mondain

23.21.150.121:3478
iphone-stun.strato-iphone.de:3478
numb.viagenie.ca:3478
s1.taraba.net:3478
s2.taraba.net:3478
stun.12connect.com:3478
stun.12voip.com:3478
stun.1und1.de:3478
stun.2talk.co.nz:3478
stun.2talk.com:3478

nitred

About

• I faced bandwidth issues between a WG Peer and a WG server. Download bandwidth when downloading from WG Server to WG peer was reduced significantly and upload bandwidth was practically non existent.
• I found a few reddit posts that said that we need to choose the right MTU. So I wrote a script to find an optimal MTU.
• Ideally I would have liked to have run all possible MTU configurations for both WG Server and WG Peer but for simplicity I choose to fix the WG Server to the original 1420 MTU and tried all MTUs from 1280 to 1500 for the WG Peer.

Testing

• On WG server, I started an iperf3 server
• On WG peer, I wrote a script that does the following:
  • wg-quick down wg0
• Edit MTU in the /etc/wireguard/wg0.conf file

TrillCyborg

Mastodon Docker Setup

Setting up

Clone Mastodon's repository.

# Clone mastodon to ~/live directory
git clone https://github.com/tootsuite/mastodon.git live
# Change directory to ~/live

cd ~/live

thesamesam

FAQ on the xz-utils backdoor (CVE-2024-3094)

This is a living document. Everything in this document is made in good faith of being accurate, but like I just said; we don't yet know everything about what's going on.

Background

On March 29th, 2024, a backdoor was discovered in xz-utils, a suite of software that

ZipFile

Retrieving Auth Token

1. Run the command:

   python pixiv_auth.py login

   This will open the browser with Pixiv login page.

touilleMan

#!/usr/bin/env python3
 
"""Simple HTTP Server With Upload.

This module builds on BaseHTTPServer by implementing the standard GET
and HEAD requests in a fairly straightforward manner.

see: https://gist.github.com/UniIsland/3346170
"""
 

sindresorhus

#!/usr/bin/env bash
# MIT © Sindre Sorhus - sindresorhus.com

# git hook to run a command after `git pull` if a specified file was changed
# Run `chmod +x post-merge` to make it executable then put it into `.git/hooks/`.

changed_files="$(git diff-tree -r --name-only --no-commit-id ORIG_HEAD HEAD)"

check_run() {
	echo "$changed_files" | grep --quiet "$1" && eval "$2"

ixs

#!/usr/bin/env python3
#
# Simple Intel x520 EEPROM patcher
# Modifies the EEPROM to unlock the card for non-intel branded SFP modules.
#
# Copyright 2020,2021,2022 Andreas Thienemann <andreas@bawue.net>
#
# Licensed under the GPLv3
#
# Based on research described at https://forums.servethehome.com/index.php?threads/patching-intel-x520-eeprom-to-unlock-all-sfp-transceivers.24634/

klzgrad

调查目的：了解当前各基于TLS的协议方案中ClientHello的指纹独特性。理论背景见 https://arxiv.org/abs/1607.01639 。

指纹数据库：

• https://tlsfingerprint.io
• https://github.com/cisco/mercury

naiveproxy v78.0.3904.70-4

（利益相关：我是这个的作者）

klzgrad

为什么流量可以进行分类

这里的“流量”一般定义为中间人观测到的一组由（时间，方向，包大小）元数据组成的序列 [Cai2014]。其源头是应用层的读写操作，经过传输层协议的变换（分片、协议状态机、加密等），流量序列产生一定变化。但是这种变化非常有限，因为流量的发生过程本质是确定性的，随机因素较小，因此对于特定环境中的特定应用（浏览器访问 google.com）各种流量特征体现出相当大的一致性和独特性，这就使“从流量特征识别应用”的监督学习问题成为可能。虽然有若干不利因素使得确定性下降，例如多层次上软件多版本的排列组合爆炸、有状态的缓存、流水线和连接复用、用户随机行为，但是因为版本的幂律分布、应用层读写操作间的依赖关系、流量特征和检测算法的改进等原因，分类依然具有相当的可行性。

分类的对象：流量应用分类与网站指纹攻击

根据分类的对象产生了两个相近但是不同的研究领域。从流量特征中分类应用类型的被称为流量分类（traffic classification），从流量特征中分类所访问网站或者网页的被称为网站指纹（website fingerprinting）。以机器学习的方法而论前者是比后者更弱但本质相同的一个问题。

这两类攻击的威胁类型不同。流量分类威胁的是可用性，如果GFW检出流量是隧道应用然后进行封锁，则破坏了可用性。而网站指纹威胁的是匿名性和隐私，如果从隐秘流量中检出是谁在访问哪个网站，则破坏了匿名性，丝绸之路就是这样被FBI破获的。