@0xAX

Software developer. Obsessed with Linux and and understanding how things work underneath. Learning math. Author of linux-insides. Open to work.

 Kazakhstan / Astana
0xAX.dev
Joined October 2012
  • Tweets8.7K
  • Following189
  • Followers12.7K
290Media
I'm looking for a remote senior or principal backend engineering role. I’m based in GMT+5, with full working-hours overlap with CET. I've spent the past 14 years building distributed systems with Go and Elixir/Erlang. You’re more likely to know me as the author of linux-insides. I'm especially interested in infrastructure, databases, observability, and challenging systems-level problems. If you're looking for an engineer who cares deeply about performance, scalability, reliability, and understanding how things work under the hood, let's connect. My DMs are open, or feel free to reach me directly at [email protected] Reposts are greatly appreciated.
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OpenBSD 8.0 released openbsd.org/80.html
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Leaning Lean 4, note #3: I have always thought of Bool as a type with two possible values: true and false. But I would never thought of it as the number 2
Alex Kuleshov
@0xAXOct 17
Learning Lean 4, note #2: Another one thing about Lean 4 that surprised me is that a function's return type can depend on the value you pass
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Learning Lean 4, note #2: Another one thing about Lean 4 that surprised me is that a function's return type can depend on the value you pass
Alex Kuleshov
@0xAXOct 13
Learning Lean 4, note #1: Everything has a type. Each type has its own type. Mind blowing 🤯
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Did anyone really notice it got faster?
GitHub
@githubOct 16
GitHub.com has fully moved off CSS-in-JS to CSS Modules, resulting in 55% less server-side render time and 25% faster component init. View article

GitHub · Change is constant. GitHub keeps you ahead. · GitHub

Join the world's most widely adopted, AI-powered developer platform where millions of developers, businesses, and the largest open source community build software that advances humanity.

github.com
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We finally got this series out. We tried to simplify Linux kernel exploitation for those interested in getting started. There are plenty of resources out there, but my impression is that they are written for experienced people, not for beginners in this complex field. In this series, we tried to do something close to real-world kernel exploitation, but much simpler, so people can use it as a first contact with Linux kernel exploitation. I hope people like it, and we will be available to help anyone who wants to reproduce all the content.
Allele Security Intelligence
@alleleintelOct 15
Have you ever wanted to get started with Linux kernel exploitation? We wrote a 4-part blog series aimed at newcomers, going from setting up the environment to bypassing SMEP and KASLR. We exploit a real Linux kernel vulnerability step by step, debugging every crash along the way. Introduction to Linux Kernel Exploitation: Vulnerability and Environment – Part 1 allelesecurity.com/intro-lin… Introduction to Linux Kernel Exploitation: Triggering the Vulnerability – Part 2 allelesecurity.com/intro-lin… Introduction to Linux Kernel Exploitation: Exploitation – Part 3 allelesecurity.com/intro-lin… Introduction to Linux Kernel Exploitation: Mitigation Bypass (KASLR and SMEP) – Part 4 allelesecurity.com/intro-lin…

Introduction to Linux Kernel Exploitation: Vulnerability and Environment – Part 1

An online training course titled “Introduction to Linux Kernel Exploitation” was conducted, aimed at beginners without prior experience in kernel vulnerabilities or exploitation. The co…

allelesecurity.com
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Alex Kuleshov retweeted
José A. Alonso@Jose_A_AlonsoOct 15
Lean 4 for mathematicians: a teacher's guide. jaalonso.github.io/calculemu… #LeanProver #ITP #Math

Lean 4 for mathematicians: a teacher's guide | Calculemus

Introduction Who it is for. This guide is aimed at teachers who want to introduce Lean 4 to mathematics students who are used to writing proofs on paper but have no previous programming experience. No

jaalonso.github.io
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The Double Headed Stack Allocator blog.demofox.org/2026/10/03/…

The Double Headed Stack Allocator

When programming high performance applications, such as video games, you learn neat tricks for writing fast code that makes the most of limited resources. Memory allocation is a huge topic for perf…

blog.demofox.org
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A bit more on Emacs + Lean 4 progress: added support for connecting Lean 4 code blocks in org-mode to LSP 🎉
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Source: github.com/0xAX/ob-lean

GitHub - 0xAX/ob-lean: Support for Lean 4 in org-babel

Support for Lean 4 in org-babel. Contribute to 0xAX/ob-lean development by creating an account on GitHub.

github.com
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Arena Allocators in C eliasebner.com/blog/guides/a…

Arena Allocators in C

In this article, I show you a simple yet effective arena allocator implementation in the C programming language. It significantly eases the task of managing memory in such a low level language.

eliasebner.com
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just use lisp
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Learning Lean 4, note #1: Everything has a type. Each type has its own type. Mind blowing 🤯
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Math is solved
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Wild times
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Current state: got latex rendering working inside lean comments in emacs
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Nice book - Calculus with Julia jverzani.github.io/CalculusW…
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one of my favorite osdev streams
Mark
@offlinemarkOct 11
week 139, streaming kernel dev (c++) topic: virtual memory this was just a small refactoring stream - tweaking and refining some of my virtual memory/paging code link + recap ↓
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vibe proving
Steve McCormick
@QuasilocalOct 8
The plot thickens. "We show that the formalised Lean proof does not correspond to the [written paper] proof of blow-up of solutions to the Navier-Stokes equations." arxiv.org/abs/2610.08144

Navier-Stokes lost in translation: Why Lean verification of AI...

Autoformalisation is increasingly used to verify mathematical texts, including those generated by AI, as in OpenAI's announced proof of blow-up of solutions to the Navier-Stokes equations. In this...

arxiv.org
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coding is solved
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Alex Kuleshov retweeted
Sasha Rush
@srush_nlpOct 8
Provably Correct Tensor Puzzles (srush.github.io/jax-lean/) In which we formally verify Python ML code by building a Jax-Lean transpiler.
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