LabOne Q: Deserialization of Untrusted Data
CVE-2026-7584 is a high-severity deserialization of untrusted data vulnerability in LabOne Q from Zurich Instruments, with a CVSS 3.1 base score of 7.8 out of 10. It can be exploited with local access to the system by an unauthenticated attacker, but only if a user takes part, for example by opening a link or file. The record lists version 26.1.2 as the first without the flaw, so updating LabOne Q to that release or later removes the exposure. There is no confirmed exploitation so far. EPSS estimates a 0.26% chance of exploitation within 30 days, which is low compared with other CVEs.
High severity with no evidence of exploitation so far.
What to do
- Update LabOne Q to 26.1.2 or a later version.
- Read the advisory on zhinst.com for workarounds and exact fixed builds.
- Because the attack needs a user to take part, warn users about unexpected links and files related to this product until it is patched.
Affected products and versions
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| Zurich Instruments | LabOne Q | 2.41.0 up to, but not including, 26.1.2; 26.4.0b1 through 26.4.0b5 | 26.1.2 |
Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.
How the severity score breaks down
- Attack vector
- LocalThe attacker needs local access or must trick a user into running something.
- Attack complexity
- LowNo special conditions are needed; the attack works reliably.
- Privileges required
- NoneNo account or login is needed.
- User interaction
- RequiredA user must take an action such as opening a file or link.
- Scope
- UnchangedImpact stays within the vulnerable component.
- Confidentiality
- HighAll data handled by the component can be read.
- Integrity
- HighData or code can be modified at will.
- Availability
- HighThe component can be taken down completely.
Vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H. Scored by CNA (ncsc.ch).
| Scoring system | Score | Severity | Scored by |
|---|---|---|---|
| CVSS 4.0 | 8.4 | High | CNA (ncsc.ch) |
| CVSS 3.1 | 7.8 | High | CNA (ncsc.ch) |
Official 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.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Deserialization of Untrusted Data
The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.
How developers prevent this class of flaw
- If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.
- When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.
- Explicitly define a final object() to prevent deserialization.
More Deserialization of Untrusted Data vulnerabilities (CWE-502)
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: none, automatable: no, technical impact: total).
- Record last changed materially (score, affected products, status or references).
References
Recent Deserialization of Untrusted Data vulnerabilities
- 8.4 High severity
- 9.8 Critical severity
- 9.8 Critical severity
- 8.8 High severity
- 9.8 Critical severity
- 8.8 High severity
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