nltk - Debian Package Tracker

general

source: nltk (main)
version: 3.10.3-1
maintainer: Debian Science Maintainers (archive) (DMD)
uploaders: Mo Zhou [DMD]
arch: all
std-ver: 4.6.0.1
VCS: Git (Browse, QA)

versions [more versions can be listed by madison] [old versions available from snapshot.debian.org]

[pool directory]

o-o-stable: 3.5-1
oldstable: 3.8-1
stable: 3.9.1-2
testing: 3.10.3-1
unstable: 3.10.3-1

versioned links

3.5-1: [.dsc, use dget on this link to retrieve source package] [changelog] [copyright] [rules] [control]
3.8-1: [.dsc, use dget on this link to retrieve source package] [changelog] [copyright] [rules] [control]
3.9.1-2: [.dsc, use dget on this link to retrieve source package] [changelog] [copyright] [rules] [control]
3.10.3-1: [.dsc, use dget on this link to retrieve source package] [changelog] [copyright] [rules] [control]

binaries

python3-nltk (1 bugs: 0, 1, 0, 0)

action needed

5 security issues in sid high

There are 5 open security issues in sid.

5 important issues:

CVE-2026-12199: 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.
CVE-2026-12259: In nltk version 3.9.4, the `nltk.downloader.Downloader._download_package()` function writes downloaded package bytes to disk and may extract them before enforcing SHA-256 or MD5 checksum validation. This allows an attacker to tamper with the package response body for `info.url` through a compromised mirror, malicious proxy, or other source-substitution condition, leading to the installation of attacker-controlled package bytes. The vulnerability can result in malicious corpus or model content being trusted by downstream users or applications.
CVE-2026-12261: A vulnerability in `nltk.downloader` in nltk/nltk versions <= 3.9.4 allows for cross-package resource and model poisoning. The downloader extracts package archives into shared namespaces such as `corpora/` and `taggers/` instead of package-isolated roots, and validates package integrity only after the archive has been written and extracted. This design flaw enables one package to overwrite another package's trusted resources within the same namespace, making the changes immediately active through ordinary NLTK APIs. This issue persists across fresh interpreter restarts and can affect downstream workflows, including machine learning pipelines and reproducibility-sensitive environments.
CVE-2026-12372: A Server-Side Request Forgery (SSRF) vulnerability exists in nltk/nltk versions 3.9.4 and the current develop branch. The `nltk.pathsec.validate_network_url()` function, intended to prevent SSRF by rejecting internal network addresses, fails to reject IPs in the RFC 6598 shared address space (`100.64.0.0/10`). This occurs because Python's `ipaddress` module does not classify such addresses as `is_private` or `is_global`, and the current guard only checks `is_private` and a few explicit categories. An attacker who can influence a URL passed to NLTK's network-loading helpers can exploit this vulnerability to make a strict-mode application send requests to shared-address-space hosts, potentially exposing non-public infrastructure reachable from the application host. The impact is limited to SSRF-style confidentiality exposure, with no code execution claimed.
CVE-2026-12876:

Created: 2026-02-19 Last update: 2026-08-19 07:31

5 security issues in forky high

There are 5 open security issues in forky.

5 important issues:

