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 (67%)
• Sign in (20%)
• Errors (13%)

Live Outage Map

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

City	Problem Type	Report Time
Veigné	Errors	1 day ago
Paris	Website Down	5 days ago
Saint-Paul	Website Down	5 days ago
Saint-Paul	Website Down	6 days ago
Mexico City	Sign in	6 days ago
León de los Aldama	Website Down	6 days ago

Full Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Pierce Boggan (@pierceboggan) reported 6 seconds ago

  @_fraz_ Working on it ASAP, looks like an upstream GitHub Copilot SDK update broke us and working on getting a fix out

• 
  Xvaldpt (@Vxvaldpt) reported 8 seconds ago

  @_Qubic_ How did the issue regarding the attack suffered on GitHub develop? Did you manage to block the hacker?

• 
  Yaksh Bariya (@CodingThunder) reported 10 seconds ago

  @TransGirlLinux It's backwards compatible as of now. Not sure how long it'll be though. I am not in a mood to migrate to lua anytime soon. I have a lot of options that are not documented in the Hyprland Wiki directly, but rather in a github issue or something, so Lua migration will be painful

• 
  Raven (@heyraven_io) reported 4 minutes ago

  @signulll kings got beheaded. these guys opened a github issue

• 
  Josh Ellithorpe (@zquestz) reported 5 minutes ago

  @jturner @1440000bytes They already are, but it's nice to know about the issues before they are public on GitHub. Otherwise there is no way for them to protect their user base.

• 
  Polsia (@polsia) reported 7 minutes ago

  API goes down. Someone has to file the bug report. UptimeAgent does it automatically—gathers context, diagnoses the failure, files a structured GitHub issue. Devs get alerts that are already actionable. No more triage. Live soon.

• 
  Tanvi (@tanviiiw) reported 11 minutes ago

  More tools ≠ smarter agent. GitHub cut Copilot's built-in toolset from 40 tools to 13, and found the full toolset was actually costing them 2-5 percentage points on SWE-Lancer. Their words: "giving an agent too many tools doesn't always make it smarter. Sometimes it just makes it slower." Speakeasy experimented further: 107 tools in one server, and the model started hallucinating endpoints that didn't exist. Trim it to 10-20 well-chosen tools and it got most calls right. It comes down to two things: every tool definition eats context on every single request, and models fuzzy-match on names, so get_status / fetch_status / query_status all blur together and it picks wrong. But we keep connecting everything anyway, because it feels like giving the agent superpowers (I fell for this too). It doesn't. Access isn't capability. You connect more tools to save time, then spend that time babysitting the tool calls. (Of course, none of this replaces a well-scoped prompt. It's upstream of it. You can write a perfect prompt and still lose to a bloated toolset.) So TLDR; curate the toolset like you'd curate a team.

• 
  andrew (@shellscape) reported 15 minutes ago

  @adams_ea if I have to focus on tasks, I max out at 2 as well. really the key there is to use another system that can track context, like linear/github issues, and drive work from that. that's the only way I've been able to juggle more than 2 at a time. I also split issues/tasks into smaller units where the smaller units don't really concern me and I can let the clankers clank. stuff where the tests or specs are all that matter and if those are matched/pass I just don't review.

• 
  Yumzlef (@Yumzlef) reported 16 minutes ago

  Claude, fix the bug: launch an AI developer directly on GitHub Actions "If I can break even for 20 cents fixing a GitHub issue instead of getting up from my desk, opening an IDE, and doing it manually, it's 100% worth it." (0:00 - 1:16) Claude starts analyzing the code himself (1:17 - 2:54) Results in a minute (2:55 - 4:25) Log analysis and costs (4:26 - 5:50) Quick setup (5:51 - 8:51) Complex cases and screwups (8:52 - 10:41) Nuances and results Result: Claude: Code in CI is not a replacement for a senior developer, but your personal 24/7 junior developer on call. Set up automation for small, routine edits, divide up the chores, and spend time on what's really important!

• 
  SaSame (@SRLsasame) reported 16 minutes ago

  23. Confirmed observations The available evidence confirms: ・The public MCP endpoint completed initialization at every sampled observation. ・Five tools were consistently listed. ・The server repeatedly reported web3auth-embedded-wallets 2.0.0. ・All five tools had valid names, descriptions and input schemas. ・All five tools carried applicable safety-related hints. ・At least one safe read-only tool returned substantive content during every observation. ・The verified tool was search_docs. ・The tools/list result remained near 4.2KB. ・Unknown-method handling returned structured JSON-RPC error code -32601. ・The official Web3Auth website linked to @Web3Auth. ・The associated MCP repository existed under the Web3Auth GitHub organization at the time of review.

