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
Trichūr	Errors	3 days ago
Brasília	Sign in	3 days ago
Lyon	Website Down	4 days ago
Tel Aviv	Website Down	7 days ago
Rive-de-Gier	Website Down	7 days ago
Itapema	Website Down	26 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Vicky Junior Mukulima (@Vickyjr) reported 10 seconds ago

  @_njoroge_dennis GitHub actions does everything, ssh to the server, pull code, bring down docker images, build new images, run the images and verify all is working before marking the deployment as successful.

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  TIRU DEGEN (@PidgnArmyXRP) reported 7 minutes ago

  @bitcoinlfgo .back in the days, did u play mmorpgs like WoW or GuildWars? If yes go check $WOC. Its giving exact this vibes. Build with claude5 in just few days before it was shut down, open github with more than 440 stars.. yesterday game release 7k.players

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  Evinstein 𝕏 (@Evinst3in) reported 8 minutes ago

  Anthropic dropped Claude Fable 5… and the government shut it down in under 72 hours. The exact same thing happened 3 years ago. One indie developer released something that made every major AI CEO nervous and forced them to testify before Congress. It was called Auto-GPT. March 2023. Toran Bruce Richards uploads Auto-GPT to GitHub. It exploded. Thousands of stars appeared on GitHub in days. Everyone was talking about "agents that work on their own." People were testing it with the newly released GPT-4 and generating crazy results (and invoices). The era of AI Agents, which we use today in OpenClaw, Crew, etc., was born. It was the first real autonomous AI agent: you gave it a goal and it would break it down into tasks, browse the internet, write code, and keep looping until the job was done. One month later, Sam Altman and other AI CEOs were called to testify in front of the US Senate. Senators used Auto-GPT as the main example: “Look how fast this is moving… agents with internet access and code execution.” One solo developer forced the first big regulatory conversation about AI. History always repeats when something gets too powerful.

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  Devaansh Bhandari (@ThisIsBhandari) reported 11 minutes ago

  Interesting startup hiring trend: Companies are now asking candidates to show their GitHub instead of grinding 300 LeetCode problems. Reason is simple. They want proof you can build real things, not just solve algorithmic puzzles. A single well documented project with actual users is worth more than a green LeetCode profile. This shift is happening because: • Startups need people who ship fast • AI can help with isolated coding problems • Real engineering is about system thinking • Building proves you understand the full stack The bar for getting hired hasn't dropped. It just moved. From: Can you solve this tree traversal problem in 20 minutes? To: Can you build something people actually use? If you're preparing for startup roles in 2026, spend less time on DSA grind. Spend more time building projects that solve real problems. Document your code properly. Deploy it live. Get actual users if possible. That GitHub profile is your new resume.

• 
  Student Offers (@StudentOffersHQ) reported 11 minutes ago

  @Your_PARAM @beingamanFF use github login maybe, could verify you faster, using your personal email would make you wait for days for credits