CVE-2026-12199: 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.
CVE-2026-12259: In nltk version 3.9.4, the `nltk.downloader.Downloader._download_package()` function writes downloaded package bytes to disk and may extract them before enforcing SHA-256 or MD5 checksum validation. This allows an attacker to tamper with the package response body for `info.url` through a compromised mirror, malicious proxy, or other source-substitution condition, leading to the installation of attacker-controlled package bytes. The vulnerability can result in malicious corpus or model content being trusted by downstream users or applications.
CVE-2026-12261: A vulnerability in `nltk.downloader` in nltk/nltk versions <= 3.9.4 allows for cross-package resource and model poisoning. The downloader extracts package archives into shared namespaces such as `corpora/` and `taggers/` instead of package-isolated roots, and validates package integrity only after the archive has been written and extracted. This design flaw enables one package to overwrite another package's trusted resources within the same namespace, making the changes immediately active through ordinary NLTK APIs. This issue persists across fresh interpreter restarts and can affect downstream workflows, including machine learning pipelines and reproducibility-sensitive environments.
CVE-2026-12372: A Server-Side Request Forgery (SSRF) vulnerability exists in nltk/nltk versions 3.9.4 and the current develop branch. The `nltk.pathsec.validate_network_url()` function, intended to prevent SSRF by rejecting internal network addresses, fails to reject IPs in the RFC 6598 shared address space (`100.64.0.0/10`). This occurs because Python's `ipaddress` module does not classify such addresses as `is_private` or `is_global`, and the current guard only checks `is_private` and a few explicit categories. An attacker who can influence a URL passed to NLTK's network-loading helpers can exploit this vulnerability to make a strict-mode application send requests to shared-address-space hosts, potentially exposing non-public infrastructure reachable from the application host. The impact is limited to SSRF-style confidentiality exposure, with no code execution claimed.
CVE-2026-12876:

Created: 2026-02-19 Last update: 2026-08-19 07:31

23 security issues in bullseye high

There are 23 open security issues in bullseye.

9 important issues:

CVE-2025-71408: NLTK (Natural Language Toolkit) before version 3.9.3 contains an eval injection vulnerability in the nltk.collocations module that allows an attacker who controls command-line arguments to execute arbitrary Python code. When collocations.py is invoked directly, the __main__ block passes command-line arguments directly to eval() as suffixes of BigramAssocMeasures without allowlist validation or sanitization, enabling an attacker to supply a Python expression that escapes the intended attribute lookup and executes arbitrary code including OS commands via the os module.
CVE-2026-12061:
CVE-2026-12072:
CVE-2026-12074:
CVE-2026-12259: In nltk version 3.9.4, the `nltk.downloader.Downloader._download_package()` function writes downloaded package bytes to disk and may extract them before enforcing SHA-256 or MD5 checksum validation. This allows an attacker to tamper with the package response body for `info.url` through a compromised mirror, malicious proxy, or other source-substitution condition, leading to the installation of attacker-controlled package bytes. The vulnerability can result in malicious corpus or model content being trusted by downstream users or applications.
CVE-2026-12261: A vulnerability in `nltk.downloader` in nltk/nltk versions <= 3.9.4 allows for cross-package resource and model poisoning. The downloader extracts package archives into shared namespaces such as `corpora/` and `taggers/` instead of package-isolated roots, and validates package integrity only after the archive has been written and extracted. This design flaw enables one package to overwrite another package's trusted resources within the same namespace, making the changes immediately active through ordinary NLTK APIs. This issue persists across fresh interpreter restarts and can affect downstream workflows, including machine learning pipelines and reproducibility-sensitive environments.
CVE-2026-12372: A Server-Side Request Forgery (SSRF) vulnerability exists in nltk/nltk versions 3.9.4 and the current develop branch. The `nltk.pathsec.validate_network_url()` function, intended to prevent SSRF by rejecting internal network addresses, fails to reject IPs in the RFC 6598 shared address space (`100.64.0.0/10`). This occurs because Python's `ipaddress` module does not classify such addresses as `is_private` or `is_global`, and the current guard only checks `is_private` and a few explicit categories. An attacker who can influence a URL passed to NLTK's network-loading helpers can exploit this vulnerability to make a strict-mode application send requests to shared-address-space hosts, potentially exposing non-public infrastructure reachable from the application host. The impact is limited to SSRF-style confidentiality exposure, with no code execution claimed.
CVE-2026-12841:
CVE-2026-12876:

14 issues postponed or untriaged:

