HighVulnerability

CVE-2026-54499: Stanza model loaders arbitrary code execution via malicious pickle files

Source: NVD(opens in a new tab)
Identifier: CVE-2026-54499
Published: July 8, 2026
Record updated: October 9, 2026

Affected: stanza <= 1.12.1
Fixed in: 1.12.2
Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.5%

Summary

CVE-2026-54499 affects Stanza, the Stanford NLP Python library, before version 1.12.2. Model loaders such as stanza.models.common.pretrain.Pretrain.load() call torch.load(..., weights_only=True) but fall back to torch.load(..., weights_only=False) when a pickle.UnpicklingError is raised. An attacker-controlled malicious .pt pretrain or model file can therefore execute arbitrary pickle code when a Stanza NLP pipeline loads it.

Mitigation

Fixed in 1.12.2.

Details

Scores and exploitation

CVSS score: 7.5(high)
Patch available: Yes
CVSS vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H
Attack vector: network
Attack complexity: high
Privileges required: none
User interaction: required
EPSS: 0.5%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on October 13, 2026.
Disclosure date: July 8, 2026

Weaknesses and techniques

Weakness (CWE): CWE-502
CWE-676
Attack pattern (CAPEC): CAPEC-586
AI threat technique (MITRE ATLAS): AML.T0010

Affected

Packages: stanza@<= 1.12.1 (fixed: 1.12.2)

Classification

Attack type: Supply chain
Attack sophistication: Moderate
AI component targeted: Model
Impact: Confidentiality,
Integrity,
Safety
Labels: security

How this record was produced

Summaries, mitigations and labels on this page are generated automatically from the source. The linked source is authoritative. The source gives this advisory a description and no title, so the title above is a headline generated from the source text.

Original source: https://nvd.nist.gov/vuln/detail/CVE-2026-54499

First tracked: July 8, 2026 at 08:07 PM ET, from NVD/CVE Database

Classifier: claude-haiku-5-5, prompt v4

Classifier confidence: 90% (self-assessed)

Affected packages in the Exposure Registry

Matched by package name and ecosystem. Each entry shows whether the package delegates to a language model and how many tracked packages depend on it.

stanzaPyPILLM dependency since 2022-04-23 · 4 tracked dependents

Topics

Model and package supply chain

Summary

Mitigation

Affected packages in the Exposure Registry

Topics

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