CVE-2024-23346 (GCVE-0-2024-23346)
Vulnerability from cvelistv5 – Published: 2024-02-21 16:13 – Updated: 2024-08-19 07:47
VLAI
EPSS
VEX
Title
pymatgen arbitrary code execution when parsing a maliciously crafted JonesFaithfulTransformation transformation_string
Summary
Pymatgen (Python Materials Genomics) is an open-source Python library for materials analysis. A critical security vulnerability exists in the `JonesFaithfulTransformation.from_transformation_str()` method within the `pymatgen` library prior to version 2024.2.20. This method insecurely utilizes `eval()` for processing input, enabling execution of arbitrary code when parsing untrusted input. Version 2024.2.20 fixes this issue.
Severity
9.4 (Critical)
SSVC
Exploitation: poc
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-02-21 18:18 UTC
CWE
- CWE-77 - Improper Neutralization of Special Elements used in a Command ('Command Injection')
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/materialsproject/pymatgen/secu… | x_refsource_CONFIRM |
| https://github.com/materialsproject/pymatgen/comm… | x_refsource_MISC |
| https://github.com/materialsproject/pymatgen/blob… | x_refsource_MISC |
| https://www.vicarius.io/vsociety/posts/critical-s… |
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| materialsproject | pymatgen |
Affected:
< 2024.2.20
|
guessed | |
| pymatgen | pymatgen |
Affected:
0 , < 2024.2.20
(custom)
cpe:2.3:a:pymatgen:pymatgen:*:*:*:*:*:*:*:* |
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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