CVE-2021-3828: (needs triaging) nltk is vulnerable to Inefficient Regular Expression Complexity
CVE-2021-3842: (needs triaging) nltk is vulnerable to Inefficient Regular Expression Complexity
CVE-2026-0846: (postponed; to be fixed through a stable update) 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.
CVE-2026-0847: (postponed; to be fixed through a stable update) 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 private keys, and API tokens, and may potentially escalate to remote code execution when combined with other vulnerabilities.
CVE-2026-0848: (postponed; to be fixed through a stable update) 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.
CVE-2021-43854: (needs triaging) 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 tokenizing unpredictable user input, then we would strongly recommend upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions. Our recommendation is to implement such a limit.
CVE-2024-39705: (postponed; to be fixed through a stable update) 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.
CVE-2025-14009: (postponed; to be fixed through a stable update) 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 result in full system compromise, including file system access, network access, and potential persistence mechanisms.
CVE-2026-12199: (postponed; to be fixed through a stable update) 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.
CVE-2026-12252: (postponed; to be fixed through a stable update) In 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.
CVE-2026-33230: (postponed; to be fixed through a stable update) 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 1c3f799607eeb088cab2491dcf806ae83c29ad8f fixes the issue.
CVE-2026-33231: (postponed; to be fixed through a stable update) 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.
CVE-2026-33236: (postponed; to be fixed through a stable update) 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.
CVE-2026-54293: (postponed; to be fixed through a stable update) 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 ../../../etc/passwd are correctly blocked, encoded variants such as %2fetc%2fpasswd, %2e%2e%2f..., and ..%2f..%2f slip past the regex and are subsequently decoded into a real filesystem path. This vulnerability is fixed in 3.10.0-rc1.

Created: 2026-07-26 Last update: 2026-08-19 07:31

20 security issues in bookworm high

There are 20 open security issues in bookworm.

9 important issues:

CVE-2025-71408: NLTK (Natural Language Toolkit) before version 3.9.3 contains an eval injection vulnerability in the nltk.collocations module that allows an attacker who controls command-line arguments to execute arbitrary Python code. When collocations.py is invoked directly, the __main__ block passes command-line arguments directly to eval() as suffixes of BigramAssocMeasures without allowlist validation or sanitization, enabling an attacker to supply a Python expression that escapes the intended attribute lookup and executes arbitrary code including OS commands via the os module.
CVE-2026-12061:
CVE-2026-12072:
CVE-2026-12074:
CVE-2026-12259: In nltk version 3.9.4, the `nltk.downloader.Downloader._download_package()` function writes downloaded package bytes to disk and may extract them before enforcing SHA-256 or MD5 checksum validation. This allows an attacker to tamper with the package response body for `info.url` through a compromised mirror, malicious proxy, or other source-substitution condition, leading to the installation of attacker-controlled package bytes. The vulnerability can result in malicious corpus or model content being trusted by downstream users or applications.
CVE-2026-12261: A vulnerability in `nltk.downloader` in nltk/nltk versions <= 3.9.4 allows for cross-package resource and model poisoning. The downloader extracts package archives into shared namespaces such as `corpora/` and `taggers/` instead of package-isolated roots, and validates package integrity only after the archive has been written and extracted. This design flaw enables one package to overwrite another package's trusted resources within the same namespace, making the changes immediately active through ordinary NLTK APIs. This issue persists across fresh interpreter restarts and can affect downstream workflows, including machine learning pipelines and reproducibility-sensitive environments.
CVE-2026-12372: A Server-Side Request Forgery (SSRF) vulnerability exists in nltk/nltk versions 3.9.4 and the current develop branch. The `nltk.pathsec.validate_network_url()` function, intended to prevent SSRF by rejecting internal network addresses, fails to reject IPs in the RFC 6598 shared address space (`100.64.0.0/10`). This occurs because Python's `ipaddress` module does not classify such addresses as `is_private` or `is_global`, and the current guard only checks `is_private` and a few explicit categories. An attacker who can influence a URL passed to NLTK's network-loading helpers can exploit this vulnerability to make a strict-mode application send requests to shared-address-space hosts, potentially exposing non-public infrastructure reachable from the application host. The impact is limited to SSRF-style confidentiality exposure, with no code execution claimed.
CVE-2026-12841:
CVE-2026-12876:

