How to Crack PRNGs Using Machine Learning on iOS
Pseudo-Random Number Generators (PRNGs) are algorithms that produce sequences of numbers that appear to be random, but are actually determined by a seed value. PRNGs are widely used in cryptography, gaming, simulation and other applications that require randomness. However, not all PRNGs are secure or reliable, and some can be cracked using machine learning techniques.
In this article, we will show you how to crack PRNGs using machine learning on iOS devices. We will use a popular app called Satella, which is a modern in-app purchase cracker that works on iOS 12-16. Satella exploits the weak PRNGs used by some apps to generate receipts for in-app purchases, and allows users to bypass the payment process and get premium features for free.
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We will explain how Satella works, and how you can use it to crack PRNGs on your own iOS device. We will also discuss some of the challenges and limitations of this approach, and how to protect your apps from being cracked by Satella or similar tools.
How Satella Works
Satella is a tweak that hooks into the system frameworks that handle in-app purchases on iOS devices. It intercepts the requests from apps to validate receipts with Apple's servers, and generates fake receipts using a machine learning model that mimics the PRNGs used by the apps. The fake receipts are then sent back to the apps, which accept them as valid and unlock the premium features.
The machine learning model used by Satella is based on the research done by NCC Group, which showed how to crack XORShift128, a simple PRNG algorithm used by Go's math/rand package. XORShift128 produces 32-bit outputs by applying bitwise XOR and shift operations on four 32-bit state variables. The algorithm is deterministic and reversible, meaning that given any four consecutive outputs, it is possible to recover the state variables and predict the next output.
NCC Group used a neural network to model the XORShift128 algorithm, and trained it on a large dataset of random numbers generated by XORShift128 with different seeds. The neural network learned to replicate the XORShift128 sequence with high accuracy without having the seed, using any consecutive four outputs as input. The neural network also learned to reverse the XORShift128 algorithm, and recover the state variables from any four outputs.
Satella uses a similar neural network model to crack PRNGs on iOS devices. However, instead of XORShift128, it targets a different PRNG algorithm used by some iOS apps, called arc4random_uniform. This algorithm is based on RC4, a stream cipher that generates a pseudo-random keystream from a secret key. The keystream is then used to encrypt or decrypt data by applying bitwise XOR operations. arc4random_uniform takes an upper bound as input, and returns a random number between 0 and the upper bound (exclusive) by using RC4 to generate a 32-bit output and discarding any values that exceed the upper bound.
Satella's neural network model takes four consecutive outputs of arc4random_uniform with a fixed upper bound as input, and predicts the next output with high accuracy. It also recovers the RC4 key from the four outputs, and uses it to generate more outputs if needed. Satella uses this model to generate fake receipts for in-app purchases that match the format and structure expected by the apps.
How to Crack PRNGs Using Satella
To crack PRNGs using Satella on your iOS device, you need to follow these steps:
Install Satella from its official repository: https://paisseon.github.io/repo/
Open Satella's settings app and enable it for the apps you want to crack.
Launch the app you want to crack and try to make an in-app purchase.
When prompted, choose \"Satella\" as the payment method.
Wait for Satella to generate a fake receipt and send it back to the app.
Enjoy your premium features for free!
Note that Satella may not work for all apps or all in-app purchases. Some apps may use different PRNG algorithms or additional security measures that prevent Satella from generating valid receipts. 06063cd7f5
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