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VulnerabilityPublished

CVE-2026-100846: MONAI before 1.5.2 contains a deserialization of untrusted data vulnerability in the

Source GCVE Database

0
Authoritative record:CVE-2026-100846· High 8.8

Not known to be exploited · CVSS 8.8 High : upgrade to 1.5.2 soon.

Data as of 26 Oct 2026, 13:47 UTC

CVSS 4.0 base score
8.8High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.3% chance of exploitation in 30 days – higher than 29% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 1.5.2
CVSS:4.0/AV:N/AC:H/AT:P/PR:H/UI:P/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H

Exploitation evidence

t = 0 is the CVE’s publication on cve.org

  1. Disclosed: evidence found.

    CVE published 27 Sep 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: evidence found.

    CISA SSVC: proof of concept public

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

Timeline

  1. CVE ID reserved

    by VulnCheck

    , 1 hour before disclosure

  2. CVE published

    on cve.org

    , t = 0

  3. CISA SSVC assessment

    proof of concept public

    , 3 days after disclosure

  4. In Threat Radar

    record ingested

    , 29 days after disclosure

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), CISA SSVC, the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.

What to do

Upgrade MONAI to 1.5.2.

Affected software

ProductAffectedFixed in
Project-MONAIMONAIAffected
  • <1.5.2
Fixed in
  • 1.5.2
PyPIMONAIpkg:pypi/MONAIOther threatsAffected
  • <1.5.2
Fixed in
  • 1.5.2

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

Description

MONAI before 1.5.2 contains a deserialization of untrusted data vulnerability in the algo_from_pickle function in monai/auto3dseg/utils.py. The function reads a .pkl file and passes its contents to pickle.loads without validating the data source or content. If an application invokes algo_from_pickle on an attacker-supplied pickle file, an object defining __reduce__ is executed during deserialization, resulting in arbitrary code execution in the context of the application.

References

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