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CVE-2025-32798: CWE-94: Improper Control of Generation of Code ('Code Injection') in conda conda-build

High
VulnerabilityCVE-2025-32798cvecve-2025-32798cwe-94
Published: Mon Jun 16 2025 (06/16/2025, 20:10:06 UTC)
Source: CVE Database V5
Vendor/Project: conda
Product: conda-build

Description

Conda-build contains commands and tools to build conda packages. Prior to version 25.4.0, the conda-build recipe processing logic has been found to be vulnerable to arbitrary code execution due to unsafe evaluation of recipe selectors. Currently, conda-build uses the eval function to process embedded selectors in meta.yaml files. This approach evaluates user-defined expressions without proper sanitization, which allows arbitrary code to be executed during the build process. As a result, the integrity of the build environment is compromised, and unauthorized commands or file operations may be performed. The vulnerability stems from the inherent risk of using eval() on untrusted input in a context intended to control dynamic build configurations. By directly interpreting selector expressions, conda-build creates a potential execution pathway for malicious code, violating security assumptions. This issue has been patched in version 25.4.0.

AI-Powered Analysis

AILast updated: 06/16/2025, 20:34:33 UTC

Technical Analysis

CVE-2025-32798 is a high-severity vulnerability affecting conda-build versions prior to 25.4.0. Conda-build is a tool used to create conda packages, widely utilized in scientific computing and data science environments for managing software dependencies and environments. The vulnerability arises from the unsafe use of the Python eval() function to process embedded selectors in meta.yaml recipe files. These selectors are expressions intended to dynamically control build configurations. However, because eval() executes arbitrary Python code, any maliciously crafted selector expression can lead to arbitrary code execution during the build process. This means that an attacker who can influence or supply a meta.yaml file can execute unauthorized commands or manipulate files within the build environment. The flaw compromises the integrity and security assumptions of the build process, potentially allowing attackers to inject malicious code into packages or the build environment itself. The vulnerability does not require authentication or user interaction, and the attack vector is network accessible if the build process consumes untrusted recipe files. The issue was patched in conda-build version 25.4.0 by removing or securing the use of eval() in selector processing. No known exploits are reported in the wild as of the publication date, but the high CVSS score of 8.2 reflects the significant risk posed by this vulnerability if exploited.

Potential Impact

For European organizations, especially those engaged in scientific research, software development, and data science, this vulnerability poses a serious risk. Conda and conda-build are popular tools in academia, research institutions, and enterprises that rely on Python environments for analytics and machine learning. Exploitation could lead to unauthorized code execution within build environments, potentially resulting in the insertion of malicious code into software packages distributed internally or externally. This compromises software supply chain integrity, leading to downstream infections or data breaches. Confidentiality, integrity, and availability of systems relying on affected packages could be severely impacted. Organizations using automated build pipelines that incorporate untrusted or external recipe files are particularly vulnerable. The vulnerability could also facilitate lateral movement within networks if attackers gain footholds through compromised build environments. Given the critical role of conda-build in many European scientific and industrial sectors, the impact could extend to critical infrastructure and intellectual property theft.

Mitigation Recommendations

1. Immediate upgrade to conda-build version 25.4.0 or later to ensure the vulnerability is patched. 2. Audit and restrict sources of meta.yaml recipe files to trusted repositories only; avoid using unverified or third-party recipes without thorough review. 3. Implement strict code review and validation processes for all build recipes to detect and remove potentially malicious selectors. 4. Use isolated and ephemeral build environments (e.g., containers or virtual machines) to limit the impact of any potential code execution during builds. 5. Monitor build logs and environment activity for unusual commands or file operations indicative of exploitation attempts. 6. Employ runtime application self-protection (RASP) or endpoint detection and response (EDR) tools to detect anomalous behavior during build processes. 7. Educate developers and build engineers about the risks of unsafe eval() usage and secure coding practices in build automation. 8. If upgrading is not immediately possible, consider disabling or sandboxing selector evaluation functionality where feasible to reduce risk.

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Technical Details

Data Version
5.1
Assigner Short Name
GitHub_M
Date Reserved
2025-04-10T12:51:12.282Z
Cvss Version
4.0
State
PUBLISHED

Threat ID: 68507c50a8c9212743849b3a

Added to database: 6/16/2025, 8:19:28 PM

Last enriched: 6/16/2025, 8:34:33 PM

Last updated: 8/12/2025, 8:55:40 AM

Views: 25

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