Bug 2498355 (CVE-2026-54499)

Summary: CVE-2026-54499 stanza: Stanza: Remote Code Execution via unsafe deserialization in model loaders
Product: [Other] Security Response Reporter: OSIDB Bzimport <bzimport>
Component: vulnerabilityAssignee: Product Security <prodsec-ir-bot>
Status: NEW --- QA Contact:
Severity: high Docs Contact:
Priority: high    
Version: unspecifiedCC: amctagga, aoconnor, bniver, flucifre, gmeno, groman, mbenjamin, mhackett, mwringe, rhel-process-autobot, sostapov, vereddy, watson-tool-maintainers
Target Milestone: ---Keywords: Security
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Hardware: All   
OS: Linux   
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A flaw was found in Stanza, a Stanford NLP Python library. Stanza model loaders, such as stanza.models.common.pretrain.Pretrain.load(), attempt to safely load PyTorch checkpoint files. However, if this safe load fails due to an attacker-controllable pickle.UnpicklingError, the loaders fall back to an unsafe deserialization method. This allows a remote attacker to craft a malicious pretrain or model file that, when loaded by a Stanza NLP pipeline, can execute arbitrary code with the privileges of the affected process, leading to potential credential theft or data exfiltration.
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Description OSIDB Bzimport 2026-07-08 23:02:54 UTC 
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.