# zeroize
[](https://badge.fury.io/py/zeroize)
[](https://github.com/radumarias/zeroize-python/actions/workflows/CI.yml)
Securely clear secrets from memory. Built on stable Rust primitives which guarantee memory is zeroed using an operation will not be 'optimized away' by the compiler.
It uses [zeroize](https://crates.io/crates/zeroize) crate under the hood to zeroize and [memsec](https://crates.io/crates/memsec) for `mlock()` and `munlock()`. **Maximum you can mlock is 2662 KB**.
It can work with `bytearray` and `numpy array`.
> [!WARNING]
> **In the case of [Copy-on-write fork](https://en.wikipedia.org/wiki/Copy-on-write) you need to zeroize the memory before forking the child process, see example below.
> Also by itself it doesn't work if memory is moved or moved to swap. You can use `zeroize.mlock()` to lock the memory, see example below.**
# Caveats of `mlock()`
`mlock` works on pages, so two variables could reside in the same page and if you `munlock` one it will `munlock` the whole page and also the memory for the other variable.
Ideally you could `munlock` all your vars at same time so it would not be affected by the overlap. One strategy could be to expire your vars that store credentials when not used and to reload them again when needed. Like that you could `mlock` when you load them and `munlock` on expire and keep all vars under the same expire policy. Like this all var will be `munlock`ed at the same time.
# Examples
**On Windows you can mlock up to 128 KB by default. If you need more you need to first call `SetProcessWorkingSetSize` to increase the `dwMinimumWorkingSetSize`. Will have an example below.**
## Lock and zeroize memory
```python
from zeroize import zeroize1, mlock, munlock
import numpy as np
if __name__ == "__main__":
try:
print("allocate memory")
# regular array
# Maximum you can mlock is 2662 KB
arr = bytearray(b"1234567890")
# numpy array
# Maximum you can mlock is 2662 KB
arr_np = np.array([0] * 10, dtype=np.uint8)
arr_np[:] = arr
assert arr_np.tobytes() == b"1234567890"
print("locking memory")
mlock(arr)
mlock(arr_np)
print("zeroize'ing...: ")
zeroize1(arr)
zeroize1(arr_np)
print("checking if is zeroized")
assert arr == bytearray(b"\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00")
assert all(arr_np == 0)
print("all good, bye!")
finally:
# Unlock the memory
print("unlocking memory")
munlock(arr)
munlock(arr_np)
```
## Zeroing memory before forking child process
This mitigates the problems that appears on [Copy-on-write fork](https://en.wikipedia.org/wiki/Copy-on-write). You need to zeroize the data before forking the child process.
```python
import os
from zeroize import zeroize1, mlock, munlock
if __name__ == "__main__":
try:
# Maximum you can mlock is 2662 KB
sensitive_data = bytearray(b"Sensitive Information")
mlock(sensitive_data)
print("Before zeroization:", sensitive_data)
zeroize1(sensitive_data)
print("After zeroization:", sensitive_data)
# Forking after zeroization to ensure no sensitive data is copied
pid = os.fork()
if pid == 0:
# This is the child process
print("Child process memory after fork:", sensitive_data)
else:
# This is the parent process
os.wait() # Wait for the child process to exit
print("all good, bye!")
finally:
# Unlock the memory
print("unlocking memory")
munlock(sensitive_data)
```
# Locking more than 128 KB
On Windows if you need to `mlock` more than `128 KB` you need to first call `SetProcessWorkingSetSize` to increase the `dwMinimumWorkingSetSize`.
Here is an example, set `min_size` to the size you want to `mlock` + some overhead.
