Skip to main content

Video Walkthrough of the New RedSn0w Jailbreak Tool

As we previously reported, RedSn0w received a massive update with its 0.9.9b1 iteration, released a few days ago.

This latest version of RedSn0w is a huge step in the right direction for the iPhone Dev Team, as it includes features like firmware fetching and caching, auto-detection from DFU mode, and SHSH blob management.

We’re very excited about the future of RedSn0w, but admittedly, all of the new fangled features can be a bit confusing. For this reason, we’ve created a brief video walkthrough that touches on some of the new areas of RedSnow…

[tube]http://www.youtube.com/watch?v=76WW9sinCmU[/tube]

New features aside, if you’re just looking to jailbreak your iOS device, it’s even easier to do so with RedSn0w 0.9.9b1.

No longer do you have to specify an IPSW firmware file, no longer do you have to concern yourself with downloading the right version of RedSn0w that’s compatible with the specific firmware running on your device — including the iOS 5 betas.

As if that wasn’t enough, RedSn0w 0.9.9b1 also includes features from TinyUmbrella, such as the ability to manage SHSH blobs, and to kick your device out of recovery mode.

It seems to me that since Apple is simplifying many features with iOS 5, e.g. delta firmware updates, the Dev Team felt they needed to work on simplifying their flagship jailbreak tool as well.

The result is a much needed upgrade to previous versions of RedSn0w, which will only get better as time goes on. I’m wholeheartedly looking forward to what the Dev Team has in store for us with future upgrades.

Have you tried the RedSn0w 0.9.9b1? If not, you can find it on our downloads page.

Note: This is an untethered jailbreak for all firmwares with untethered jailbreaks available before (4.3.3 and below). Everything else, including iOS 5 betas are tethered only. This version of RedSn0w doesn’t introduce any new untethered jailbreaks, just new features.

https://neveropen.tech/video-walkthrough-of-the-new-redsn0w-jailbreak-tool/?feed_id=103&_unique_id=683d028d00bbb

Comments

Popular posts from this blog

Bare Metal Billing Client Portal Guide

Contents Order a Bare Metal Server My Custom / Contract Pricing View Contract Details Location Management Order History & Status View Order Details Introduction The phoenixNAP Client Portal allows you to purchase bare metal servers and other phoenixNAP products and services. Using the intuitive interface and its essential tools, you can also easily manage your infrastructure. This quick guide will show you how to use the new form to order a bare metal server and how to navigate through new bare metal features within the phoenixNAP Client Portal. Order a Bare Metal Server An order form is an accordion-based process for purchasing phoenixNAP products. Our order form allows you to view the pricing and order multiple products from the same category at the same time. Note: The prices on the form are per month . A contract is not required. However, if you want a contracted price, you may be eligible for a discount depending on the quantity and ...

Add an element in Array to make the bitwise XOR as K

Given an array arr[] containing N positive integers, the task is to add an integer such that the bitwise Xor of the new array becomes K. Examples: Input: arr[] = 1, 4, 5, 6, K = 4 Output: 2 Explanation: Bit-wise XOR of the array is 6.  And bit-wise XOR of 6 and 2 is 4. Input: arr[] = 2, 7, 9, 1, K = 5 Output: 8   Approach: The solution to the problem is based on the following idea of bitwise Xor: If for two numbers X and Y , the bitwise Xor of X and Y is Z then the bitwise Xor of X and Z is Y. Follow the steps to solve the problem: Let the bitwise XOR of the array elements be X .  Say the required value to be added is Y such that X Xor Y = K . From the above observation, it is clear that the value to be added (Y) is the same as X Xor K . Below is the implementation of the above approach: C++ // C++ code to implement the above approach   #include using namespace std;   // Function to find the required value int find_...

Mahotas – Template Matching

In this article we will see how we can do template matching in mahotas. Template is basically a part or structure of image. In this tutorial we will use “lena” image, below is the command to load it.   mahotas.demos.load('lena') Below is the lena image      In order to do this we will use mahotas.template_match method Syntax : mahotas.template_match(img, template) Argument : It takes image object and template as argument Return : It returns image object    Note : Input image should be filtered or should be loaded as grey In order to filter the image we will take the image object which is numpy.ndarray and filter it with the help of indexing, below is the command to do this   image = image[:, :, 0] Below is the implementation    Python3 # importing required libraries import mahotas import mahotas.demos from pylab import gray, imshow, show import numpy as np import matplotlib.pyplot as plt      # loading image ...