Picklescan uses numpy.f2py.crackfortran.myeval, which is a function in numpy to execute remote pickle files.
The attack payload executes in the following steps:
class RCE:
def __reduce__(self):
from numpy.f2py.crackfortran import myeval
return (myeval, ("os.system('ls')",))
Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. Attackers can embed malicious code in pickle file that remains undetected but executes when the pickle file is loaded. Attackers can distribute infected pickle files across ML models, APIs, or saved Python objects.
Pinji Chen (cpj24@mails.tsinghua.edu.cn) from the NISL lab (https://netsec.ccert.edu.cn/about) at Tsinghua University, Guanheng Liu (coolwind326@gmail.com).
{
"nvd_published_at": null,
"cwe_ids": [
"CWE-94"
],
"severity": "HIGH",
"github_reviewed": true,
"github_reviewed_at": "2025-12-29T20:04:09Z"
}