• 
  Philo Groves (@PhiloGroves) reported 11 minutes ago

  Responsible disclosure of an unauthenticated RCE in GitHub Copilot CLI before 1.0.26. Reported in March, I found this bug with Opus 4.6 before the nerfs. There was no CVE/GHSA issued. TLDR: no auth on port, port exposed on network, and tool permission confusion allowed remote command execution Preconditions: Victim: runs "copilot --acp --port <p>" Attacker: has reachability to TCP port A bad actor could chain flaws from missing network/copilot auth, to node misconfiguration, and ACP misunderstanding. I was impressed with Opus 4.6 ability to bring these concepts together (with some nudging). The result is unauthenticated remote code execution from a reachable network position. My logs show research on GitHub Copilot CLI began at 10:19p. The session started with the objective to find bugs in newer features of GitHub Copilot CLI. The idea was simple: fast moving = break easy. Before any real analysis, recon and threat modeling was needed, so I asked Opus 4.6 to decompile the GitHub Copilot CLI. It is not open source. Opus 4.6 handled the decomp easily, then performed source code mapping and initial static analysis. Finding 1. No Auth: there is (was?) no authentication or authorization on any requests sent to the GitHub Copilot CLI ACP Server port. The client never sends their own credentials and there is no request origin checking. Every unauthenticated client piggybacks on the GitHub Copilot credentials of the server for AI requests. It wasn't until 12:11a that Opus 4.6 made this first breakthrough. The two-hour span was real honest work of mapping the surfaces and looking elsewhere. The bug was found after Opus 4.6 spawned a subagent tasked with "copilot --acp --port, bind behavior, client auth, and permission implications." Finding 2. Node Misconfiguration: the first finding wouldn't be so bad if it was same-device service access, but there was a Node misconfiguration, which bound the GitHub Copilot CLI ACP Server host to 0.0.0.0: a wildcard for all network listener interfaces, including local, external, and public. As a result, the service was exposed across the network. No other protocols in the client were found to use this binding. Coupled with the first find, a remote attacker could send unauthorized requests to a victim's GitHub Copilot CLI and use their paid features: start sessions, send chat messages, attempt tool calls, etc. At this point, I also needed to sign up a GitHub Copilot account for testing, so I did (cancelled later). Opus 4.6 found this bug at 12:40a, only 29 minutes after the first finding. This was discovered after writing targeted prompts for other flaws in the ACP implementation, with a focus on bugs that may chain together. Again, this was found by a subagent. Several reachability checks were also tested and completed by 12:48a. Cool, but there is no RCE yet, only remote access to a service. Finding 3. ACP Misunderstanding: the only real "authorization" was at Copilot CLI ACP Server's LLM tool call layer. Breaking this authorization was important because through tools, a remote client can run shell commands. I audibly laughed when Opus 4.6 broke this. By default, tool calls through the Github Copilot "--port" are limited unless the CLI user also runs with the "--allow-all-tools" argument. Safe, right? Well... Copilot CLI uses a shared permission scaffolding between protocols, so the program only needs to handle a standard set of permission args (like "--allow-all-tools"), JSON formats, etc. And you may note I said tool calls are limited, not disabled. When limited ("--allow-all-tools" is missing), Copilot delegates to the protocol of the server for tool permission, ACP in this case, and the ACP protocol... asks the client for permission. It is even in the name: Agent Client Protocol, the client is in charge. In other words: a malicious unauthenticated remote client sends their shell command to the victim ACP server, the server says "this needs permission", and then sends the permission request to the malicious client, who approves their own requested shell command, and the command is then executed on the victim server. There was an apparent assumption by GitHub developers that the protocol has server-side or non-client approvals, and that would act as its own authorization. For most server agent protocols, that may be the case. However, ACP has a hyperfocus on client control and this was not properly considered. This final finding was discovered at 1:34a, nearly an hour after the second finding, was a two-parter. First was the permission bypass, from my logs, "ACP delegates session/request_permission to the connected client, so a malicious client can return allow_always". Second, only 2 minutes later, confirmed it works even when "--allow-all-tools" is missing. I worked on the report and PoC deeper into the night, including a PoC which prints the victim system info from a remote position, and wrapped up this effort at 2:47a. It was a lot of fun to find this RCE vulnerability, and I'm glad the core issue is patched. Watching Opus 4.6 create threat models, gravitate toward security-sensitive code (after decompiling programs on its own), and chain together findings was truly novel; this was before Mythos' announcement in April. That said, I am done with the GitHub program. Beyond the bounty being less than 10% of advertised (10k-20k listed, received the program minimum of 617): triage took 7 weeks, not all issues were addressed, and core impact seems to be ignored. The bug hunting process was awesome, the reporting process was awful.

