NLTK: URL-Encoded Path Traversal in nltk.data.load() Allows Arbitrary Local File Read
NLTK (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. Prior to 3.10.0-rc1, nltk.data.load() in NLTK is vulnerable to path traversal via URL-encoded path separators and traversal segments when using the nltk: URL scheme. The unsafe-path regex check is performed before url2pathname() decodes the %xx sequences (a classic decode-after-check / TOCTOU-style flaw), allowing an attacker to bypass the protection documented in NLTK's SECURITY.md and read arbitrary files from the filesystem. While literal traversal strings such as ../../../et
Unauthenticated Denial of Service in nltk.app.wordnet_app
A vulnerability in `nltk.app.wordnet_app` up to version 3.9.3 allows unauthenticated remote shutdown of the local WordNet Browser HTTP server when started in its default mode. The server listens on all interfaces and processes a specific unauthenticated GET request (`/SHUTDOWN%20THE%20SERVER`) to terminate the process immediately via `os._exit(0)`. This results in a denial of service, impacting service availability. The issue arises due to insufficient authentication and protection mechanisms for critical server functions.
NLTK has a Downloader Path Traversal Vulnerability (AFO) - Arbitrary File Overwrite
NLTK (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. In versions 3.9.3 and prior, the NLTK downloader does not validate the `subdir` and `id` attributes when processing remote XML index files. Attackers can control a remote XML index server to provide malicious values containing path traversal sequences (such as `../`), which can lead to arbitrary directory creation, arbitrary file creation, and arbitrary file overwrite. Commit 89fe2ec2c6bae6e2e7a46dad65cc34231976ed8a patches the issue.
NLTK has unauthenticated remote shutdown in nltk.app.wordnet_app
NLTK (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. In versions 3.9.3 and prior, `nltk.app.wordnet_app` allows unauthenticated remote shutdown of the local WordNet Browser HTTP server when it is started in its default mode. A simple `GET /SHUTDOWN%20THE%20SERVER` request causes the process to terminate immediately via `os._exit(0)`, resulting in a denial of service. Commit bbaae83db86a0f49e00f5b0db44a7254c268de9b patches the issue.
NLTK (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. In versions 3.9.3 and prior, `nltk.app.wordnet_app` contains a reflected cross-site scripting issue in the `lookup_...` route. A crafted `lookup_<payload>` URL can inject arbitrary HTML/JavaScript into the response page because attacker-controlled `word` data is reflected into HTML without escaping. This impacts users running the local WordNet Browser server and can lead to script execution in the browser origin of that application. Commit 1c3f799607eeb088cab2491dcf806ae83c29ad8
Arbitrary File Read via Absolute Path Input in nltk.util.filestring()
A vulnerability in the `filestring()` function of the `nltk.util` module in nltk version 3.9.2 allows arbitrary file read due to improper validation of input paths. The function directly opens files specified by user input without sanitization, enabling attackers to access sensitive system files by providing absolute paths or traversal paths. This vulnerability can be exploited locally or remotely, particularly in scenarios where the function is used in web APIs or other interfaces that accept user-supplied input.
Arbitrary Code Execution in NLTK StanfordSegmenter via Untrusted JAR Loading
NLTK versions <=3.9.2 are vulnerable to arbitrary code execution due to improper input validation in the StanfordSegmenter module. The module dynamically loads external Java .jar files without verification or sandboxing. An attacker can supply or replace the JAR file, enabling the execution of arbitrary Java bytecode at import time. This vulnerability can be exploited through methods such as model poisoning, MITM attacks, or dependency poisoning, leading to remote code execution. The issue arises from the direct execution of the JAR file via subprocess with unvalidated classpath input, allowing malicious classes to execute when loaded by the
A vulnerability in NLTK versions up to and including 3.9.2 allows arbitrary file read via path traversal in multiple CorpusReader classes, including WordListCorpusReader, TaggedCorpusReader, and BracketParseCorpusReader. These classes fail to properly sanitize or validate file paths, enabling attackers to traverse directories and access sensitive files on the server. This issue is particularly critical in scenarios where user-controlled file inputs are processed, such as in machine learning APIs, chatbots, or NLP pipelines. Exploitation of this vulnerability can lead to unauthorized access to sensitive files, including system files, SSH priva
Zip Slip Vulnerability in nltk/nltk Leading to Remote Code Execution
A critical vulnerability exists in the NLTK downloader component of nltk/nltk, affecting all versions. The _unzip_iter function in nltk/downloader.py uses zipfile.extractall() without performing path validation or security checks. This allows attackers to craft malicious zip packages that, when downloaded and extracted by NLTK, can execute arbitrary code. The vulnerability arises because NLTK assumes all downloaded packages are trusted and extracts them without validation. If a malicious package contains Python files, such as __init__.py, these files are executed automatically upon import, leading to remote code execution. This issue can resu
NLTK through 3.8.1 allows remote code execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.
NLTK (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokeni
NLTK Downloader before 3.4.5 is vulnerable to a directory traversal, allowing attackers to write arbitrary files via a ../ (dot dot slash) in an NLTK package (ZIP archive) that is mishandled during extraction.