Nltk
- 2
- vulnerabilities tracked
- 4 July 2026
- latest publication
cve
Vulnerability watch
idvulnerabilityseveritypublished
CVE-2026-12252In nltk/nltk versions 3.9.3 and earlier, five Stanford interface classes (StanfordPOSTagger, StanfordNERTagger, StanfordParser, StanfordDependencyParser, and StanfordNeuralDependencyParser) are vulnerable to untrusted JAR code execution. These classes accept user-controllable JAR paths and execute them via the `java()` function, which invokes `subprocess.Popen()` without integrity verification. This vulnerability is identical to CVE-2026-0848, which was fixed for StanfordSegmenter by adding SHA256 verification. However, the fix was not applied to these additional classes, leaving them susceptible to arbitrary code execution when loading untrusted JAR files.Nltk High CVSS 7.8 CVE-2026-12243NLTK version 3.9.4 is vulnerable to a path traversal attack due to an incomplete fix for GitHub Issue #3504. The `_UNSAFE_NO_PROTOCOL_RE` regex in `nltk/data.py` checks for literal `../` sequences but fails to account for percent-encoded traversal sequences such as `..%2f`. The `url2pathname()` function decodes these sequences after the validation step, allowing an attacker to bypass the protection. This vulnerability enables an attacker to read arbitrary files accessible to the Python process by controlling the resource name parameter passed to `nltk.data.load()` or `nltk.data.find()`. The issue affects applications that rely on NLTK for resource loading, including NLP web applications, Jupyter notebooks, and CLI tools. The default `pathsec.ENFORCE=False` setting exacerbates the impact by not blocking the file read at the `open()` stage.Nltk High CVSS 7.5