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VulnerabilityPublished

CVE-2026-7584: Zurich Instruments LabOne Q · Deserialization of Untrusted Data

Affects Zurich Instruments LabOne QSource CVE Database V5

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Not known to be exploited · CVSS 7.8 High : upgrade to 26.1.2 soon.

Data as of 29 Oct 2026, 19:04 UTC

CVSS 3.1 base score
7.8High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.2% chance of exploitation in 30 days – higher than 17% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 26.1.2
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 1 May 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponized: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  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

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 29 Oct 2026.

What to do

Upgrade LabOne Q and laboneq to 26.1.2.

Affected software

ProductAffectedFixed in
Zurich InstrumentsLabOne QAffected
  • >=2.41.0 <26.1.2
  • >=26.4.0b1 <=26.4.0b5
Fixed in
  • 26.1.2
PyPIlaboneqpkg:pypi/laboneqOther threatsAffected
  • >=2.41.0 <26.1.2
  • >=26.4.0b1 <=26.4.0b5
Fixed in
  • 26.1.2
PyPIlabone-qpkg:pypi/labone-qOther threatsAffected
  • =2.41.0
  • =26.4.0
Fixed in–

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

AI-suggested

Users should exercise caution when opening experiment files from untrusted or unknown sources to avoid loading malicious serialized data.

Description

The LabOne Q serialization framework uses a class-loading mechanism (import_cls) to dynamically import and instantiate Python classes during deserialization. Prior to the fix, this mechanism accepted arbitrary fully-qualified class names from the serialized data without any validation of the target class or restriction on which modules could be imported. An attacker can craft a serialized experiment file that causes the deserialization engine to import and instantiate arbitrary Python classes with attacker-controlled constructor arguments, resulting in arbitrary code execution in the context of the user running the Python process. Exploitation requires the victim to load a malicious file using LabOne Q's deserialization functions, for example a compromised experiment file shared for collaboration or support purposes.

References

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