CVE-2024-52338
Nov. 29, 2024, 3:15 p.m.
9.8
Critical
Description
Deserialization of untrusted data in IPC and Parquet readers in the Apache Arrow R package versions 4.0.0 through 16.1.0 allows arbitrary code execution. An application is vulnerable if it
reads Arrow IPC, Feather or Parquet data from untrusted sources (for
example, user-supplied input files). This vulnerability only affects the arrow R package, not other Apache Arrow
implementations or bindings unless those bindings are specifically used via the R package (for example, an R application that embeds a Python interpreter and uses PyArrow to read files from untrusted sources is still vulnerable if the arrow R package is an affected version). It is recommended that users of the arrow R package upgrade to 17.0.0 or later. Similarly, it
is recommended that downstream libraries upgrade their dependency
requirements to arrow 17.0.0 or later. If using an affected
version of the package, untrusted data can read into a Table and its internal to_data_frame() method can be used as a workaround (e.g., read_parquet(..., as_data_frame = FALSE)$to_data_frame()).
This issue affects the Apache Arrow R package: from 4.0.0 through 16.1.0.
Users are recommended to upgrade to version 17.0.0, which fixes the issue.
Product(s) Impacted
| Product | Versions |
|---|---|
| Apache Arrow R package |
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-502
Deserialization of Untrusted Data
The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid.
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: LOW
- Privileges Required: NONE
- Scope: UNCHANGED
- Confidentiality Impact: HIGH
- Integrity Impact: HIGH
- Availability Impact: HIGH
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
Timeline
Published: Nov. 28, 2024, 5:15 p.m.
Last Modified: Nov. 29, 2024, 3:15 p.m.
Last Modified: Nov. 29, 2024, 3:15 p.m.
Status : Awaiting Analysis
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
security@apache.org
*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.