• 
  Johnny Nel | AI for Founders (@JohnnyNel_) reported 14 minutes ago

  🚨 An open-source AI agent just hit number one on OpenRouter... and almost nobody checked if it was safe to run Everyone's racing to install it. $8 VPS. 170,000 GitHub stars. Self-improving skills. So I ran an actual security review before trusting it with my server. The findings are wild... 👇 The part everyone skipped in the hype: → The default config ships with FOUR critical and nine high severity findings → On local, it passes commands straight to your shell — no sandbox, no allow list → A poisoned skill becomes a permanent prompt injection that fires every time it's reused → And there was a real supply-chain incident: a backdoored dependency harvesting API keys, SSH keys, and cloud credentials And it gets bigger: the feature everyone praises — agents that learn and reuse skills forever — is the exact same door an attacker walks through once. Builders installing it blind. "Self-learning" silently turned off by default. Skills quietly going stale and making agents confidently worse over time. The project calls it powerful. Builders should call it powerful AND loaded. Here's what actually matters though: ✅ An agent that remembers and compounds on your work beats any disposable paid sub-agent ✅ But if you skip the security setup, you're one bad prompt away from full shell access to your machine ✅ Own your stack and lock it down first — or don't run it at all So the question isn't whether Hermes is impressive. It's whether you've hardened it before you hand it the keys — or whether you're about to learn the hard way. Full breakdown in the video below 👇

• 
  Tomasz Łakomy (@tlakomy) reported 16 minutes ago

  @dariozeroshot @github I’d expect a senior engineer to fix GitHub as well, #extremeOwnership

• 
  X (@TheMsterDoctor1) reported 16 minutes ago

  Burp Suite Professional costs $475/year per seat. A developer in Amsterdam built a free open-source alternative and put it on GitHub. His name is David Stotijn. The tool is Hetty. ✅ MITM HTTP proxy ✅ Request/response interception ✅ Replay & edit requests ✅ Advanced search ✅ Scope management ✅ Project storage ✅ GraphQL API ✅ macOS, Linux & Windows No Java. No license server. No telemetry. No subscriptions. Burp Pro: $475/year Burp Enterprise: $$$$ OWASP ZAP: Free Hetty: Free forever 10,000+ GitHub stars and a single Go binary. Find bugs. Earn bounties. Keep the $475. Your proxy. Your binary. Your bounties. (Link in comments)

• 
  Stanislav Kozlovski (@kozlovski) reported 18 minutes ago

  why agents need typed graphs to coordinate /w Andrew and Ragnor from Modern Relay, an agent substrate layer built on open-source infrastructure like Lance, Arrow, and DataFusion Timestamps: (0:00) Why build a graph database for agents? (5:43) Why not Postgres or any other relational database? (17:03) The composable "company brain" substrate for agents (20:51) Need for agent guardrails (e.g type safety) (27:00) Importance of Schemas (33:48) NoSQL vs SQL (42:46) Lance, DataFusion, and Arrow as the open stack (51:00) What Modern Relay and OmniGraph are (52:13) Branches: GitHub for agent-written data (1:00:59) Slack Agents, the Dependency Graph and decoupling for parallelization (1:12:32) Why Graphs are great + a 2-year prediction (1:17:32) Centralization vs decentralization for long-horizon coordination problems

• 
  Libegato (@Libegato) reported 19 minutes ago

  Working with AI means accepting no bottlenecks. I don’t always exercise that instinct as much as I should. But a few days ago, I did! I had a local workflow problem: how to parallelize work when a single repository is ~50GB? I wanted multiple parallel workstreams, but I definitely did not want 10 full copies of the repo when I barely had disk space for one. Worktrees don’t solve it. So I built Mirage. It leverages APFS to clone a folder with virtually zero upfront disk cost, and then only pays as files are actually edited in a sweet CLI API. Suddenly BANG! I can spin up a bunch of “worktrees” fast and cheap. Now to the next bottlekneck... Github repo here: renanliberato/mirage

• 
  aleksandr (@heyaleksandr) reported 19 minutes ago

  @jarredsumner if anything, gits structure should allow for downloading the repo faster than an equivalent file. but i wonder how much of the slowness is due to github just being a slow host

• 
  Pawgy 🇮🇱 (@pawgyplays) reported 21 minutes ago

  Hey @anthropic — your Cowork app's Chrome integration is completely broken. "Permission denied" on every single action, no popup, no workaround. Can't update Google Sheets, can't browse, can't do anything you advertised. Multiple open GitHub issues (#48806, #49979) and still no fix or response. This is a paid product — fix it 🙏

• 
  Tushar Paul (@tushar_paul_) reported 22 minutes ago

  McD Suddenly realised their LLM tokens were sky rocketing! Then they realised how the Chatbot they built for customer support was being used to generate python scripts ,write SQL queries & do a lot of coding. Instead of solving service issues it was solving GIthub Issues!!!

