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GHSA-r8g5-cgf2-4m4m
No affected components available
Summary
An unsafe deserialization vulnerability allows an attacker to execute arbitrary code on the host when loading a malicious pickle payload from an untrusted source.
Details
The numpy.f2py.crackfortran module exposes many functions that call eval on arbitrary strings of values. This is the case for getlincoef and _eval_length. This list is probably not exhaustive.
According to https://numpy.org/doc/stable/reference/security.html#advice-for-using-numpy-on-untrusted-data, the whole numpy.f2py should be considered unsafe when loading a pickle.
PoC
from numpy.f2py.crackfortran import getlincoef
class EvilClass:
def __reduce__(self):
payload = "__import__('os').system('echo \"successful attack\"')"
return getlincoef, (payload, [])
Impact
Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files from untrusted sources.
What is the impact? Attackers can embed malicious code in pickle file that remains undetected but executes when the pickle file is loaded.
Supply Chain Attack: Attackers can distribute infected pickle files across ML models, APIs, or saved Python objects.
Note
The problem was originally reported to the joblib project, but this was deemed unrelated to joblib itself. However, I checked that picklescan was indeed vulnerable.
The vulnerability can be exploited over the network without needing physical access. It is easy for an attacker to exploit this vulnerability. An attacker does not need any special privileges or access rights. No user interaction is needed for the attacker to exploit this vulnerability.
Exploitation activity has been observed. Apply available patches or mitigations urgently.
The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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