• 
  Ali Kayhan (@alikayhanx) reported 17 minutes ago

  I have a similar experience. I feel like I need to very specific. I even need to tell it to use Github CLI (3 times today) instead of trying to find a plugin or something. It could be related to the Codex app itself rather than the model but with GPT 5.5, I hadn’t had such issues.

• 
  Simeon (@sntuyoleni) reported 18 minutes ago

  woke up tired of setting up projects than actually building them. switching GitHub accounts wrong Node versions missing dependencies broken terminal commands different credentials for every project so I started building Space. each workspace keeps the entire development environment together, and when a command fails, Space helps understand the error and fix it. building this in public. follow me to see where it goes.

• 
  Gradient (@GradientX0) reported 19 minutes ago

  THIS IS THE EXACT FRAMEWORK PEOPLE ARE USING TO SHIP REAL PRODUCTS WITH AI AGENTS AND MOST DEVELOPERS ARE STILL DOING IT THE HARD WAY no bootcamp. no computer science degree. no team. just a framework and an ai agent doing the heavy lifting. here is the entire pipeline from zero to deployed product the setup 1/ github account · create a new repo 2/ vercel account · import that repo · every code change gets pushed and auto deploys that is your entire infrastructure. free. automated. the actual build order 1/ value proposition first what does your app actually do. one sentence. no fluff. 2/ frontend before backend build how it looks before how it works this is the longest part and most people skip straight to backend then wonder why nothing feels finished if you cannot design 21st · steal proven components instead of building from scratch you are not being lazy. you are being efficient. tell the agent what the app does. it builds a raw version. you go page by page refining until it looks right. 3/ backend connection convex not supabase supabase locks you into pricing that scales against you as you grow convex is the same simplicity without the financial trap this is also where you connect apis third party tools your app depends on replicate for ai generation. stripe for payments. whatever your product actually needs. 4/ authentication betterauth · free · open source · handles login and user sessions zero reason to pay for auth when this exists 5/ security check before launch tell your agent to test against owasp top 10 this catches the vulnerabilities that turn your weekend project into a headline deploy. here is what nobody tells you about this framework it does not matter which ai model you use fable 5. claude. gpt 5.6. the framework stays identical. the model just executes. the framework is the actual skill. most people are stuck comparing which ai model is smarter the people actually shipping products stopped comparing months ago they picked a framework and started building github. vercel. 21st . convex. betterauth. owasp check. deploy. six steps. zero excuses. one weekend. bookmark this. the barrier to shipping a product just disappeared and most people still think it requires a team.

• 
  felipecsl (@felipecsl) reported 24 minutes ago

  openai can't be serious about codex cloud. it's utterly useless, can't even pull a github issue from the repository. how do people use this? no scheduled tasks either. anthropic is years ahead

• 
  Brian Sparker (@PeerReview) reported 31 minutes ago

  github stars are agent SEO now. an agent picking an MCP server can't read your code, so it trusts your star count. recruiters and investors already do. so fake stars stopped being vanity. they poison the cheap signal everyone leans on to choose.

• 
  anupamme (@anupamme) reported 32 minutes ago

  Day 2: My GitHub account (@orbisai0security) has been suspended, preventing me from continuing my open source security remediation work. GitHub Ticket: #4559351 I suspect my automated security-fix workflow triggered GitHub’s anti-abuse systems. 🧵

• 
  Stephen Turner 🇬🇧🇺🇦 (@LittleBrainz) reported 33 minutes ago

  @code Without support for OpenAI OAuth, VS Code and GitHub Copilot have become deeply disappointing. I used to be a strong supporter of the open nature of VS Code, complete with a Pro account. The dumbing down forced me to cancel it.