11 issues postponed or untriaged:

CVE-2026-0846: (needs triaging) 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.
CVE-2026-0847: (needs triaging) 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 private keys, and API tokens, and may potentially escalate to remote code execution when combined with other vulnerabilities.
CVE-2026-0848: (needs triaging) 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.
CVE-2024-39705: (postponed; to be fixed through a stable update) 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.
CVE-2025-14009: (needs triaging) 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 result in full system compromise, including file system access, network access, and potential persistence mechanisms.
CVE-2026-12199: (postponed; to be fixed through a stable update) 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.
CVE-2026-12252: (postponed; to be fixed through a stable update) In 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.
CVE-2026-33230: (needs triaging) 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 1c3f799607eeb088cab2491dcf806ae83c29ad8f fixes the issue.
CVE-2026-33231: (needs triaging) 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.
CVE-2026-33236: (needs triaging) 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.
CVE-2026-54293: (postponed; to be fixed through a stable update) 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 ../../../etc/passwd are correctly blocked, encoded variants such as %2fetc%2fpasswd, %2e%2e%2f..., and ..%2f..%2f slip past the regex and are subsequently decoded into a real filesystem path. This vulnerability is fixed in 3.10.0-rc1.

Created: 2024-06-28 Last update: 2026-08-19 07:31

5 security issues in buster high

There are 5 open security issues in buster.

1 important issue:

CVE-2024-39705: 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.

4 issues postponed or untriaged:

CVE-2021-3828: (needs triaging) nltk is vulnerable to Inefficient Regular Expression Complexity
CVE-2021-3842: (needs triaging) nltk is vulnerable to Inefficient Regular Expression Complexity
CVE-2019-14751: (needs triaging) 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.
CVE-2021-43854: (needs triaging) 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 tokenizing unpredictable user input, then we would strongly recommend upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions. Our recommendation is to implement such a limit.

Created: 2024-06-28 Last update: 2024-06-28 15:00

5 new commits since last upload, is it time to release? normal

vcswatch reports that this package seems to have new commits in its VCS but has not yet updated debian/changelog. You should consider updating the Debian changelog and uploading this new version into the archive.

Here are the relevant commit logs:

commit c5329b5027036e8062d934c3d458daecb973b287
Author: Alexandre Detiste <tchet@debian.org>
Date:   Fri Aug 14 09:38:57 2026 +0200

    add debian/salsa-ci.yml

commit 5c0bc95bb449041d1cf978d44cfae436725a5888
Author: Alexandre Detiste <tchet@debian.org>
Date:   Fri Aug 14 09:34:18 2026 +0200

    d/rules: drop Python2 crumb

commit 9fcc3cece7ab4404c4980b970beef4ff4b113186
Author: Alexandre Detiste <tchet@debian.org>
Date:   Fri Aug 14 09:33:40 2026 +0200

    bump Standards-Version to 4.7.4, drop Priority: tag

commit 751f2f9c25cfaa59f7546a16feb56496a5c2ac75
Author: Alexandre Detiste <tchet@debian.org>
Date:   Fri Aug 14 09:31:49 2026 +0200

    drop "Rules-Requires-Root: no": it is now the default

commit 686cd45e882a0e31c7d67a6c089d0cf7a8a6b458
Author: Alexandre Detiste <tchet@debian.org>
Date:   Fri Aug 14 09:31:29 2026 +0200

    use dh-sequence-python3

https://salsa.debian.org/api/v4/projects/science-team%2Fnltk API request failed: 401 Unauthorized at /srv/qa.debian.org/data/vcswatch/vcswatch line 410.

