stanfordnlp Stanza up to 1.12.1 Model Loader Pretrain.load deserialization

CVSS Meta Temp Score
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CTI Interest Score
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6.0$0-$5k0.00

Summaryinfo

A vulnerability was found in stanfordnlp Stanza up to 1.12.1. It has been classified as critical. The affected element is the function Pretrain.load of the component Model Loader. This manipulation causes deserialization. This vulnerability appears as CVE-2026-54499. The attack may be initiated remotely. There is no available exploit.

Detailsinfo

A vulnerability was found in stanfordnlp Stanza up to 1.12.1. It has been declared as critical. Affected by this vulnerability is the function Pretrain.load of the component Model Loader. The manipulation with an unknown input leads to a deserialization vulnerability. The CWE definition for the vulnerability is CWE-502. The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid. As an impact it is known to affect confidentiality, integrity, and availability. The summary by CVE is:

Stanza is a Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages. Prior to 1.12.2, Stanza model loaders such as stanza.models.common.pretrain.Pretrain.load() attempt torch.load(..., weights_only=True) but fall back to torch.load(..., weights_only=False) on attacker-controllable pickle.UnpicklingError, allowing a malicious .pt pretrain or model file to execute arbitrary pickle code when a Stanza NLP pipeline loads it. This issue is fixed in version 1.12.2.

The advisory is shared at github.com. This vulnerability is known as CVE-2026-54499 since 06/15/2026. The exploitation appears to be easy. The attack can be launched remotely. The exploitation doesn't need any form of authentication. It demands that the victim is doing some kind of user interaction. Technical details are known, but no exploit is available.

Upgrading to version 1.12.2 eliminates this vulnerability.

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Productinfo

Vendor

Name

Version

Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 6.3
VulDB Meta Temp Score: 6.0

VulDB Base Score: 6.3
VulDB Temp Score: 6.0
VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv2info

AVACAuCIA
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VectorComplexityAuthenticationConfidentialityIntegrityAvailability
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍

Exploitinginfo

Class: Deserialization
CWE: CWE-502 / CWE-20
CAPEC: 🔒
ATT&CK: 🔒

Physical: No
Local: No
Remote: Yes

Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔒

Upgrade: Stanza 1.12.2

Timelineinfo

06/15/2026 CVE reserved
07/08/2026 +23 days VulDB entry created
07/09/2026 +0 days Advisory disclosed
07/09/2026 +0 days VulDB entry last update

Sourcesinfo

Product: github.com

Advisory: github.com
Status: Confirmed

CVE: CVE-2026-54499 (🔒)
GCVE (CVE): GCVE-0-2026-54499
GCVE (VulDB): GCVE-100-377053

Entryinfo

Created: 07/09/2026 00:45
Changes: 07/09/2026 00:45 (54)
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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