CVE-2025-71370

highPriorität · verfolgen · 0OT-Risiko · erhöhtEPSS 0.005 · 41. PerzentilEUUS
grimoire priorityP2 · Scheduled
Exploitable?
—
no known exploitation
Likely / severe?
0.48% (41st) EPSS
CVSS 8.1 · high
Is it mine?
2 products
Prüfe deine Angriffsfläche
Who says so?
3 sources
cnnvd · enisa_euvd · osv

EPSS · bewertet 2026-10-28

picklescan before 0.0.28 fails to detect malicious torch.jit.unsupported_tensor_ops.execWrapper function calls embedded in pickle files. Attackers can craft malicious pickle files that bypass picklescan detection and execute arbitrary code when loaded via pickle.load().

01

cvss

Technischer Schweregrad, 0–10. Eine Zeile je Quelle.

8.1
010

Basiswert 0–10 · höher = schwerwiegender · Vektor überfahren zum Auflösen⚠ Quellen uneinig · medium–high · 4.9–8.1

v3.18.1highCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:Nsecondary · disclosure@vulncheck.comAusnutzbarkeit 2.8 · Auswirkung 5.2
v3.18.1highCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:Nsecondary · OSV
v4.07.6highCVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:Nsecondary · ENISA EU
v4.07.6highCVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:Xsecondary · disclosure@vulncheck.com
v4.04.9mediumCVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N/E:U/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:Xsecondary · CVSS-BT (t0sche)
02

SSVC

Eine Handlungsentscheidung — aus Ausnutzung und Auswirkung.

Exploitation: poc · Automatable: no · Technical Impact: totalcoordinatorcisa_ssvcUS
03

schwächen

Die CWE-Schwächeklassen, zu denen dies gehört.

04

betroffene Produkte (2)

Betroffene Produkte und Versionsbereiche.

05

Advisories (2)

Hersteller- und Ökosystem-Meldungen dazu.

  • GHSA-vr7h-p6mm-wpmhPicklescan missing detection when calling pytorch function torch.jit.unsupported_tensor_ops.execWrapper2025-08-22ghsa · osvUS

    ### Summary Using torch.jit.unsupported_tensor_ops.execWrapper function, which is a pytorch library function to execute remote pickle file. ### Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to torch.jit.unsupported_tensor_ops.execWrapper function in reduce method Then when the victim after checking whether the pickle file is safe by using Picklescan library and this library doesn't dectect any dangerous functions, decide to pickle.load() this malicious pickle file, thus lead to remote code execution. ### PoC ``` import torch.jit.unsupported_tensor_ops as unsupported_tensor_ops class EvilTorchJitUnsupportedTensorOpsExecWrapper: def __reduce__(self): code = '__import__("os").system("whoami")' glob = {} loc = {} return unsupported_tensor_ops.execWrapper, (code, glob, loc) ``` ### Impact Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. 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. ### Corresponding https://github.com/FredericDT https://github.com/Qhaoduoyu

  • PYSEC-2026-4136Picklescan missing detection when calling pytorch function torch.jit.unsupported_tensor_ops.execWrapper2026-10-01vendor · osvUS

    ### Summary Using torch.jit.unsupported_tensor_ops.execWrapper function, which is a pytorch library function to execute remote pickle file. ### Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to torch.jit.unsupported_tensor_ops.execWrapper function in reduce method Then when the victim after checking whether the pickle file is safe by using Picklescan library and this library doesn't dectect any dangerous functions, decide to pickle.load() this malicious pickle file, thus lead to remote code execution. ### PoC ``` import torch.jit.unsupported_tensor_ops as unsupported_tensor_ops class EvilTorchJitUnsupportedTensorOpsExecWrapper: def __reduce__(self): code = '__import__("os").system("whoami")' glob = {} loc = {} return unsupported_tensor_ops.execWrapper, (code, glob, loc) ``` ### Impact Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. 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. ### Corresponding https://github.com/FredericDT https://github.com/Qhaoduoyu

06

auch bekannt als (5)

Weitere Namen und Kennungen dieser Entität.

07

quellen

Welche Quellen diesen Datensatz belegen und wann.

veröffentlicht 2026-06-23geändert 2026-06-23
08

Referenzen (6)

Externe Belege — Patches, Meldungen, Analysen.

scry

Angreifer nutzen Schwachstellen wie diese gegen im Internet exponierte Dienste aus. Sehen Sie mit einem kostenlosen Passiv-Scan, was exponiert ist.

Kostenloser Scan