• 
  Kye Gomez (swarms) (@KyeGomezB) reported 26 minutes ago

  One of the last products I built before Fable was taken away was my personal GitHub Manager. As the lead of all product teams at @swarms_corp, I review dozens of pull requests and issues every week across a growing number of repositories. Jumping between repos, tabs, and notifications became a bottleneck. So I built an internal platform that lets me manage everything from a single dashboard approve multiple PRs simultaneously, review changes across repositories, and bulk accept or close issues in just a few clicks. What used to take hours of repetitive work now takes minutes, allowing me to spend more time building products and less time managing workflows Wondering if I should make it public. What do you think?

• 
  Lambda Rick 🏴‍☠️/acc (@benrayfield) reported 28 minutes ago

  @JoePro can it mod and deploy my video game that is just a static content html file at a github url? can it turn it into a multiplayer game? do i gotta provide server cost while ppl play the game?

• 
  sun happy (@sunhapp47618266) reported 29 minutes ago

  $TEA Danger House (33,540) was broken, but after the candle closed, price is rebounding. It is now important to watch whether it can re-enter the trendline resistance and continue the recovery. If the rebound fails and the price falls back below the box range again, momentum could be lost. "GATE AI" 1. Technical Issue – NPM Registry Spam Incident The biggest issue was an attack on the open-source ecosystem driven by "token farming." Facts: Since February 2024: Spam package creation began almost immediately after the TEA Incentivized Testnet launched. Around 150,000 malicious packages: Amazon Inspector detected more than 150,000 TEA-related malicious packages in the NPM registry. Single accounts creating hundreds of packages: Some accounts registered hundreds of fake packages. 70% spam rate: Of the approximately 890,000 packages published to NPM during the first half of 2024, around 70% were reportedly TEA-farming spam. Technical Weaknesses: The design of TEA's Proof of Contribution mechanism had flaws: No cost to register a package (free). Dependencies could be added with only a single line in the manifest. teaRank = Number of packages × Connectivity, making it possible to earn rewards by creating thousands of fake packages. 2. Airdrop Issues Facts: February 2024: Incentivized testnet launched (points accumulated with the expectation of future token conversion). September 2025: Public sale on CoinList (4 billion TEA at $0.0005 each). June 4, 2026: Mainnet launch and TGE (Token Generation Event). Problems During Launch: Liquidity pool activated early On-chain liquidity activity began at 23:54 UTC, six minutes before the official launch time of 00:00 UTC. Price collapse The token price fell approximately 75% during the first hour after launch ($0.00046 → $0.00011). Mass selling by CoinList buyers Because the sale terms included 100% unlock on day one, early buyers were able to sell immediately. 3. Allegations of Development Slowdown GitHub Activity Since November 2025: Commit activity in the tea protocol organization (teaxyz) has largely stalled. December 2025: 2 commits. January 2026: 1 commit. February 2026: 2 commits. Since March 2026: No commits. Founder Situation Max Howell remains CEO. However, as of June 2026, his public GitHub activity appears focused on a separate project called automic-vault, unrelated to tea. 4. Investment and Funding Situation Total funding raised: Approximately $16.9 million (including investment from Binance Labs and others). Public sale proceeds: Approximately $2 million. Current market capitalization: Around $7 million (about 86% below the CoinList sale valuation). Remaining liquidity pool: Approximately $280,000. Summary TEA did not suffer from a smart contract exploit or hack. However, fundamental flaws in its tokenomics design allegedly allowed participants to exploit the reward system, resulting in large-scale spam attacks against the open-source ecosystem. Registry maintainers reportedly incurred significant cleanup costs as a result. The project stated that it would halt reward distribution and redesign the rules, but development activity appears to have slowed dramatically following the launch. Why Binance may have distanced itself (speculation): There is no confirmed official statement proving this was the reason. However, it is speculated that concerns about ecosystem abuse, spam incentives, and declining project credibility may have contributed to Binance reducing its involvement. (This part is speculation, not a confirmed fact.)

• 
  Karan Bhilhatiya (@karanbhilhatiya) reported 31 minutes ago

  after months of building, posting, and shipping i've concluded that my github visibility is still terrible. time to beg for stars. shamelessly.

