flairNLP Flair up to 0.15.1 Clustering clustering.py ClusteringModel.load deserialization
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 6.2 | $0-$5k | 0.35 |
Summary
A vulnerability, which was classified as problematic, has been found in flairNLP Flair up to 0.15.1. This vulnerability affects the function ClusteringModel.load of the file flair/models/clustering.py of the component Clustering. The manipulation leads to deserialization.
This vulnerability is documented as CVE-2026-76843. The attack needs to be performed locally. There is not any exploit available.
Details
A vulnerability, which was classified as problematic, has been found in flairNLP Flair up to 0.15.1. This issue affects the function ClusteringModel.load of the file flair/models/clustering.py of the component Clustering. The manipulation with an unknown input leads to a deserialization vulnerability. Using CWE to declare the problem leads to CWE-502. The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid. Impacted is confidentiality, integrity, and availability. The summary by CVE is:
The official Flair wheels for 0.15.0 and 0.15.1 still contain flair/models/clustering.py, whose ClusteringModel.load static method returns pickle.loads(joblib.load(str(model_file))) and so executes arbitrary Python while loading a model file. Loading a model supplied by an attacker therefore runs that attacker's code with the privileges of the loading process. This is the same sink and the same file as CVE-2024-10073, which records 0.15.0 as the fixed version on the basis that clustering support was dropped in that release; the module was removed from the documented API but remains present in the distributed artifact and reachable by importing flair.models.clustering directly, so the earlier record's fixed version does not hold for the shipped package.
The advisory is shared at github.com. The identification of this vulnerability is CVE-2026-76843 since 08/19/2026. The exploitation is known to be easy. An attack has to be approached locally. It demands that the victim is doing some kind of user interaction. Technical details are known, but no exploit is available.
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
Product
Vendor
Name
Version
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒
CVSSv3
VulDB Meta Base Score: 6.3VulDB Meta Temp Score: 6.2
VulDB Base Score: 4.8
VulDB Temp Score: 4.7
VulDB Vector: 🔒
VulDB Reliability: 🔍
CNA Base Score: 7.8
CNA Vector (VulnCheck): 🔒
CVSSv2
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| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: DeserializationCWE: CWE-502 / CWE-20
CAPEC: 🔒
ATT&CK: 🔒
Physical: Partially
Local: Yes
Remote: Partially
Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔒
Timeline
08/19/2026 CVE reserved08/24/2026 Advisory disclosed
08/24/2026 VulDB entry created
08/24/2026 VulDB entry last update
Sources
Advisory: github.comStatus: Not defined
CVE: CVE-2026-76843 (🔒)
GCVE (CVE): GCVE-0-2026-76843
GCVE (VulDB): GCVE-100-394661
Entry
Created: 08/24/2026 15:28Changes: 08/24/2026 15:28 (76)
Complete: 🔍
Cache ID: 216::103
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
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