CVE-2026-100843 (GCVE-0-2026-100843)

Vulnerability from cvelistv5 – Published: 2026-09-27 01:28 – Updated: 2026-09-27 01:28
VLAI
Title
MONAI before 1.6.0 Remote Code Execution via algo_from_pickle
Summary
MONAI versions before 1.6.0 contain a remote code execution vulnerability in the algo_from_pickle() function due to unsafe pickle.loads() deserialization in monai/auto3dseg/utils.py. Attackers can craft malicious pickle files that execute arbitrary system commands when deserialized by the vulnerable function.
Severity
8.5 (High)
CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
7.8 (High)
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
CWE
  • CWE-502 - Deserialization of Untrusted Data
Assigner
References
Impacted products
Vendor Product Version CPE status
Project-MONAI MONAI Affected: 0 , < 1.6.0 (semver)
Unaffected: 1.6.0 (semver)
    cpe:2.3:a:project-monai:monai:*:*:*:*:*:*:*:*
Create a notification for this product.
Date Public
2026-06-11 00:00
Credits
aslein1413-sys
Show details on NVD website
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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

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Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



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Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.