Created: 2026-08-13 Last update: 2026-08-20 15:02

lintian reports 1 warning normal

Lintian reports 1 warning about this package. You should make the package lintian clean getting rid of them.

Created: 2026-08-14 Last update: 2026-08-14 21:31

19 low-priority security issues in trixie low

There are 19 open security issues in trixie.

19 issues left for the package maintainer to handle:

CVE-2026-0846: (needs triaging) 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.
CVE-2026-0847: (needs triaging) 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 private keys, and API tokens, and may potentially escalate to remote code execution when combined with other vulnerabilities.
CVE-2026-0848: (needs triaging) 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.
CVE-2025-14009: (needs triaging) 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 result in full system compromise, including file system access, network access, and potential persistence mechanisms.
CVE-2025-71408: (needs triaging) NLTK (Natural Language Toolkit) before version 3.9.3 contains an eval injection vulnerability in the nltk.collocations module that allows an attacker who controls command-line arguments to execute arbitrary Python code. When collocations.py is invoked directly, the __main__ block passes command-line arguments directly to eval() as suffixes of BigramAssocMeasures without allowlist validation or sanitization, enabling an attacker to supply a Python expression that escapes the intended attribute lookup and executes arbitrary code including OS commands via the os module.
CVE-2026-12061: (needs triaging)
CVE-2026-12072: (needs triaging)
CVE-2026-12074: (needs triaging)
CVE-2026-12199: (needs triaging) 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.
CVE-2026-12252: (needs triaging) In 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.
CVE-2026-12259: (needs triaging) In nltk version 3.9.4, the `nltk.downloader.Downloader._download_package()` function writes downloaded package bytes to disk and may extract them before enforcing SHA-256 or MD5 checksum validation. This allows an attacker to tamper with the package response body for `info.url` through a compromised mirror, malicious proxy, or other source-substitution condition, leading to the installation of attacker-controlled package bytes. The vulnerability can result in malicious corpus or model content being trusted by downstream users or applications.
CVE-2026-12261: (needs triaging) A vulnerability in `nltk.downloader` in nltk/nltk versions <= 3.9.4 allows for cross-package resource and model poisoning. The downloader extracts package archives into shared namespaces such as `corpora/` and `taggers/` instead of package-isolated roots, and validates package integrity only after the archive has been written and extracted. This design flaw enables one package to overwrite another package's trusted resources within the same namespace, making the changes immediately active through ordinary NLTK APIs. This issue persists across fresh interpreter restarts and can affect downstream workflows, including machine learning pipelines and reproducibility-sensitive environments.
CVE-2026-12372: (needs triaging) A Server-Side Request Forgery (SSRF) vulnerability exists in nltk/nltk versions 3.9.4 and the current develop branch. The `nltk.pathsec.validate_network_url()` function, intended to prevent SSRF by rejecting internal network addresses, fails to reject IPs in the RFC 6598 shared address space (`100.64.0.0/10`). This occurs because Python's `ipaddress` module does not classify such addresses as `is_private` or `is_global`, and the current guard only checks `is_private` and a few explicit categories. An attacker who can influence a URL passed to NLTK's network-loading helpers can exploit this vulnerability to make a strict-mode application send requests to shared-address-space hosts, potentially exposing non-public infrastructure reachable from the application host. The impact is limited to SSRF-style confidentiality exposure, with no code execution claimed.
CVE-2026-12841: (needs triaging)
CVE-2026-12876: (needs triaging)
CVE-2026-33230: (needs triaging) 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 1c3f799607eeb088cab2491dcf806ae83c29ad8f fixes the issue.
CVE-2026-33231: (needs triaging) 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.
CVE-2026-33236: (needs triaging) 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.
CVE-2026-54293: (needs triaging) 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 ../../../etc/passwd are correctly blocked, encoded variants such as %2fetc%2fpasswd, %2e%2e%2f..., and ..%2f..%2f slip past the regex and are subsequently decoded into a real filesystem path. This vulnerability is fixed in 3.10.0-rc1.

