PyMemoryEditor

A Python library developed with ctypes to manipulate Windows and Linux processes (32 bits and 64 bits),
reading, writing and searching values in the process memory.

Installing PyMemoryEditor:

pip install PyMemoryEditor

Tkinter application sample:

Type pymemoryeditor at the CLI to run a tkinter app — similar to the Cheat Engine — to scan a process.

Basic Usage:

Import PyMemoryEditor and open a process using the OpenProcess class, passing a window title, process name
or PID as an argument. You can use the context manager for doing it.

from PyMemoryEditor import OpenProcess

with OpenProcess(process_name = "example.exe") as process:
    # Do something...

After that, use the methods read_process_memory and write_process_memory to manipulate the process
memory, passing in the function call the memory address, data type and its size. See the example below:

from PyMemoryEditor import OpenProcess

title = "Window title of an example program"
address = 0x0005000C

with OpenProcess(window_title = title) as process:

    # Getting value from the process memory.
    value = process.read_process_memory(address, int, 4)

    # Writing to the process memory.
    process.write_process_memory(address, int, 4, value + 7)

Getting memory addresses by a target value:

You can look up a value in memory and get the address of all matches, like this:

for address in process.search_by_value(int, 4, target_value):
    print("Found address:", address)

Choosing the comparison method used for scanning:

There are many options to scan the memory. Check all available options in ScanTypesEnum.

The default option is EXACT_VALUE, but you can change it at scan_type parameter:

for address in process.search_by_value(int, 4, target_value, scan_type = ScanTypesEnum.BIGGER_THAN):
    print("Found address:", address)

Note: The scan types EXACT_VALUE and NOT_EXACT_VALUE uses KMP (Knuth–Morris–Pratt) Algorithm, that has completixy O(n + m) — n is the size of the memory page and m is the value length — to speed up the search process. The other scan types use the brute force algorithm, which is O(n * m), so the search may be slower depending on the length of the target value.

You can also search for a value within a range:

for address in process.search_by_value_between(int, 4, min_value, max_value, ...):
    print("Found address:", address)

All methods described above work even for strings, including the method search_by_value_between — however, bytes comparison may work differently than str comparison, depending on the byteorder of your system.

Progress information on searching:

These methods has the progress_information parameter that returns a dictionary containing the search progress information.

for address, info in process.search_by_value(..., progress_information = True):
    template = "Address: 0x{:<10X} | Progress: {:.1f}%"
    progress = info["progress"] * 100
    
    print(template.format(address, progress))

Reading multiple addresses efficiently:

If you have a large number of addresses where their values need to be read from memory, using the search_by_addresses method is much more efficient than reading the value of each address one by one.

for address, value in process.search_by_addresses(int, 4, addresses_list):
    print(f"Address", address, "holds the value", value)

The key advantage of this method is that it reads a memory page just once, obtaining the values of the addresses within the page. This approach reduces the frequency of system calls.

Getting memory regions:

Use the method get_memory_regions() to get the base address, size and more information of all memory regions used by the process.

for memory_region in process.get_memory_regions():
    base_address = memory_region["address"]
    size = memory_region["size"]
    information = memory_region["struct"]