CVE-2026-54499
Description
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.
Statement
An unsafe deserialization vulnerability in the Stanza Python library can lead to remote code execution. A malicious model pretrain file from an untrusted or compromised source can trigger an insecure deserialization fallback during model loading, resulting in arbitrary code execution with the privileges of the affected process.
Mitigation
To mitigate this vulnerability, ensure that Stanza model pretrain files are exclusively sourced from trusted repositories and locations. Avoid loading model files from untrusted or unverified sources, as this could lead to the execution of arbitrary code. Implement strict access controls on directories where Stanza models are stored to prevent the introduction of malicious files.
Common Vulnerability Scoring System (CVSS) Score Details
Info alert:Important note
CVSS scores for open source components depend on vendor-specific factors (e.g. version or build chain). Therefore, Red Hat's score and impact rating can be different from NVD and other vendors. Red Hat remains the authoritative CVE Naming Authority (CNA) source for its products and services (see Red Hat classifications).
The following CVSS metrics and score provided are preliminary and subject to review.
CVSS v3 Score Breakdown
| Red Hat | NVD | cve.org | |
|---|---|---|---|
| Base Score | 7.5 | N/A | 7.5 |
| Attack Vector | Network | N/A | Network |
| Attack Complexity | High | N/A | High |
| Privileges Required | None | N/A | None |
| User Interaction | Required | N/A | Required |
| Scope | Unchanged | N/A | Unchanged |
| Confidentiality | High | N/A | High |
| Integrity Impact | High | N/A | High |
| Availability Impact | High | N/A | High |
Vector
Red Hat: CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H
cve.org: CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H
Understanding the Weakness (CWE)
Integrity
Technical Impact: Modify Application Data; Unexpected State
Attackers can modify unexpected objects or data that was assumed to be safe from modification. Deserialized data or code could be modified without using the provided accessor functions, or unexpected functions could be invoked.
Availability
Technical Impact: DoS: Resource Consumption (CPU)
If a function is making an assumption on when to terminate, based on a sentry in a string, it could easily never terminate.
Other
Technical Impact: Varies by Context
The consequences can vary widely, because it depends on which objects or methods are being deserialized, and how they are used. Making an assumption that the code in the deserialized object is valid is dangerous and can enable exploitation. One example is attackers using gadget chains to perform unauthorized actions, such as generating a shell.
Frequently Asked Questions
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