CVE-2024-5206
Apache scikit-learn Data Leakage-XSS
Description
A sensitive data leakage vulnerability was identified in scikit-learn's TfidfVectorizer, specifically in versions up to and including 1.4.1.post1, which was fixed in version 1.5.0. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.
INFO
Published Date :
June 6, 2024, 7:16 p.m.
Last Modified :
Nov. 21, 2024, 9:47 a.m.
Source :
[email protected]
Remotely Exploitable :
No
Impact Score :
3.6
Exploitability Score :
1.0
Public PoC/Exploit Available at Github
CVE-2024-5206 has a 1 public PoC/Exploit available at Github.
Go to the Public Exploits tab to see the list.
References to Advisories, Solutions, and Tools
Here, you will find a curated list of external links that provide in-depth
information, practical solutions, and valuable tools related to
CVE-2024-5206.
We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).
Weather forecasting web application focusing on containerization with Docker and Kubernetes. The system leverages machine learning for weather predictions while ensuring scalability, high availability, and security through advanced deployment strategies.
Dockerfile Python Jupyter Notebook
Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2024-5206 vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2024-5206 vulnerability over time.
Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.
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CVE Modified by af854a3a-2127-422b-91ae-364da2661108
Nov. 21, 2024
Action Type Old Value New Value Added Reference https://github.com/scikit-learn/scikit-learn/commit/70ca21f106b603b611da73012c9ade7cd8e438b8 Added Reference https://huntr.com/bounties/14bc0917-a85b-4106-a170-d09d5191517c -
Initial Analysis by [email protected]
Oct. 24, 2024
Action Type Old Value New Value Added CVSS V3.1 NIST AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N Changed Reference Type https://github.com/scikit-learn/scikit-learn/commit/70ca21f106b603b611da73012c9ade7cd8e438b8 No Types Assigned https://github.com/scikit-learn/scikit-learn/commit/70ca21f106b603b611da73012c9ade7cd8e438b8 Patch Changed Reference Type https://huntr.com/bounties/14bc0917-a85b-4106-a170-d09d5191517c No Types Assigned https://huntr.com/bounties/14bc0917-a85b-4106-a170-d09d5191517c Third Party Advisory Added CWE NIST CWE-922 Added CPE Configuration OR *cpe:2.3:a:scikit-learn:scikit-learn:*:*:*:*:*:python:*:* versions up to (excluding) 1.5.0 -
CVE Modified by [email protected]
Jun. 17, 2024
Action Type Old Value New Value Removed CVSS V3 huntr.dev AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N Added CVSS V3 huntr.dev AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N -
CVE Received by [email protected]
Jun. 06, 2024
Action Type Old Value New Value Added Description A sensitive data leakage vulnerability was identified in scikit-learn's TfidfVectorizer, specifically in versions up to and including 1.4.1.post1, which was fixed in version 1.5.0. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer. Added Reference huntr.dev https://huntr.com/bounties/14bc0917-a85b-4106-a170-d09d5191517c [No types assigned] Added Reference huntr.dev https://github.com/scikit-learn/scikit-learn/commit/70ca21f106b603b611da73012c9ade7cd8e438b8 [No types assigned] Added CWE huntr.dev CWE-921 Added CVSS V3 huntr.dev AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2024-5206 is
associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification
(CAPEC)
stores attack patterns, which are descriptions of the common attributes and
approaches employed by adversaries to exploit the CVE-2024-5206
weaknesses.