0.0
NA
CVE-2026-31237
Ludwig Insecure Deserialization Vulnerability
Description

The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction.

INFO

Published Date :

May 12, 2026, 6:16 p.m.

Last Modified :

May 12, 2026, 6:16 p.m.

Remotely Exploit :

No
Affected Products

The following products are affected by CVE-2026-31237 vulnerability. Even if cvefeed.io is aware of the exact versions of the products that are affected, the information is not represented in the table below.

No affected product recoded yet

Solution
Update Ludwig to a version that addresses insecure deserialization in the predict() method.
  • Update Ludwig to a version that sanitizes pickle file inputs.
  • Avoid loading untrusted pickle files directly.
  • Implement strict input validation for file paths.
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-2026-31237.

URL Resource
https://github.com/ludwig-ai/ludwig
https://www.notion.so/CVE-2026-31237-35d1e139318881fb95a2ee7c5d0e17d8
CWE - Common Weakness Enumeration

While CVE identifies specific instances of vulnerabilities, CWE categorizes the common flaws or weaknesses that can lead to vulnerabilities. CVE-2026-31237 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-2026-31237 weaknesses.

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).

Results are limited to the first 15 repositories due to potential performance issues.

The following list is the news that have been mention CVE-2026-31237 vulnerability anywhere in the article.

The following table lists the changes that have been made to the CVE-2026-31237 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.

  • New CVE Received by [email protected]

    May. 12, 2026

    Action Type Old Value New Value
    Added Description The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction.
    Added Reference https://github.com/ludwig-ai/ludwig
    Added Reference https://www.notion.so/CVE-2026-31237-35d1e139318881fb95a2ee7c5d0e17d8
EPSS is a daily estimate of the probability of exploitation activity being observed over the next 30 days. Following chart shows the EPSS score history of the vulnerability.