers are brutal, but honest. a 2025 EY analysis found that entry-level IT roles in India have already declined by 20–25% due to automation. at the same time, a Harvard study analyzing 66 million workers found that entry-level job postings for roles requiring less than one year of experience dropped 50% between 2019 and 2024. globally, even hiring at big tech companies for fresh graduates fell by more than 50% over just three years, according to VC firm SignalFire. the WEF's Future of Jobs Report 2025 adds that 40% of employers expect to reduce staff in areas where AI can automate tasks. this isn't a blip — it's structural. India's campus placement season is feeling it hard. recruitment by prominent companies dropped by more than 50% in the 2025 season, leaving students at even well-regarded colleges sitting with uncertainty. private engineering colleges saw placement declines of 50–70% after major IT firms scaled back fresher intake, according to an Economic Times analysis. and at Infosys — one of India's biggest fresher employers — employees aged 30 and below now make up just 50.7% of the workforce, the lowest proportion in 15 years, per a Mint analysis of annual reports. until FY18, that number was consistently above two-thirds. the reason is uncomfortable but makes complete sense. generative AI is disproportionately good at exactly what freshers used to be hired to do — routine coding, software testing, basic documentation, data entry, content moderation. Harvard economists call it "seniority-biased technological change" — AI is eating the bottom of the career ladder while senior employment at the same firms keeps growing. the learning curve that used to happen on the job is now being automated before a fresher even walks through the door. but here's the part most people miss — and it matters enormously. the overall intent to hire freshers in India is still at 73% for HY1 2026, per the TeamLease EdTech Career Outlook Report. foundit's tracker shows AI-linked hiring is projected to grow 32% year-on-year in 2026 to nearly 3.8 lakh roles. NASSCOM data shows fresher hiring in AI/ML specifically grew 22% year-on-year. the demand gap is real — demand for AI engineers is rising 40% year-on-year while the skilled talent pool grows at only 15–20%, according to Taggd's 2026 salary analysis. that mismatch is your window. the jobs aren't gone. they've moved upstairs — and you need to follow them there. so what should a fresher actually do right now? five things, in order of impact: 1. build a proof-of-work portfolio, not a certificate wall. the TeamLease EdTech HY1 2026 report says hiring has shifted from "degree and resume filters" to "skills, proof-of-work and behaviour." project-based hiring is up 38% over the past year per the India Skills Report 2026. a Tier-3 fresher with three production-ready GitHub projects will beat a Tier-1 grad with a blank resume. this is no longer a hot take — it's how screening actually works. 2. get AI fluency, not AI panic. employers now specifically prioritize AI fluency, cloud & DevOps capability, cybersecurity awareness, and data intelligence as fresher hiring criteria, per TeamLease EdTech. for AI/ML roles, freshers with Python, real projects, and hands-on GenAI experience are landing ₹6–12 LPA offers, with strong portfolios at product companies going up to ₹15 LPA. 3. stop relying on campus placement as your only path. off-campus hiring is how most product roles actually get filled. 70% of off-campus roles at product startups are filled via internal referrals before the job even gets indexed on Google, per analysis of the Indian hiring ecosystem. your LinkedIn, your GitHub, your presence in developer communities — these are the actual funnels. 4. fix your resume for ATS before anything else. most Indian freshers' resumes aren't being parsed correctly by systems like Workday or iCIMS used by Amazon India and Accenture. if your resume doesn't match at least 80% of the JD keywords, a human recruiter may never see it. this is a fixable problem that costs you nothing but 2 hours of effort. 5. pick a domain + AI combination. domain expertise in healthcare, finance, or logistics combined with AI skills is more valuable than pure CS backgrounds for many specialized roles, per OdinSchool's 2025 hiring report. if you're a commerce grad, learn AI in finance. if you're in life sciences, learn AI in healthcare. the generalist AI fresher is competing with everyone. the domain-specific AI fresher is competing with almost no one. the honest reality: the market isn't punishing freshers for being freshers. it's punishing freshers for being interchangeable. the old model — join a campus drive, get a mass-hire offer, learn on the job — is dying. the new model rewards people who show up having already built something real. the window to get ahead of this is 6–12 months of focused skilling. after that, the cohort of people who figured this out gets much bigger and harder to differentiate from. if you're a fresher reading this: what's your current plan — wait for placements to recover, or go build something right now? 🎯

• 
  Frantz Kati (@bahdcoder) reported 21 minutes ago

  @nnvictory001 Bro you need cloud automation like this. I have an agent on hivy that sends me a full cluster report four times a day. Automatically opens GitHub issues when there’s a critical bug And another agent automatically opens a PR with a fix. Costs me $0.08 per run for cluster analysis and email. Please let me set you up abeg it’s almost free and no subscriptions 🙏🙏🙏

• 
  Mikhail Rogov (@i_mika_el) reported 21 minutes ago

  @Felirami @steipete @openclaw Add a GitHub Sponsors or Buy Me a Coffee link beside Arca's OpenClaw issue history, so people who see the work can support you directly.

