CVE-2025-71344

highPriorität · verfolgen · 0EPSS 0.005 · 40. PerzentilEUUS
grimoire priorityP2 · Scheduled
Exploitable?
—
no known exploitation
Likely / severe?
0.47% (40th) 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 0.0.30 (affected versions 0.0.26 and earlier) fails to detect the ensurepip._run_pip built-in function when scanning pickle files, allowing attackers to execute arbitrary code. Malicious pickle files embedding ensurepip._run_pip calls in __reduce__ methods bypass picklescan detection and achieve remote code execution upon pickle.load() invocation.

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: partialcoordinatorcisa_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-xp4f-hrf8-rxw7Picklescan is missing detection when calling built-in python ensurepip._run_pip2025-08-26ghsa · osvUS

    ### Summary Using ensurepip._run_pip function, which is a built-in python 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 ensurepip._run_pip 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 ``` from ensurepip import _run_pip class EvilEnsurepipRunpip: def __reduce__(self): payload = "[(__import__('os').system('whoami'),)]" return _run_pip, (payload,) ``` ### 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-2026-1792Picklescan is missing detection when calling built-in python ensurepip._run_pip2026-07-07vendor · osvUS

    ### Summary Using ensurepip._run_pip function, which is a built-in python 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 ensurepip._run_pip 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 ``` from ensurepip import _run_pip class EvilEnsurepipRunpip: def __reduce__(self): payload = "[(__import__('os').system('whoami'),)]" return _run_pip, (payload,) ``` ### 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 2026-06-22geändert 2026-06-23
08

Referenzen (6)

Externe Belege — Patches, Meldungen, Analysen.

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