CVE-2026-0848 in nltk
Summary
by MITRE • 03/05/2026
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.
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Analysis
by VulDB Data Team • 03/10/2026
The vulnerability identified as CVE-2026-0848 represents a critical security flaw in the Natural Language Toolkit library affecting versions 3.9.2 and earlier. This weakness resides within the StanfordSegmenter module where the library fails to properly validate input parameters during the dynamic loading of external Java archive files. The flaw stems from inadequate sandboxing mechanisms that permit the execution of arbitrary Java bytecode without proper verification or isolation. According to CWE-472, this vulnerability manifests as an external control flow modification, where untrusted input directly influences the execution path of external processes. The security implications are severe as the flaw allows for arbitrary code execution through the manipulation of Java classpath parameters during import operations.
The technical exploitation of this vulnerability occurs through multiple attack vectors including model poisoning, man-in-the-middle attacks, and dependency poisoning techniques. When an attacker successfully substitutes or supplies a malicious Java .jar file, the NLTK library executes the loaded bytecode within the JVM context without any validation checks. This behavior aligns with ATT&CK technique T1059.007, which describes the execution of code through Java-based applications, and represents a direct violation of secure coding principles for external process invocation. The subprocess execution mechanism used by the StanfordSegmenter module lacks proper input sanitization, creating an environment where attacker-controlled classpath entries can be executed with the privileges of the running application. The vulnerability's root cause lies in the improper handling of dynamic classpath construction, where user-supplied input is directly incorporated into system calls without adequate sanitization or verification.
The operational impact of this vulnerability extends beyond simple code execution to encompass potential system compromise and data exfiltration capabilities. Attackers can leverage this flaw to execute malicious Java applications, establish persistence mechanisms, or perform lateral movement within compromised networks. The vulnerability affects any system utilizing NLTK's StanfordSegmenter functionality, particularly those in environments where network traffic is not properly monitored or where dependency management is not strictly enforced. Organizations relying on NLTK for natural language processing tasks face significant risk, especially in cloud environments or containerized applications where the attack surface is expanded. The vulnerability's exploitation requires minimal privileges and can be automated, making it particularly dangerous for widespread deployment scenarios.
Mitigation strategies for CVE-2026-0848 should focus on immediate version upgrades to NLTK 3.9.3 or later where the vulnerability has been addressed through proper input validation and sandboxing mechanisms. Organizations should implement strict dependency verification processes, including checksum validation and digital signature verification of all external Java libraries. Network segmentation and monitoring should be enhanced to detect unauthorized Java .jar file modifications or unexpected subprocess executions. The implementation of secure coding practices including parameter sanitization, input validation, and process isolation should be enforced throughout the application lifecycle. Additionally, security teams should conduct regular vulnerability assessments of third-party dependencies and establish automated monitoring for suspicious classpath modifications or unexpected Java bytecode execution patterns. These measures align with industry standards including NIST SP 800-53 controls for secure coding and software development lifecycle security practices.