Skip to content

hsiegersma/MarvelRivals-DMA

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

MarvelRivals DMA

A simple, high performance Marvel Rivals DMA cheat utilizing Dear ImGUI for the overlay/menu and DMALibrary for memory reading. It communicates with a Kmbox NET/BPro/MAKCU for aimbot. This project demonstrates how scatter reads and caching can significantly boost speed when using DMA.

Disclaimer: This project is for educational purposes only. It cannot be used out of the box, as all offsets have been stripped. Do not use this to cheat.

🚀 Key Optimizations

  • Scatter reading for almost everything, except for the initial Player Array and Player States.
  • Smart caching: Only reads and caches UWorld, Game Instance, and other rarely changing pointers when necessary.
  • Reduced memory reads: Slower-updating pointers (e.g., Player Array & Player States) are only refreshed every 5 seconds.
  • Batch reads for efficiency: Critical data such as camera and bone values are batched into a single scatter read.
  • Manual memory refreshing using -norefresh.
  • Optimized player reads: Entire Player Array and Bone Array are read in one go instead of scatter reading each pointer in the array, reducing overhead and improving performance.
  • Multithreaded rendering for better performance.

📋 Potential Improvements

  • Pre-emptive reading: Scatter reading the Player State array alongside the Player Array would mean that if the Player Array hasn't changed the Player State array would already be obtained.
  • Dynamic bones: Automatically retrieving the head bone for different characters instead of hardcoding values.

🛠️ Notes

  • Multithreading for organization: The separate threads used for reading are not for performance gains—DMA reads are the bottleneck. Instead, multithreading is used for better cache management and code organization.

Credits:

ImGUI

DMALibrary

MemProcFS

About

Simple example of optimised ESP and Aimbot using Direct Memory Access

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages

  • C++ 88.4%
  • C 11.6%