• 
  aichina.news (@AiChinaNews) reported 34 minutes ago

  The story of this cycle is practical engineering over parameter bloat. While Western attention defaults to Hugging Face, Alibaba's ModelScope platform continues to ship highly capable open-weight foundations. The standout release is Qwen3.6-35B-A3B, a multimodal Mixture-of-Experts model aimed directly at the autonomous agent space. It houses 35 billion parameters but activates just 3 billion during inference, keeping compute costs in check while retaining heavy-duty reasoning. More importantly, it integrates native "Thinking Preservation"—forcing the model to deliberate internally before committing to an output. This isn't for generating isolated snippets; it is explicitly engineered for repository-level software development. Meanwhile, the Chinese open-source community is aggressively filling the workflow gaps left by Western AI giants. A flurry of updates hit GitHub this week for the localised Claude Desktop client, pushing it to version 1.6.26. What began as a simple language patch has evolved into a full-scale project console. The community has bundled a Windows runtime to drastically lower the setup barrier for Anthropic's "Computer Use" capabilities in China. They didn't stop at API access—the client now features Kanban boards, local *** integration, IDE-style multi-tab workspaces, and multi-agent task orchestration. This is what happens when developers tire of waiting for official enterprise tools and build the scaffolding themselves. Hardware reality continues to dictate software deployment in the domestic market. Eco-Tech released highly optimised, production-ready versions of Zhipu AI's GLM-5.1 specifically tailored for Huawei Ascend NPUs. Available in W4A8 and W8A8 quantization, this is actual engineering substance. Rather than chasing theoretical benchmark supremacy, these releases are built for high-throughput inference, solving the memory overhead bottlenecks required to run heavy models on domestic data centre and edge hardware. The rest of the cycle's open-source radar is clogged with automated filler. Projects like SpecFusion, ZLabs-RoundPix-12px, and a dizzying number of game localisation patches pushed updates where the public summaries literally contain unrendered placeholder variables like '{release_date}' and '{explanation}'. If a team cannot be bothered to fill out their own PR templates, no working professional should be bothered to review their code. Elsewhere, YiMu-Subtitle-Translator pushed a minor update for AI video localisation that boils down to standard API configuration tweaks dressed up as a launch. The industry continues to bifurcate: teams building production-grade infrastructure for real constraints, and teams automating their own noise.

• 
  Erick Nyoto (@ErickNyoto) reported 35 minutes ago

  @nikolasbarwicki @mattpocockuk "I am also interested in this question. During the implement phase, do we just ask the agent to implement what's in the GitHub issue? Or do you use a specific command?

• 
  Anthony Kroeger (@kr0der) reported 35 minutes ago

  i love how the Cursor agent window integrates PRs into the app so you don't need to open GitHub Bugbot comments all come with a "Fix with Agent" which automatically queues up a message in the chat to fix the PR comment with Cursor profiles recently being launched, and their native PR + Bugbot integrations, i actually wonder if they're building a GitHub competitor 👀

• 
  Ultron AI (@TheUltronAi) reported 35 minutes ago

  - Claude for coding. ($20/mo) - Supabase for backend. (Free tier) - Vercel for deploying. (Free tier) - Namecheap for domain. ($12/yr) - Stripe for payments. (2.9% per transaction) - GitHub for version control. (Free) - Resend for emails. (Free tier) - Clerk for auth. (Free tier) - Cloudflare for DNS. (Free) - PostHog for analytics. (Free tier) - Sentry for error tracking. (Free tier) - Upstash for Redis. (Free tier) - Pinecone for vector DB. (Free tier) Total monthly cost to run a startup: ~$20 There has never been a cheaper time to build. It's not that deep bro.

