PatchFirst · Latest vulnerabilities
The comparison for picklescan 0.0.29 is incomplete. Review the confirmed matches below.
Could not compare 3 records. The results are incomplete.
Vulnerabilities: 33
picklescan before 0.0.34 fails to detect the _operator.methodcaller built-in function when scanning pickle files for malicious code. Attackers can craft malicious pickle payloads using _operator.methodcaller that evade detection and execute arbitrary code when loaded by pickle.load().
picklescan before 0.0.33 fails to detect operator.methodcaller function calls in pickle files, allowing attackers to bypass security checks. Remote attackers can craft malicious pickle payloads using operator.methodcaller that execute arbitrary code when loaded, compromising systems relying on picklescan for validation.
Picklescan before 0.0.33 fails to detect the numpy.f2py.crackfortran.getlincoef gadget in pickle __reduce__ methods, allowing arbitrary code execution. Attackers can craft malicious pickle files that execute arbitrary Python code when loaded, bypassing Picklescan's safety checks and enabling supply-chain poisoning of shared model files.
picklescan before 0.0.34 fails to detect _operator.attrgetter function calls in pickle payloads, allowing attackers to bypass security checks. Remote attackers can craft malicious pickle files using _operator.attrgetter in reduce methods to execute arbitrary code when pickle.load() processes the file.
picklescan before 0.0.30 fails to detect the asyncio.unix_events._UnixSubprocessTransport._start function in pickle reduce methods, allowing remote code execution. Attackers can craft malicious pickle files embedding this built-in function that evade detection but execute arbitrary commands when loaded.
picklescan before 0.0.33 fails to detect unsafe deserialization when numpy.f2py.crackfortran functions call eval on arbitrary strings. Attackers can embed malicious code in pickle files that executes when loaded from untrusted sources.
picklescan before 0.0.33 fails to detect malicious pickle files using numpy.f2py.crackfortran.param_eval function in reduce methods, allowing attackers to bypass security checks. Remote attackers can embed undetected code in pickle files that executes during deserialization, enabling arbitrary code execution in applications loading untrusted pickle data.
picklescan before 0.0.30 fails to detect malicious pickle files that invoke torch.utils.bottleneck.__main__.run_autograd_prof function. Attackers can embed undetected code in pickle files that executes during deserialization, enabling remote code execution.
picklescan before 0.0.30 fails to detect malicious pickle files that exploit lib2to3.pgen2.pgen.ParserGenerator.make_label function in the reduce method. Attackers can craft malicious pickle files with embedded code that evades detection but executes arbitrary commands when pickle.load() is called.
picklescan before 0.0.30 fails to detect malicious pickle files using idlelib.run.Executive.runcode in reduce methods. Attackers can embed undetected code in pickle files that executes during pickle.load, enabling remote code execution in PyTorch models and supply chain attacks.
picklescan before 0.0.30 fails to detect the doctest.debug_script function when analyzing pickle files, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files embedding doctest.debug_script calls that bypass picklescan detection and execute arbitrary commands upon pickle.load invocation.
picklescan before 0.0.30 fails to detect cProfile.run function calls in pickle reduce methods, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files with cProfile.run payloads that bypass picklescan detection and achieve code execution upon deserialization.
picklescan through 0.0.26 fails to detect malicious pickle files that invoke idlelib.pyshell.ModifiedInterpreter.runcode in __reduce__ methods. Attackers can embed undetected code in pickle files that executes arbitrary commands when the file is loaded via pickle.load(), enabling supply chain attacks on PyTorch models and saved Python objects. This is fixed in version 0.0.30.
picklescan before 1.0.4 fails to block at least seven Python standard library modules (including uuid, _osx_support, _aix_support, _pyrepl.pager, and imaplib) exposing eight functions that provide direct arbitrary command execution. Attackers can craft malicious pickle files importing these unblocked modules to achieve remote code execution while bypassing picklescan's safety validation entirely.
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 arbitrary code that evades picklescan detection and executes remote code when loaded.
picklescan before 0.0.30 (affected versions 0.0.26 and earlier) fails to detect the ensurepip._run_pip built-in function when scanning pickle files, allowing attackers to execute arbitrary code. Malicious pickle files embedding ensurepip._run_pip calls in __reduce__ methods bypass picklescan detection and achieve remote code execution upon pickle.load() invocation.
Picklescan before 0.0.33 fails to detect the numpy.f2py.crackfortran._eval_length gadget in pickle __reduce__ methods, allowing arbitrary code execution. Attackers can craft malicious pickle files that execute arbitrary Python code when loaded by victims who trust Picklescan's safety validation.
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 and execute remote code when loaded via pickle.load().
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 executes remote commands when loaded by victims.
picklescan before 1.0.1 contains an unsafe pickle deserialization vulnerability allowing unauthenticated attackers to create arbitrary zero-byte files via logging.FileHandler class instantiation. Attackers can exploit this by crafting malicious pickle payloads to bypass RCE blocklists and create lock files or other filesystem artifacts, potentially causing denial of service or application disruption.
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