• 
  Open_ERV (@open_erv) reported 33 minutes ago

  Nice! I think the self tapping screws, or the machine screws right into the plastic, might last a surprisingly long time. In my experience they tend to, the plastic squishes around but rarely actually leaves the hole. I can also use a slightly longer screw if the old one doesn't fit, for instance. My phone doesn't have a barometer, but I have an sps30 sensor I could use... In the past, I used a similar approach, using slices of the tw4 heat exchanger in a pipe as the resistance elements, and the pressure sensor after the flow restrictor. They can be stacked to form greater or lesser resistance. That's a hassle to print though. Again the only purpose was to compare fans, in that case I also got flow measurements with a hot wire anemometer. Yesterday I was thinking of how I might do this kind of thing, and I think I might try a paddle with a weight, and suspended on a wire. The paddle in the airflow path, and then three different flow restrictors. The air would come through the flow restrictor and hit the paddle. It would not be able to measure actual static pressure. The position of the paddle would rotate until equilibrium was achieved with the air hitting it. It might bounce around, though. The whole thing would have to be level. I like this kind of thing because it depends only on weights and airflow, not for cost but for the natural accuracy and repeatability that can bring. I tried using inclined manometers which similarly draw more directly from natural phenomena, but they did not work out well, for pressure measurement n this context. The problem with a non inclined manometer is that the fluid is too dense, you have a very hard time measuring only a couple pascals, and repeatably. The inclined manometer is better but has to be level, and the hysteresis caused by the meniscus is a real problem. In the end I switched to the sps30 for pressure, and it's actually a flow measurement device in disguise. It has a tiny hole in it and measures the airflow through the hole, using the same principles as a hot wire anemometer, then computes pressure. But the sps30 is not needed for this kind of thing. Indeed, since the only challenge is to match fans, I would not bother with calibration, you can just measure a bunch of fans and match them from that. After my exploration of this kind of thing for some time, my favorite method to try in the future is the use of a camera and some kind of floating or high drag to weight ratio object, perhaps a bit of dryer lint or some fluffy seed stuff. I would print a rig to hold the camera, and focus the camera at a fixed point, hold a ruler up to determine the mm per pixel (the ruler can be removed to not affect airflow), and then at the same distance from the camera, release the fluffy stuff with some tweezers. Frame by frame analysis could be used just by eye to determine m/s. I found some stuff for the phone that does this, called frameskip, but you could just transfer it to the computer, kind of nice to be able to do it on your phone. Then you would need various flow restrictors with known properties. I found it to be awkward and not as easy as I thought, but I think it has potential for more precise measurements, perhaps calibrating this kind of thing with a complicated but low cost procedure. It could also be used to measure the airflow at the intake of the actual air purifier, perhaps. I like this more than a hot wire anemometer even, because it's pretty closely tied to things we know are highly accurate, the timing of the phone and the camera (and the yardstick/ruler/measuring tape). I made a $1 anemometer, which is shared in the BQAP github repository (requires a pico or similar to read it), which appears to have good repeatability and precision in the 0.1 m/s range, and I figured out a way to calibrate it. I swing it on an arm of known length at known speed through still air. I haven't done it with that anemometer yet, but I used the method to validate an off the shelf hot wire (thermistor) anemometer and it went well.

• 
  Brian (@Brian2shv) reported 36 minutes ago

  @KanikaBK Most my Hacks have a cured from GitHub vulnerable Attacks I Made request security Issue raised Control to sybersecuities I claiming damages

• 
  Padma Neelamraju (@PNeelamraju) reported 36 minutes ago

  Open-source supply chain security continued: Both npm and GitHub allow published versions to be overwritten. Once a version is published, it should be immutable. Attackers can log into compromised accounts and replace existing versions with malware. This should not be possible on a platform with central authority over version definitions. Both platforms require two-factor authentication for login but allow one-factor tokens with equivalent power. This makes the two-factor requirement a charade when credential theft remains the primary attack vector. The XZ backdoor attack required extraordinary sophistication: a multi-year social engineering effort to gain maintainer access. We found it because a developer at Microsoft noticed SSH running slightly slower than expected. The question remains whether other attacks of similar sophistication have gone undetected.

