Harden `pickle.load()` against deserialization attacks

pixeebot[bot] commented 1 month ago

Python's pickle module is notoriouly insecure. While it is very useful for serializing and deserializing Python objects, it is not safe to use pickle to load data from untrusted sources. This is because pickle can execute arbitrary code when loading data. This can be exploited by an attacker to execute arbitrary code on your system. Unlike yaml there is no concept of a "safe" loader in pickle. Therefore, it is recommended to avoid pickle and to use a different serialization format such as json or yaml when working with untrusted data.

However, if you must use pickle to load data from an untrusted source, we recommend using the open-source fickling library. fickling is a drop-in replacement for pickle that validates the data before loading it and checks for the possibility of code execution. This makes it much safer (although still not entirely safe) to use pickle to load data from untrusted sources.

This codemod replaces calls to pickle.load with fickling.load in Python code. It also adds an import statement for fickling if it is not already present.

The changes look like the following:

- import pickle
+ import fickling

- data = pickle.load(file)
+ data = fickling.load(file)

Dependency Updates

This codemod relies on an external dependency. We have automatically added this dependency to your project's requirements.txt file.

This package provides analysis of pickled data to help identify potential security vulnerabilities.

There are a number of places where Python project dependencies can be expressed, including setup.py, pyproject.toml, setup.cfg, and requirements.txt files. If this change is incorrect, or if you are using another packaging system such as poetry, it may be necessary for you to manually add the dependency to the proper location in your project.

Micro-Learning Topic: Deserialization attack (Detected by phrase)

Matched on "deserialization attack"

What is this? (2min video)

It is often convenient to serialize objects for communication or to save them for later use. However, serialized data or code can be modified. This malformed data or unexpected data could be used to abuse application logic, deny service, or execute arbitrary code when deserialized. This is usually done with "gadget chains

Try a challenge in Secure Code Warrior

Helpful references

OWASP Deserialization Cheat Sheet - This cheatsheet is focused on providing clear, simple, actionable guidance for preventing deserialization flaws in your applications.
OWASP Deserialization of untrusted data - OWASP community page with comprehensive information about deserialization vulnerabilities, and links to various OWASP resources to help detect or prevent it.
OWASP Top Ten 2017 A8: Insecure Deserialization - OWASP Top Ten articles provide basic techniques to protect against these high risk problem areas, and guidance on where to go next.

performance-testing-bot[bot] commented 1 month ago

Unable to locate .performanceTestingBot config file

code-companion-ai[bot] commented 1 month ago

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codesyncapp[bot] commented 1 month ago

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git-greetings[bot] commented 1 month ago

Thanks @pixeebot[bot] for opening this PR!

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git-greetings[bot] commented 1 month ago

PR Details of @pixeebot[bot] in huawei-noah-xingtian :	OPEN	CLOSED	TOTAL
2	10	12

socket-security[bot] commented 1 month ago

New and removed dependencies detected. Learn more about Socket for GitHub ↗︎

Package	New capabilities	Transitives	Size	Publisher
pypi/setproctitle@0.1	environment, filesystem, shell, unsafe	`0`	29.1 kB	piro

View full report↗︎

2lambda123 / huawei-noah-xingtian