```python
import platform
def setup_memory_limit():
if not platform.system() == "Windows":
return
import ctypes
from ctypes import wintypes
# Define the Windows API functions
kernel32 = ctypes.WinDLL('kernel32', use_last_error=True)
GetCurrentProcess = kernel32.GetCurrentProcess
GetCurrentProcess.restype = wintypes.HANDLE
SetProcessWorkingSetSize = kernel32.SetProcessWorkingSetSize
SetProcessWorkingSetSize.restype = wintypes.BOOL
SetProcessWorkingSetSize.argtypes = [wintypes.HANDLE, ctypes.c_size_t, ctypes.c_size_t]
# Get the handle of the current process
current_process = GetCurrentProcess()
# Set the working set size
min_size = 6 * 1024 * 1024 # Minimum working set size
max_size = 10 * 1024 * 1024 # Maximum working set size
result = SetProcessWorkingSetSize(current_process, min_size, max_size)
if not result:
error_code = ctypes.get_last_error()
error_message = ctypes.FormatError(error_code)
raise RuntimeError(f"SetProcessWorkingSetSize failed with error code {error_code}: {error_message}")
# Call this before you mlock
setup_memory_limit()
```
# Build from source
## Browser
[](https://gitpod.io/#https://github.com/radumarias/zeroize-python)
[](https://github.com/codespaces/new/?repo=radumarias%2Fzeroize-python&ref=main)
## Geting sources from GitHub
Skip this if you're starting it in browser.
```bash
git clone https://github.com/radumarias/zeroize-python && cd zeroize-python
```
## Compile and run
```bash
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
```
To configure your current shell, you need to source
the corresponding env file under $HOME/.cargo.
This is usually done by running one of the following (note the leading DOT):
```bash
. "$HOME/.cargo/env"
```
```bash
python -m venv .env
source .env/bin/activate
pip install -r requirements.txt
maturin develop
pytest
python examples/lock_and_zeroize.py
python examples/zeroize_before_fork.py
python examples/mlock.py
```
# Contribute
Feel free to fork it, change and use it in any way that you want.
If you build something interesting and feel like sharing pull requests are always appreciated.
## How to contribute
Please see [CONTRIBUTING.md](CONTRIBUTING.md).
Raw data
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"description": "# zeroize\n\n[](https://badge.fury.io/py/zeroize)\n[](https://github.com/radumarias/zeroize-python/actions/workflows/CI.yml)\n\nSecurely clear secrets from memory. Built on stable Rust primitives which guarantee memory is zeroed using an operation will not be 'optimized away' by the compiler.\n\nIt uses [zeroize](https://crates.io/crates/zeroize) crate under the hood to zeroize and [memsec](https://crates.io/crates/memsec) for `mlock()` and `munlock()`. **Maximum you can mlock is 2662 KB**. \nIt can work with `bytearray` and `numpy array`.\n\n> [!WARNING] \n> **In the case of [Copy-on-write fork](https://en.wikipedia.org/wiki/Copy-on-write) you need to zeroize the memory before forking the child process, see example below. \n> Also by itself it doesn't work if memory is moved or moved to swap. You can use `zeroize.mlock()` to lock the memory, see example below.**\n\n# Caveats of `mlock()`\n\n`mlock` works on pages, so two variables could reside in the same page and if you `munlock` one it will `munlock` the whole page and also the memory for the other variable.\n Ideally you could `munlock` all your vars at same time so it would not be affected by the overlap. One strategy could be to expire your vars that store credentials when not used and to reload them again when needed. Like that you could `mlock` when you load them and `munlock` on expire and keep all vars under the same expire policy. Like this all var will be `munlock`ed at the same time.\n\n# Examples\n\n**On Windows you can mlock up to 128 KB by default. If you need more you need to first call `SetProcessWorkingSetSize` to increase the `dwMinimumWorkingSetSize`. Will have an example below.