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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 JVM.
nltk
A vulnerability was found in StanfordVL GibsonEnv 0.3.1. It has been classified as critical. Affected is the function cloudpickle.load of the file gibson\utils\pposgd_fuse.py. The manipulation leads to deserialization. It is possible to launch the attack remotely. The complexity of an attack is rather high. The exploitability is told to be difficult. The exploit has been disclosed to the public and may be used. The identifier of this vulnerability is VDB-252204.
standford
stanford-parser v3.9.2 and below was discovered to contain a code injection vulnerability in the component edu.stanford.nlp.io.getBZip2PipedInputStream. This vulnerability is exploited via passing an unchecked argument.
stanford