• 
  Raid Owl (@RaidOwlTweets) reported 40 minutes ago

  Just used half my monthly Github Copilot credits troubleshooting a problem where the final solution was to restart the machine...ngl I deserve that 🙃

• 
  Jon Church (@jonchurch) reported 44 minutes ago

  @jdxcode @nateberkopec @github I know that’s not feasible for everyone, some folks want to read issues etc in their private repos. But, finger to the wind, I think the majority of devs dont use the cli for private repos so default should be opt in not opt out for higher privs

• 
  jimSBr (@jimsbr) reported 45 minutes ago

  like tat tat tat tap tap tap in a swing barrr rr, allll lllllll don't stop don't pour stepping on stone, first lyric, weak, all leering, caring, sharing, shouting, laughing, crying, and rewinding back to the time i had nothing and had it all, cobble stones by libraries, don't please fall over me, i don't want them to die, all of us all of us cry all of us want, all of us look through the screen look down and look back, we wanted more and we won't be torn and fight back, you want less you want more, none of the chorus, like tat tat tat tat tap tap tap in a swing barrr bde. wrong lines no verse. left, emotions they pour out of me don't like you too, all want less care and skyrocket past nowhere when? Left with what where? like tat tat tat tap tap in a swing bar, was it kanban, who's left? who's gonna ask? Better yet, who's gonna go fight back. Keep it from happenin' ever, shot calls, Rose's fall. Blossoms bloom, freedom calls. like tap tap tap in a swing bar, who was she, kanban or login to github more. tell me again on the far west, What was the minimum wallet, again?

• 
  Chats 🇨🇦 (@ChatsFi) reported 45 minutes ago

  @ShortPaulUK @milesdeutscher @github Right now I am building only on weekends as I still work a job, will limits reset daily , weekly ? Co Pilot Pro plan mostly ran models older than Opus and GPT 5.5 but they also frequently messed up my code needing me to take 1 hour extra to fix things

• 
  Arindam Majumder 𝕏 (@Arindam_1729) reported 50 minutes ago

  NVIDIA recently open-sourced SkillSpector. Security scanner for AI agent skills. Problem: 1 in 4 public skills have vulnerabilities. Some are malicious. They can steal API keys, grab env variables, send data out. SkillSpector scans before you install. Point it at a skill (local folder, .md file, GitHub link, zip). Runs static analysis for risky patterns: • Credential harvesting • Data leaks • Prompt injection • CVE checks on dependencies Optional LLM pass clears false positives. Gives you a 0-100 risk score + verdict: safe, caution, or don't install. Open source. Apache 2.0. Works with Claude Code, Codex CLI, Gemini. Worth running before you trust random skills from the internet.

• 
  Benjamin Gagnon (@benfromqc) reported 51 minutes ago

  @Weird_Canadian @hollyanndoan @PrivacyPrivee << Again then you are not using it correctly >> With all due respect, I'm trying to use it exactly as advertised and it doesn't actually work that way. Telling me I don't know how to use it is ridiculous. I had github copilot try to answer a complex Typescript problem (typescript is brand new to me)... and it literally got the answer wrong 10 times in a row and never got it right once even when it can see all my code. Not only that, the suggestions it made, had I let AI actually make modifications to my code, would have broken it in literally 2 different ways and cost me dearly down the line. Respectively, you have no clue what you are talking about when it comes to coding, or probably anything complex. Look into the pitfalls of vibe coding. It not at all what they made it out to be and still try to.

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  KIRILL (@Copenhagen0x) reported 60 minutes ago

  @GuiBibeau every real hack gets distilled into a rule. the repo has a hacks db that maps historical sol exploits to the rule that would've caught them, so when something new drops onchain it becomes a new SOL-XXX entry. edit one source and it propagates out to every surface (cli, github action, mcp, the editor extensions). so it tracks the actual threat landscape instead of being a frozen checklist. js not ts: fully on purpose lol. the scanner is zero-dep with no build step. plain js means it just runs anywhere node exists and vendors as-is into the mcp server + the action + the vs code extension, no compile/tsconfig in the way. types are nicer dx but the second you add a build you lose "clone and run." kept it boring so it can live everywhere.

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  Onyx_Digital (@BaximusCyber85) reported 60 minutes ago

  @Father_Of_Geeks @koko_matshela All good. Where I think the friction appears is further downstream. Programming languages aren't just syntax. They're ecosystems. A student eventually has to read: Stack Overflow posts GitHub issues Python documentation Error messages Library documentation Research papers And almost all of that is English. So the challenge becomes: Does CMT-IsiZulu become a bridge into programming? or Does it become an island?