You can find information about how to handle these issues in the security team's documentation.

Created: 2026-02-19 Last update: 2026-08-19 07:31

Standards version of the package is outdated. wishlist

The package should be updated to follow the last version of Debian Policy (Standards-Version 4.7.4 instead of 4.6.0.1).

Created: 2022-05-11 Last update: 2026-08-14 12:14

news

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[2026-08-19] nltk 3.10.3-1 MIGRATED to testing (Debian testing watch)
[2026-08-14] Accepted nltk 3.10.3-1 (source) into unstable (Tianyu Chen) (signed by: Alexandre Detiste)
[2026-08-08] nltk 3.10.1-1 MIGRATED to testing (Debian testing watch)
[2026-08-02] Accepted nltk 3.10.1-1 (source) into unstable (Mo Zhou)
[2026-07-18] nltk 3.10.0-1 MIGRATED to testing (Debian testing watch)
[2026-07-13] Accepted nltk 3.10.0-1 (source) into unstable (Mo Zhou)
[2026-03-13] nltk 3.9.3-1 MIGRATED to testing (Debian testing watch)
[2026-03-07] Accepted nltk 3.9.3-1 (source) into unstable (Mo Zhou)
[2026-02-20] nltk 3.9.2-1 MIGRATED to testing (Debian testing watch)
[2026-02-14] Accepted nltk 3.9.2-1 (source) into unstable (Mo Zhou)
[2024-10-18] nltk 3.9.1-2 MIGRATED to testing (Debian testing watch)
[2024-10-12] Accepted nltk 3.9.1-2 (source) into unstable (Santiago Vila)
[2024-10-07] nltk 3.9.1-1 MIGRATED to testing (Debian testing watch)
[2024-10-02] Accepted nltk 3.9.1-1 (source) into unstable (Mo Zhou)
[2023-06-23] nltk 3.8.1-1 MIGRATED to testing (Debian testing watch)
[2023-06-18] Accepted nltk 3.8.1-1 (source) into unstable (Mo Zhou)
[2022-12-20] nltk 3.8-1 MIGRATED to testing (Debian testing watch)
[2022-12-14] Accepted nltk 3.8-1 (source) into unstable (Mo Zhou)
[2022-02-22] nltk 3.7-1 MIGRATED to testing (Debian testing watch)
[2022-02-16] Accepted nltk 3.7-1 (source) into unstable (Mo Zhou)
[2022-01-12] nltk 3.6.7-1 MIGRATED to testing (Debian testing watch)
[2022-01-06] Accepted nltk 3.6.7-1 (source) into unstable (Mo Zhou)
[2021-11-19] nltk 3.6.5-1 MIGRATED to testing (Debian testing watch)
[2021-11-13] Accepted nltk 3.6.5-1 (source) into unstable (Mo Zhou)
[2020-04-28] nltk 3.5-1 MIGRATED to testing (Debian testing watch)
[2020-04-23] Accepted nltk 3.5-1 (source) into unstable (Mo Zhou)
[2019-12-27] nltk 3.4.5-2 MIGRATED to testing (Debian testing watch)
[2019-12-22] Accepted nltk 3.4.5-2 (source) into unstable (Mo Zhou) (signed by: Zhou Mo)
[2019-08-30] nltk 3.4.5-1 MIGRATED to testing (Debian testing watch)
[2019-08-24] Accepted nltk 3.4.5-1 (source) into unstable (Mo Zhou) (signed by: Zhou Mo)

bugs [bug history graph]

all: 4
RC: 0
I&N: 4
M&W: 0
F&P: 0
patch: 0

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[Information about Ubuntu for Debian Developers]

version: 3.10.3-1