CVE-2025-71362
highPriorität · verfolgen · 0EPSS 0.004 · 37. PerzentilEUUSEPSS · bewertet 2026-10-28
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.
cvss
Technischer Schweregrad, 0–10. Eine Zeile je Quelle.
Basiswert 0–10 · höher = schwerwiegender · Vektor überfahren zum Auflösen⚠ Quellen uneinig · medium–high · 4.9–8.1
SSVC
Eine Handlungsentscheidung — aus Ausnutzung und Auswirkung.
schwächen
Die CWE-Schwächeklassen, zu denen dies gehört.
betroffene Produkte (2)
Betroffene Produkte und Versionsbereiche.
Advisories (1)
Hersteller- und Ökosystem-Meldungen dazu.
- GHSA-r8g5-cgf2-4m4mPicklescan missing detection when calling numpy.f2py.crackfortran.getlincoef2025-12-29ghsa · osvUS
### 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 ```python 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.
auch bekannt als (3)
Weitere Namen und Kennungen dieser Entität.
quellen
Welche Quellen diesen Datensatz belegen und wann.
Referenzen (6)
Externe Belege — Patches, Meldungen, Analysen.
- https://github.com/mmaitre314/picklescan/security/advisories/GHSA-r8g5-cgf2-4m4mcnnvd
- https://www.vulncheck.com/advisories/picklescan-arbitrary-code-execution-via-unsafe-deserialization-in-numpy-f2py-crackfortrancnnvd
- https://github.com/mmaitre314/picklescan/security/advisories/GHSA-r8g5-cgf2-4m4menisa_euvd
- https://www.vulncheck.com/advisories/picklescan-arbitrary-code-execution-via-unsafe-deserialization-in-numpy-f2py-crackfortranenisa_euvd
- https://github.com/mmaitre314/picklescan/security/advisories/GHSA-r8g5-cgf2-4m4mnvd
- https://www.vulncheck.com/advisories/picklescan-arbitrary-code-execution-via-unsafe-deserialization-in-numpy-f2py-crackfortrannvd
Angreifer nutzen Schwachstellen wie diese gegen im Internet exponierte Dienste aus. Sehen Sie mit einem kostenlosen Passiv-Scan, was exponiert ist.
Kostenloser Scan