Skip to main content

A Python library for memory manipulation, code injection and function hooking

Project description

PyJectify logo

PyJectify

A Python library for memory manipulation, code injection and function hooking.

Quick start

PyJectify is available on PyPI.

Alternatively, you can download releases from GitHub or clone the project.

Documentation is available at https://petitoto.github.io/pyjectify/

Features

Windows (x86 & x86_64)

Core

  • Allocate / Free / Read / Write memory
  • Create threads
  • List loaded modules
  • PE parser
  • Use kernel32 or ntdll functions

Modules

  • MemScan: scan memory using regex patterns
  • Inject: load library, from disk (remote LoadLibrary) or from memory (fully map the DLL into the remote process)
  • Hook: set up inline hooks in the target process
  • PythonLib: embed python into a remote process

Utils

  • Syscall: parse syscall codes from ntdll.dll (from the loaded library or from the disk), and produce a ntdll-like object which can be used by the core to use direct syscalls
  • ApiSetSchema: parse Windows ApiSet

Examples

Memory search & basic operations

import pyjectify

# Open notepad process (only the first found if multiple instances of notepad are running)
notepad = pyjectify.byName('Notepad.exe')[0]

# Use the pattern "secret( is)?: (.){10}", but encoded in utf-16-le because Notepad uses wchar_t
words = ['secret', ' is', ': ', '.']
pattern = b'%b(%b)?%b(%b){10}' % tuple(e.encode('utf-16-le') for e in words)

# Search for the secret in notepad's memory
addrs = notepad.memscan.scan(pattern)

# Process found addresses
for addr in addrs:
    secret = notepad.process.read(addr, 50).decode('utf-16-le')
    print('[+] Found secret:', secret)
    notepad.process.write(addr, ('*'*len(secret)).encode('utf-16-le')) # let's hide the secret!

# Reset memscan to perform a new search regardless of the previous scan
notepad.memscan.reset()

Python code injection

import pyjectify

# Open notepad process
notepad = pyjectify.byName('Notepad.exe')[0]

# Inject Python DLL
notepad.pythonlib.python_mod = notepad.inject.load_library("C:\\path\\to\\python-embed\\python311.dll")

# Run some Python code from notepad
notepad.pythonlib.initialize()
notepad.pythonlib.exec('import os; os.system("calc.exe")')

# Undo all initializations
notepad.pythonlib.finalize()

Setup an inline hook written in Python

import pyjectify

# Open notepad process & inject Python DLL
notepad = pyjectify.byName('Notepad.exe')[0]
notepad.pythonlib.python_mod = notepad.inject.load_library("C:\\path\\to\\python-embed\\python311.dll")
notepad.pythonlib.initialize()

# Let's hook GetClipboardData!
# Step 1: define our new function
pycode = """
import ctypes
def GetClipboardData(uFormat:ctypes.c_uint) -> ctypes.c_void_p:
  ctypes.windll.user32.MessageBoxW(0, "I hooked you :D", "MyNewGetClipboardData", 0)
  return o_GetClipboardData(uFormat)
"""
notepad.pythonlib.exec(pycode)

# Step 2: get original function address and setup a trampoline (of 15 bytes size)
user32 = notepad.process.get_module('user32.dll')
oaddr = user32.exports['GetClipboardData'] + user32.base_addr
trampoline_addr = notepad.hook.trampoline(oaddr, 15)

# Step 3: prepare Python function hooking, ie create o_GetClipboardData and get ou Python GetClipboardData address
hook_addr = notepad.pythonlib.prepare_hook('GetClipboardData', trampoline_addr)

# Step 4: inline hook
notepad.hook.inline(oaddr, hook_addr)

Advanced DLL injection

import pyjectify

# Open processes
proc1 = pyjectify.byName('proc1.exe')[0]
proc2 = pyjectify.byName('proc2.exe')[0]

# Extract a library from proc1's memory
module = proc1.process.get_module('module.dll')

# Extract common syscalls from ntdll.dll and wrap them into a ntdll-like object
syscall = pyjectify.windows.Syscall()
syscall.get_common(from_disk=True)

# Use direct syscalls to operate on proc2 (memory read / write / protect, thread creation...)
proc2.process.ntdll = syscall

# Inject the module directly from memory into proc2, at a random location and without PE headers
proc2.inject.memory_loader(module, prefer_base_addr=False, copy_headers=False)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyjectify-0.7.tar.gz (22.7 kB view details)

Uploaded Source

Built Distribution

pyjectify-0.7-py3-none-any.whl (25.6 kB view details)

Uploaded Python 3

File details

Details for the file pyjectify-0.7.tar.gz.

File metadata

  • Download URL: pyjectify-0.7.tar.gz
  • Upload date:
  • Size: 22.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.0.0 CPython/3.12.3

File hashes

Hashes for pyjectify-0.7.tar.gz
Algorithm Hash digest
SHA256 32ff14cdbc24ffd9ce067bd04c056350d1d9a08f5e8331a18eb098f9ec7a6e59
MD5 139080684603dcbf6bbcd95a190c5ee0
BLAKE2b-256 04e53c40bb71b305046e66c56fb9187d17169cc3f6cb89419c0266506b9929da

See more details on using hashes here.

File details

Details for the file pyjectify-0.7-py3-none-any.whl.

File metadata

  • Download URL: pyjectify-0.7-py3-none-any.whl
  • Upload date:
  • Size: 25.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.0.0 CPython/3.12.3

File hashes

Hashes for pyjectify-0.7-py3-none-any.whl
Algorithm Hash digest
SHA256 122b9ef376ef43dcb7f9ecf751d024e4482a6f00b7f874f09f75281bd26216c0
MD5 21f832de46b75a57bf54d732a6d13c67
BLAKE2b-256 f8b80d98cb9ab0ce48e4013e7327425ce32e18c8ceb6ed908a9fd6520195d283

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page