High [CVE-2026-12243] Information disclosure via path traversal vulnerability

NLTK 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.

A flaw was found in NLTK. An attacker can exploit a path traversal vulnerability by providing specially crafted input to `nltk.data.load()` or `nltk.data.find()`.

The vulnerability allows arbitrary file reads when an attacker can control the resource_name parameter by using percent-encoded path separators to bypass validation.

In Red Hat products where NLTK is bundled (OpenShift AI, OpenShift Lightspeed, Ansible Automation Platform), the resource loading functions are typically used internally to load pre-packaged NLP models and corpora.