High CVSS 7.5
CVE-2026-54499
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.
What this means
- Exposure
- Exploitable remotely over the network and without authentication — but only if a user opens booby-trapped content. The attack does require particular conditions, which makes it less systematic.
- Impact
- An attacker can read sensitive data, modify or destroy data and take the service offline.
- Weakness
- The application rebuilds an object from attacker-controlled data, which often leads to code execution.
- Likelihood
- Its EPSS score stays low: nothing points to imminent exploitation, which is no reason to leave it unpatched.
What to doFold into the next patch cycle.
Read automatically from the CVSS vector, the weakness type (CWE) and the EPSS score. The technical description above remains the one published by NIST.