Harden pickle.load() against deserialization attacks
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| @@ -84,6 +84,7 @@ dependencies = [ | |||
| "black >= 22.6", | |||
| "isort >= 5.10", | |||
| "parameterized ==0.8.1", | |||
| "fickling>=0.1.3,~=0.1.0", | |||
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This package provides analysis of pickled data to help identify potential security vulnerabilities.
License: LGPL-3.0 ✅ Open Source ✅ More facts
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Unsafe Deserialization
DescriptionUnsafe Deserialization (also referred to as Insecure Deserialization) is a vulnerability wherein malformed and untrusted data input is insecurely deserialized by an application. It is exploited to hijack the logic flow of the application end might result in the execution of arbitrary code. Although this isn't exactly a simple attack to employ, it featured in OWASP's Top 10 most recent iteration as part of the Software and Data Integrity Failures risk, due to the severity of impact upon compromise. The process of converting an object state or data structure into a storable or transmissible format is called serialization. Deserialization is its opposite - the process of extracting the serialized data to reconstruct the original object version. Unsafe Deserialization issues arise when an attacker is able to pass ad hoc malicious data into user-supplied data to be deserialized. This could result in arbitrary object injection into the application that might influence the correct target behavior. Read moreImpactA successful Unsafe Deserialization attack can result in the full compromise of the confidentiality, integrity, and availability of the target system, and the oft-cited Equifax breach is probably the best example of the worst outcome that can arise. In Equifax's case, an unsafe Java deserialization attack leveraging the Struts 2 framework resulted in remote code execution, which, in turn, led to the largest data breach in history. PreventionIt is important to consider any development project from an architectural standpoint to determine when and where serialization is necessary. If it is unnecessary, consider using a simpler format when passing data. In cases where it is impossible to forego serialization without disrupting the application's operational integrity, developers can implement a range of defence-in-depth measures to mitigate the chances of being exploited.
Finally, if possible, replace object serialization with data-only serialization formats, such as JSON. TestingVerify that serialization is not used when communicating with untrusted clients. If this is not possible, ensure that adequate integrity controls (and possibly encryption if sensitive data is sent) are enforced to prevent deserialization attacks including object injection.
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Micro-Learning Topic: Deserialization attack (Detected by phrase)Matched on "deserialization attack"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 WarriorHelpful references
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Review changes with SemanticDiff. Analyzed 1 of 2 files. Overall, the semantic diff is 9% smaller than the GitHub diff.
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Overall, a solid improvement in security practices. |
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Potential issues, bugs, and flaws that can introduce unwanted behavior:
Code suggestions and improvements for better exception handling, logic, standardization, and consistency:
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Micro-Learning Topic: Insecure deserialization (Detected by phrase)Matched on "Unsafe Deserialization"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 WarriorHelpful references
Micro-Learning Topic: Template Object Injection (Detected by phrase)Matched on "object injection"Instantiating a template using a user-controlled object is vulnerable to local file read and potential remote code execution. Try a challenge in Secure Code WarriorHelpful references
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![codereviewbot-ai[bot]](https://avatars.githubusercontent.com/in/309638?s=60&v=4){kind=small}
| with open(self.pathfinder_baked_filename, "rb") as fil: | ||
| try: | ||
| mapstr, dist_matrix, pathfinding_routes = pickle.load(fil) | ||
| mapstr, dist_matrix, pathfinding_routes = fickling.load(fil) | ||
| except Exception: | ||
| logger.log_trace() | ||
| if ( |
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The code catches a generic Exception when loading data with fickling.load(fil). Catching generic exceptions can make debugging difficult and may hide other issues. It's better to catch specific exceptions that fickling.load might raise, such as fickling.exceptions.UnpicklingError.
Recommended Solution:
Catch specific exceptions related to the fickling.load function to improve error handling and debugging.
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Please double check the following review of the pull request:Issues counts
Changes in the diff
Identified Issues
Issue 1: 💪Best PracticesExplanation:The Code to Address the Issue:import fickling
def safe_load(file):
try:
data = fickling.load(file)
# Add validation logic here
if not isinstance(data, tuple) or len(data) != 3:
raise ValueError("Invalid data format")
return data
except Exception as e:
logger.log_trace()
raise e
# Usage
with open(self.pathfinder_baked_filename, "rb") as fil:
try:
mapstr, dist_matrix, pathfinding_routes = safe_load(fil)
except Exception:
logger.log_trace()Explanation of the Fix:The Missing TestsTest for
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Issues Summary1. Operation Cancellation ErrorLogs Summary: The operation was canceled during the job execution.Failing Step: The operation was canceled. Related Source Files: None Related Failures: ℹ️ Help(You can turn this bot off by adding a comment/ai off, or force a refresh of this report with /ai ...)
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Hello @D0LLi. The PR is blocked on your approval. Please review it ASAP. |
4 similar comments
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Hello @D0LLi. The PR is blocked on your approval. Please review it ASAP. |
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Hello @D0LLi. The PR is blocked on your approval. Please review it ASAP. |
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Hello @D0LLi. The PR is blocked on your approval. Please review it ASAP. |
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Hello @D0LLi. The PR is blocked on your approval. Please review it ASAP. |
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I'm confident in this change, but I'm not a maintainer of this project. Do you see any reason not to merge it? If this change was not helpful, or you have suggestions for improvements, please let me know! |
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Just a friendly ping to remind you about this change. If there are concerns about it, we'd love to hear about them! |
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Hello @D0LLi. The PR is blocked on your approval. Please review it ASAP. |
1 similar comment
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Hello @D0LLi. The PR is blocked on your approval. Please review it ASAP. |
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This change may not be a priority right now, so I'll close it. If there was something I could have done better, please let me know! You can also customize me to make sure I'm working with you in the way you want. |
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Python's
picklemodule is notoriouly insecure. While it is very useful for serializing and deserializing Python objects, it is not safe to usepickleto load data from untrusted sources. This is becausepicklecan execute arbitrary code when loading data. This can be exploited by an attacker to execute arbitrary code on your system. Unlikeyamlthere is no concept of a "safe" loader inpickle. Therefore, it is recommended to avoidpickleand to use a different serialization format such asjsonoryamlwhen working with untrusted data.However, if you must use
pickleto load data from an untrusted source, we recommend using the open-sourceficklinglibrary.ficklingis a drop-in replacement forpicklethat 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 usepickleto load data from untrusted sources.This codemod replaces calls to
pickle.loadwithfickling.loadin Python code. It also adds an import statement forficklingif it is not already present.The changes look like the following:
Dependency Updates
This codemod relies on an external dependency. We have automatically added this dependency to your project's
pyproject.tomlfile.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, andrequirements.txtfiles. If this change is incorrect, or if you are using another packaging system such aspoetry, it may be necessary for you to manually add the dependency to the proper location in your project.More reading
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