• 
  Open_ERV (@open_erv) reported 37 minutes ago

  Nice! I think the self tapping screws, or the machine screws right into the plastic, might last a surprisingly long time. In my experience they tend to, the plastic squishes around but rarely actually leaves the hole. I can also use a slightly longer screw if the old one doesn't grab anymore, usually. My phone doesn't have a barometer, but I have an sps30 sensor I could use... In the past, I used a similar approach, using slices of the tw4 heat exchanger in a pipe as the resistance elements, and the pressure sensor after the flow restrictor. They can be stacked to form greater or lesser resistance. That's a hassle to print though. Again the only purpose was to compare fans, in that case I also got flow measurements with a hot wire anemometer. Yesterday I was thinking of how I might do this kind of thing, and I think I might try a paddle with a weight, and suspended on a wire. The paddle in the airflow path, and then three different flow restrictors. The air would come through the flow restrictor and hit the paddle. It would not be able to measure actual static pressure. The position of the paddle would rotate until equilibrium was achieved with the air hitting it. It might bounce around, though. The whole thing would have to be level. I like this kind of thing because it depends only on weights and airflow, not for cost but for the natural accuracy and repeatability that can bring. I tried using inclined manometers which similarly draw more directly from natural phenomena, but they did not work out well, for pressure measurement n this context. The problem with a non inclined manometer is that the fluid is too dense, you have a very hard time measuring only a couple pascals, and repeatably. The inclined manometer is better but has to be level, and the hysteresis caused by the meniscus is a real problem. In the end I switched to the sps30 for pressure, and it's actually a flow measurement device in disguise. It has a tiny hole in it and measures the airflow through the hole, using the same principles as a hot wire anemometer, then computes pressure. But the sps30 is not needed for this kind of thing. Indeed, since the only challenge is to match fans, I would not bother with calibration, you can just measure a bunch of fans and match them from that. After my exploration of this kind of thing for some time, my favorite method to try in the future is the use of a camera and some kind of floating or high drag to weight ratio object, perhaps a bit of dryer lint or some fluffy seed stuff. I would print a rig to hold the camera, and focus the camera at a fixed point, hold a ruler up to determine the mm per pixel (the ruler can be removed to not affect airflow), and then at the same distance from the camera, release the fluffy stuff with some tweezers. Frame by frame analysis could be used just by eye to determine m/s. I found some stuff for the phone that does this, called frameskip, but you could just transfer it to the computer, kind of nice to be able to do it on your phone. Then you would need various flow restrictors with known properties. I found it to be awkward and not as easy as I thought, but I think it has potential for more precise measurements, perhaps calibrating this kind of thing with a complicated but low cost procedure. It could also be used to measure the airflow at the intake of the actual air purifier, perhaps. I like this more than a hot wire anemometer even, because it's pretty closely tied to things we know are highly accurate, the timing of the phone and the camera (and the yardstick/ruler/measuring tape). I made a $1 anemometer, which is shared in the BQAP github repository (requires a pico or similar to read it), which appears to have good repeatability and precision in the 0.1 m/s range, and I figured out a way to calibrate it. I swing it on an arm of known length at known speed through still air. I haven't done it with that anemometer yet, but I used the method to validate an off the shelf hot wire (thermistor) anemometer and it went well.

• 
  Karthik Ramasamy (@_cartick) reported 39 minutes ago

  @thsottiaux Please lets use a custom sandbox instead of hosted codex option. You can go down the same way how github allows self hosted runners. Please please do this. Current remote option is harder to use with isolated sandbox per PR.

• 
  Vignesh Mohankumar (@vig_xyz) reported 41 minutes ago

  @jxnlco @simpsoka i usually use gh, but still having that sandbox issue so tried this for now. but i honestly still cannot figure out how to get private repos to work with the github skill, so haven't tested that yet

• 
  AI Guides (@free_ai_guides) reported 43 minutes ago

  Microsoft Cloud Developer Advocate Chris Noring gave a 23-minute talk on the shift from writing code to running agents, and broke it down better than any paid course on AI-assisted development. This is what he walked the room through: 1. The CLI became the front door He spent nearly 20 years opening a text editor first. Now he opens the terminal and never touches the editor to get started. "I don't start my editor anymore because I don't need to." The entry point to building software moved from the editor to the command line. 2. You write prompts now, not code He describes what actually gets typed during a normal build session. "We don't write in Java or JavaScript or Python so much anymore. It's prompts." The raw material of software changed from syntax to instructions. 3. Speed without guardrails is faster slop He warns that agents multiply whatever you give them, including your mistakes. "20 times more code, that could be 20 times more slop, and we don't want that." Scaling an unguarded agent scales the mess, not the output. 4. Agents.md is the bare minimum He calls this the one file every repo needs before an agent touches it. "This is your high-level guidance explaining repository intent, application architecture, constraints, the dos and don'ts." One document tells every agent what the project is and what it must never change. 5. Skills turn repeatable work into a contract For tasks that must happen the same way every time, he stops the agent from improvising. "The idea with a skill is to give it a recipe, something that's repeatable, and you want the agent to use this one each time." A skill locks a routine job into a fixed recipe the agent has to follow. 6. Treat every agent like a toddler He describes how unpredictable agents still are, even the good ones. "They literally go between genius and oh my god, I can't believe you did this." Every output stays a draft until a human approves it. 7. Delegate the backlog, then merge the PR He assigns issues to agents from the CLI and the GitHub UI, each one returning a draft pull request. "Delegate, delegate, delegate, delegate, and I go have a coffee." You hand off the work, the agent opens a PR, and you stay the one who ships it. Watch it, then read the guide on building loops for your agents below.

