Fickling is a Python pickling decompiler and static analyzer. Fickling versions up to and including 0.1.6 do not treat Python’s runpy module as unsafe. Because of this, a malicious pickle that uses ru
Fickling is a Python pickling decompiler and static analyzer. Fickling versions up to and including 0.1.6 do not treat Python's cProfile module as unsafe. Because of this, a malicious pickle that uses
Fickling is a Python pickling decompiler and static analyzer. Prior to version 0.1.7, the unsafe_imports() method in Fickling's static analyzer fails to flag several high-risk Python modules that can
Fickling is a Python pickling decompiler and static analyzer. Versions prior to 0.1.6 had a bypass caused by `pty` missing from the block list of unsafe module imports. This led to unsafe pickles base
Fickling is a Python pickling decompiler and static analyzer. Versions prior to 0.1.6 are missing `marshal` and `types` from the block list of unsafe module imports. Fickling started blocking both mod
Fickling is a Python pickling decompiler and static analyzer. Prior to version 0.1.7, Fickling is vulnerable to detection bypass due to "builtins" blindness. This issue has been patched in version 0.1
Fickling is a Python pickling decompiler and static analyzer. Prior to version 0.1.7, both ctypes and pydoc modules aren't explicitly blocked. Even other existing pickle scanning tools (like picklesca
The snorkel library thru v0.10.0 contains a critical insecure deserialization vulnerability (CWE-502) in the BaseLabeler.load() method of the BaseLabeler class. The method loads serialized labeler mod
picklescan before 0.0.30 fails to detect malicious pickle files using idlelib.pyshell.ModifiedInterpreter.runcommand in reduce methods. Attackers can embed undetected code in pickle files that execute
A critical deserialization vulnerability exists in the run-llama/llama_index library's JsonPickleSerializer component, affecting versions v0.12.27 through v0.12.40. This vulnerability allows remote co
The imgaug library thru 0.4.0 contains an insecure deserialization vulnerability in its BackgroundAugmenter class within the multicore.py module. The class uses Python's pickle module to deserialize d
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework autom
picklescan before 1.0.1 contains an unsafe deserialization vulnerability allowing unauthenticated users to execute arbitrary code by hiding eval calls nested under callable objects via getattr. Attack
picklescan before 1.0.4 contains an incomplete blocklist for the profile module that fails to block the module-level profile.run() function, allowing attackers to achieve arbitrary code execution via
A Protection Mechanism Failure vulnerability in mmaitre314 picklescan versions up to and including 0.0.30 allows a remote attacker to bypass the unsafe globals check. This is possible because the scan
picklescan before 0.0.30 fails to detect cProfile.runctx function calls in pickle file reduce methods, allowing attackers to execute arbitrary code. Malicious pickle files bypass picklescan detection
picklescan before 0.0.29 fails to detect the profile.Profile.runctx function when analyzing pickle files, allowing attackers to embed undetected malicious code. Remote attackers can craft malicious pi
MooreThreads torch_musa through all versions contains an unsafe deserialization vulnerability in torch_musa.utils.compare_tool. The compare_for_single_op() and nan_inf_track_for_single_op() functions
picklescan before 0.0.28 fails to detect malicious torch.jit.unsupported_tensor_ops.execWrapper function calls embedded in pickle files. Attackers can craft malicious pickle files that bypass picklesc
picklescan before 0.0.33 fails to detect malicious pickle files that invoke numpy.f2py.crackfortran.myeval function through the reduce method. Attackers can craft malicious pickle files embedding arbi
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