**\n\n## Lock and zeroize memory\n\n```python\nfrom zeroize import zeroize1, mlock, munlock\nimport numpy as np\n\n\nif __name__ == \"__main__\":\n try:\n print(\"allocate memory\")\n\n # regular array\n # Maximum you can mlock is 2662 KB\n arr = bytearray(b\"1234567890\")\n\n # numpy array\n # Maximum you can mlock is 2662 KB\n arr_np = np.array([0] * 10, dtype=np.uint8)\n arr_np[:] = arr\n assert arr_np.tobytes() == b\"1234567890\"\n\n print(\"locking memory\")\n\n mlock(arr)\n mlock(arr_np)\n\n print(\"zeroize'ing...: \")\n zeroize1(arr)\n zeroize1(arr_np)\n\n print(\"checking if is zeroized\")\n assert arr == bytearray(b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\")\n assert all(arr_np == 0)\n\n print(\"all good, bye!\")\n\n finally:\n # Unlock the memory\n print(\"unlocking memory\")\n munlock(arr)\n munlock(arr_np)\n```\n\n## Zeroing memory before forking child process\n\nThis mitigates the problems that appears on [Copy-on-write fork](https://en.wikipedia.org/wiki/Copy-on-write). You need to zeroize the data before forking the child process.\n\n```python\nimport os\nfrom zeroize import zeroize1, mlock, munlock\n\n\nif __name__ == \"__main__\":\n try:\n # Maximum you can mlock is 2662 KB\n sensitive_data = bytearray(b\"Sensitive Information\")\n mlock(sensitive_data)\n\n print(\"Before zeroization:\", sensitive_data)\n\n zeroize1(sensitive_data)\n print(\"After zeroization:\", sensitive_data)\n\n # Forking after zeroization to ensure no sensitive data is copied\n pid = os.fork()\n if pid == 0:\n # This is the child process\n print(\"Child process memory after fork:\", sensitive_data)\n else:\n # This is the parent process\n os.wait() # Wait for the child process to exit\n \n print(\"all good, bye!\")\n\n finally:\n # Unlock the memory\n print(\"unlocking memory\")\n munlock(sensitive_data)\n```\n\n# Locking more than 128 KB\n\nOn Windows if you need to `mlock` more than `128 KB` you need to first call `SetProcessWorkingSetSize` to increase the `dwMinimumWorkingSetSize`.\n\nHere is an example, set `min_size` to the size you want to `mlock` + some overhead.\n\n```python\nimport platform\n\n\ndef setup_memory_limit():\n if not platform.system() == \"Windows\":\n return\n\n import ctypes\n from ctypes import wintypes\n\n # Define the Windows API functions\n kernel32 = ctypes.WinDLL('kernel32', use_last_error=True)\n\n GetCurrentProcess = kernel32.GetCurrentProcess\n GetCurrentProcess.restype = wintypes.HANDLE\n\n SetProcessWorkingSetSize = kernel32.SetProcessWorkingSetSize\n SetProcessWorkingSetSize.restype = wintypes.BOOL\n SetProcessWorkingSetSize.argtypes = [wintypes.HANDLE, ctypes.c_size_t, ctypes.c_size_t]\n\n # Get the handle of the current process\n current_process = GetCurrentProcess()\n\n # Set the working set size\n min_size = 6 * 1024 * 1024 # Minimum working set size\n max_size = 10 * 1024 * 1024 # Maximum working set size\n\n result = SetProcessWorkingSetSize(current_process, min_size, max_size)\n\n if not result:\n error_code = ctypes.get_last_error()\n error_message = ctypes.FormatError(error_code)\n raise RuntimeError(f\"SetProcessWorkingSetSize failed with error code {error_code}: {error_message}\")\n\n# Call this before you mlock\nsetup_memory_limit()\n```\n\n# Build from source\n\n## Browser\n\n[](https://gitpod.io/#https://github.com/radumarias/zeroize-python)\n\n[](https://github.com/codespaces/new/?repo=radumarias%2Fzeroize-python&ref=main)\n\n## Geting sources from GitHub\n\nSkip this if you're starting it in browser.\n\n```bash\ngit clone https://github.com/radumarias/zeroize-python && cd zeroize-python\n```\n\n## Compile and run\n\n```bash\ncurl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh\n```\n\nTo configure your current shell, you need to source\nthe corresponding env file under $HOME/.cargo.\nThis is usually done by running one of the following (note the leading DOT):\n\n```bash\n. \"$HOME/.cargo/env\"\n```\n\n```bash\npython -m venv .env\nsource .env/bin/activate\npip install -r requirements.txt\nmaturin develop\npytest\npython examples/lock_and_zeroize.py\npython examples/zeroize_before_fork.py\npython examples/mlock.py\n```\n\n# Contribute\n\nFeel free to fork it, change and use it in any way that you want.\nIf you build something interesting and feel like sharing pull requests are always appreciated.\n\n## How to contribute\n\nPlease see [CONTRIBUTING.md](CONTRIBUTING.md).\n\n",
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