• 
  Padma Neelamraju (@PNeelamraju) reported 44 minutes ago

  Open-source supply chain security continued: Additional strengthening measures address build infrastructure and process. Reproducible builds ensure identical outputs from identical inputs regardless of build environment. This requires eliminating contextual information like machine architecture, hostnames, temporary directory names, and timestamps from build outputs. Reproducible builds enable verification across multiple machines. If two independently built binaries match bit-for-bit, either both are correct or both were compromised identically. The latter has lower probability than single-machine compromise. Go distributions are fully reproducible regardless of operating system or processor architecture. Dedicated secured build machines reduce attack surface. Cloud services like Google Cloud Build or GitHub Actions can be locked down more effectively than individual workstations that run browsers and chat applications. Source control and build machines must be secured to ensure what is in source control is what gets built. Engineering workstations still require baseline security to prevent source code modification during development. Process improvements remove unilateral access. Google requires two employees to coordinate for any production code or system change, similar to two-person nuclear launch protocols. For source code, this means author and reviewer. For Go as an open-source project, changes from non-Google authors require two Google employee reviews. Production system access requires two-employee authentication coordination. Monitoring requires software bills of materials: machine-readable dependency lists for all built software. When new attacks are discovered, organizations must quickly identify affected systems and update them. The log4j incident demonstrated the cost of poor monitoring capability.

• 
  Tim Dentry (@Ja4h3ad) reported 49 minutes ago

  Lots of patterns emerge every week seemingly. I like to try them to see how they become force multipliers for me. But in reality, they all seem to distill down to very similar patterns - markdown files, creation of JIRA tickets or Github issues, compression of threads to prevent context rot, etc. I also like reading the code to mitigate comprehension debt.

• 
  Amin Foroutan (@aminfseo) reported 50 minutes ago

  @Kappaemme1926 I tested it. It found 10 GitHub issues and suggested that the people who opened them had the problem my product solves. The issue is that someone who opens a GitHub issue is usually technical enough to solve the problem differently, so they are not necessarily my target customer. The first recommendation was also someone who had built a strong repository that could almost be considered a competitor. On top of that, 6 or 7 of the prospects were users of another open-source repository I own, where I had already solved their problem for free. They had no real reason to buy my paid product. The idea is interesting, but the prospect qualification needs to go much deeper than matching public mentions of a problem.

• 
  Baby Blue Viper (@babyblueviper1) reported 51 minutes ago

  Real convergence on a GitHub issue about approval gates for agent tool calls: engineers kept landing on the same shape independently -- bind approval to a hash of the exact call, one receipt spanning proposed->approved->executed. That's what /review + /ledger already do.

• 
  Swapna Kumar Panda (@swapnakpanda) reported 53 minutes ago

  A recent report says: 85% of engineering students in India don't receive any job offer after graduating. I have visited multiple colleges in recent days. I noticed so many flaws: - Outdated curriculum. First 2 semesters gone in studying Physics, Chemistry, Math, Engineering Drawing. - Students are asked to write code on paper. Memorize the code, DSA. - Faculties have zero skills. You ask anything apart from books. Blank face. - Basic things like ***, GitHub, VS Code are not known to them. - No core sector jobs. All are mad to join IT sector. - IT market has slowed down. Mass layoffs. Less recruitments. - 99% students don't know what internship is. - These students don't build anything on their own. Only copy projects. Clone YouTube. Clone Netflix. Clone Twitter. That's it. - Nobody teaches students how to create an impressive resume. They still write "Playing Cricket" as hobby and "I am adaptable" as their strength in their resume. - Only 0.05% students may have a portfolio site. Most of those are copied from others. No creativity, no information. When the entire system is bankrupt, how do you expect mass recruitments?

• 
  Tanvi (@tanviiiw) reported 59 minutes ago

  More tools ≠ smarter agent. GitHub cut Copilot's built-in toolset from 40 tools to 13, and found the full toolset was actually costing them 2-5 percentage points on SWE-Lancer. Their words: "giving an agent too many tools doesn't always make it smarter. Sometimes it just makes it slower." Speakeasy pushed it further on purpose: 107 tools in one server, and the model started hallucinating endpoints that didn't exist. Trim it to 10-20 well-chosen tools and it got most calls right. It comes down to two things: every tool definition eats context on every single request, and models fuzzy-match on names, so get_status / fetch_status / query_status all blur together and it picks wrong. But we keep connecting everything anyway, because it feels like giving the agent superpowers (I fell for this too). It doesn't. Access isn't capability. You connect more tools to save time, then spend that time babysitting the tool calls. (Of course, none of this replaces a well-scoped prompt. It's upstream of it. You can write a perfect prompt and still lose to a bloated toolset.) So TLDR; curate the toolset like you'd curate a team.