An unsafe deserialization vulnerability allows an attacker to execute arbitrary code on the host when loading a malicious pickle payload from an untrusted source.

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.

from numpy.f2py.crackfortran import getlincoef

class EvilClass:
  def  reduce (self):
    payload = " import ('os').system('echo "successful attack"')"
    return getlincoef, (payload, [])

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.

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.