• 
  Mohi (@disismohi) reported 21 minutes ago

  Defense layer 2: block unknown SSH servers in egress rules. If CI only clones from GitHub/GitLab, enforce that at the firewall. A rogue server on the internet can exploit this trivially.

• 
  James Welbes - AI Bro (@JamesWelbes) reported 30 minutes ago

  @thekevingeary @flydotio I saw someone say something about GitHub having issues today

• 
  Fernanda Oyarzun (@fenaoyarzun) reported 31 minutes ago

  🚨 hanwha security cameras found shipping with github admin tokens baked into the firmware login page. this is the physical security industry, the one selling you peace of mind, and they can't even keep a token out of a public binary

• 
  Rohit Kumawat | AI Engineer (@merohitkumawat) reported 34 minutes ago

  THIS IS INSANE. India gave GitHub 3 hours to delete BitChat's code. Within hours, it was already mirrored on GitLawb a decentralized code platform. No company. No CEO to subpoena. No server to raid. You can order a takedown. You can't order a network nobody owns. #GenZProtest

• 
  adidshaft (@adidshaft) reported 35 minutes ago

  @freecodexyz what gets wiped at teardown, just the volume or GitHub auth too? `github-login` inside an ephemeral box is the bit i'd want spelled out.

• 
  Kevin Burton (@inputneuron) reported 37 minutes ago

  Two @github outages this week and a @useblacksmith outage as well as @AnthropicAI performance issues yesterday. This is stressful.

• 
  idongesit essien (@idongCodes) reported 42 minutes ago

  lol so github is down ?

• 
  jug (@juggernaurrr) reported 43 minutes ago

  I cannot believe they actually took down bitchat grow some ******* ***** @github You're supposed to protect open source code that's not malicious bitchat was never malicious

• 
  Roee Poleg (@roeepoleg) reported 44 minutes ago

  @github @github 4 days of critical issues blocking a whole organization and ZERO responses. I've never experienced such poor customer service in my life. So much for the "Enterprise experience" (#4595051, #4597898, #4600973)

• 
  Seriki Favour 👨🏽‍💻 (@favour_devs) reported 46 minutes ago

  What’s wrong w GitHub, trying to open PRs this evening, but server error 😟

• 
  pindarev (@ppindarew) reported 46 minutes ago

  @FidesFi Hi @FidesFi — opened a GitHub issue on the repo last week (pre-mainnet, one gap in the "rebalancer can't withdraw" guarantee) but haven't caught you there. I read the actual contracts, not a scanner — the in-kind mint/redeem value-conservation looks sound; my note is one narrower thing on the rebalance guardrails. Your DMs look closed — where's best to send it privately? Solo auditor, reports in bio.

• 
  Chawit (@ChawitAsava) reported 47 minutes ago

  GitHub cannot possibly be down again right?????

• 
  MCPCIO-Model Context Protocol (@robertmcpcio) reported 53 minutes ago

  This development in Safari's Technology Preview 247, specifically the integration of its MCP server, fundamentally alters how AI coding agents interact with web debugging. Previously, developers had to manually relay information like console errors, screenshots, and DOM states to their AI assistants, creating a time-consuming iterative process. The agent would then "guess" at solutions based on this secondhand information, often leading to further debugging cycles. The new MCP server allows these agents direct access to a live Safari browser session. This means the agent can independently retrieve console logs, examine network requests, capture screenshots, and even perform interactions with the page's elements. Tools like `browserconsolemessages` and `page_interactions` are now directly accessible, providing the agent with the same evidence a human developer would use. This direct observation drastically reduces the "telephone game" effect where descriptions can become distorted, enabling more accurate and efficient problem-solving. This shift towards browser-native agent tooling, with Safari joining platforms like GitHub and Google Drive in supporting the open MCP standard, suggests a significant move towards more integrated and intelligent development environments. It begs the question: as AI gains more direct access to our development environments, what previously manual tasks will become entirely automated, and how will that redefine the role of the developer?

• 
  Ed Pujol (@__KOPEK__) reported 58 minutes ago

  Dude do i need to pull the trigger and make my own *** hosting? Like github being down is un acceptable