Python Script to disable ASLR and make nv fatbins read-only to reduce memory commit

fixNvPe.py

# Simple script to disable ASLR and make .nv_fatb sections read-only
# Requires: pefile  ( python -m pip install pefile )
# Usage:  fixNvPe.py --input path/to/*.dll

import argparse
import pefile
import glob
import os
import shutil

def main(args):
    failures = []
    for file in glob.glob( args.input, recursive=args.recursive ):
        print(f"\n---\nChecking {file}...")
        pe = pefile.PE(file, fast_load=True)
        nvbSect = [ section for section in pe.sections if section.Name.decode().startswith(".nv_fatb")]
        if len(nvbSect) == 1:
            sect = nvbSect[0]
            size = sect.Misc_VirtualSize
            aslr = pe.OPTIONAL_HEADER.IMAGE_DLLCHARACTERISTICS_DYNAMIC_BASE
            writable = 0 != ( sect.Characteristics & pefile.SECTION_CHARACTERISTICS['IMAGE_SCN_MEM_WRITE'] )
            print(f"Found NV FatBin! Size: {size/1024/1024:0.2f}MB  ASLR: {aslr}  Writable: {writable}")
            if (writable or aslr) and size > 0:
                print("- Modifying DLL")
                if args.backup:
                    bakFile = f"{file}_bak"
                    print(f"- Backing up [{file}] -> [{bakFile}]")
                    if os.path.exists( bakFile ):
                        print( f"- Warning: Backup file already exists ({bakFile}), not modifying file! Delete the 'bak' to allow modification")
                        failures.append( file )
                        continue
                    try:
                        shutil.copy2( file, bakFile)
                    except Exception as e:
                        print( f"- Failed to create backup! [{str(e)}], not modifying file!")
                        failures.append( file )
                        continue
                # Disable ASLR for DLL, and disable writing for section
                pe.OPTIONAL_HEADER.DllCharacteristics &= ~pefile.DLL_CHARACTERISTICS['IMAGE_DLLCHARACTERISTICS_DYNAMIC_BASE']
                sect.Characteristics = sect.Characteristics & ~pefile.SECTION_CHARACTERISTICS['IMAGE_SCN_MEM_WRITE']
                try:
                    newFile = f"{file}_mod"
                    print( f"- Writing modified DLL to [{newFile}]")
                    pe.write( newFile )
                    pe.close()
                    print( f"- Moving modified DLL to [{file}]")
                    os.remove( file )
                    shutil.move( newFile, file )
                except Exception as e:
                    print( f"- Failed to write modified DLL! [{str(e)}]")
                    failures.append( file )
                    continue

    print("\n\nDone!")
    if len(failures) > 0:
        print("***WARNING**** These files needed modification but failed: ")
        for failure in failures:
            print( f" - {failure}")







def parseArgs():
    parser = argparse.ArgumentParser( description="Disable ASLR and make .nv_fatb sections read-only", formatter_class=argparse.ArgumentDefaultsHelpFormatter )
    parser.add_argument('--input', help="Glob to parse", default="*.dll")
    parser.add_argument('--backup', help="Backup modified files", default=True, required=False)
    parser.add_argument('--recursive', '-r', default=False, action='store_true', help="Recurse into subdirectories")

    return parser.parse_args()


###############################
# program entry point
#
if __name__ == "__main__":
    args = parseArgs()
    main( args )

@szan12 For it to be getting 'access denied' in your User directory, I would assume that it means the file is in use. Try restarting your computer and then running it, or try typing "taskkill /f /im python.exe" in your command prompt before running it (this will forcefully close any python process you have running). If that still fails, try running from a cmd prompt that is "Run as administrator", but that shouldn't be necessary in the 'user' directory

i can't remove the folder's read-only attributes, when i removed, and it just automatically recovery the attributes.

Thank you for sharing codes and troubleshooting. Yet, this didn't work for me. I am surprised I can't train a FCN8s on NVIDIA 3090 with 24 Gb of VRAM. I could have done that in an older server with two 12 Gb cards. The main difference is that the old server ran Keras on linux. So I'll have to change OS and maybe go back to keras/TF.

Best regards!