CVE-2024-52338: Apache Arrow R Package RCE Vulnerability

CVE-2024-52338 Overview

CVE-2024-52338 is an Insecure Deserialization vulnerability affecting the Apache Arrow R package versions 4.0.0 through 16.1.0. The vulnerability exists in the IPC and Parquet readers, allowing arbitrary code execution when an application reads Arrow IPC, Feather, or Parquet data from untrusted sources such as user-supplied input files.

This vulnerability is specifically limited to the arrow R package and does not affect 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 remains vulnerable if the arrow R package is an affected version.

Critical Impact

This insecure deserialization vulnerability enables remote arbitrary code execution through maliciously crafted Arrow IPC, Feather, or Parquet files, potentially leading to complete system compromise when processing untrusted data.

Affected Products

• Apache Arrow R package versions 4.0.0 through 16.1.0
• Applications reading Arrow IPC data from untrusted sources
• Applications reading Feather or Parquet files from user-supplied inputs

Discovery Timeline

• 2024-11-28 - CVE CVE-2024-52338 published to NVD
• 2025-07-15 - Last updated in NVD database

Technical Details for CVE-2024-52338

Vulnerability Analysis

This vulnerability falls under CWE-502 (Deserialization of Untrusted Data), a class of security issues where applications deserialize data without adequate validation, allowing attackers to inject malicious serialized objects that execute arbitrary code upon deserialization.

The Apache Arrow R package provides high-performance data interchange capabilities, supporting multiple columnar data formats including Arrow IPC, Feather, and Parquet. The vulnerability manifests when the package's reader functions process serialized data from untrusted sources without proper sanitization or validation of the deserialized content.

When a victim application uses affected versions of the arrow R package to read maliciously crafted data files, the deserialization process can be exploited to execute arbitrary code within the context of the R process. This is particularly dangerous in data science and analytics environments where processing external datasets is common practice.

Root Cause

The root cause of CVE-2024-52338 is insufficient validation during the deserialization process within the Arrow R package's IPC and Parquet readers. The package failed to properly sanitize serialized objects before reconstructing them in memory, allowing attackers to embed malicious payloads that execute during the deserialization phase.

Insecure deserialization vulnerabilities occur when applications trust the serialized data's integrity without verification. In this case, the Arrow R package's reader functions processed serialized Arrow data structures without adequately validating that the content was safe to deserialize, creating an avenue for code injection through specially crafted data files.

Attack Vector

The attack vector is network-based, requiring no privileges or user interaction. An attacker can exploit this vulnerability by:

1. Crafting a malicious Arrow IPC, Feather, or Parquet file containing embedded code execution payloads
2. Delivering the malicious file to a target system through various means (file uploads, data feeds, shared storage)
3. Waiting for the victim application to process the file using an affected version of the arrow R package

The vulnerability is exploited during the normal file reading operation. Any R application that ingests external data using functions like read_parquet(), read_feather(), or read_ipc_file() from affected versions is potentially vulnerable when processing untrusted input.

For detailed technical information about the vulnerability mechanism, refer to the Apache Mailing List Thread and the Openwall OSS-Security Post.

Detection Methods for CVE-2024-52338

Indicators of Compromise

• Unexpected child processes spawned by R interpreter sessions processing Arrow/Parquet files
• Unusual network connections originating from R applications
• Anomalous file system activity during data file ingestion operations
• R processes exhibiting behaviors inconsistent with typical data processing tasks

Detection Strategies

• Monitor R package installations and audit for arrow package versions between 4.0.0 and 16.1.0
• Implement file integrity monitoring on directories where external Arrow/Parquet files are stored
• Deploy endpoint detection rules to identify suspicious process chains involving R interpreters
• Use application-level logging to track all external data file ingestion events

Monitoring Recommendations

• Enable verbose logging for R applications that process external data files
• Implement network segmentation to limit R application access to external resources
• Configure SentinelOne agents to monitor R interpreter activity for anomalous behavior
• Establish baseline behavior patterns for data processing applications to detect deviations

How to Mitigate CVE-2024-52338

Immediate Actions Required

• Upgrade the Apache Arrow R package to version 17.0.0 or later immediately
• Audit all R applications to identify those using affected arrow package versions
• Implement input validation and source verification for all external data files
• Review and restrict which applications have access to process untrusted data sources

Patch Information

Apache has addressed this vulnerability in arrow R package version 17.0.0. Users should upgrade immediately by running:

install.packages("arrow")

The security fix is documented in the GitHub Apache Arrow Commit. Downstream libraries should also update their dependency requirements to arrow 17.0.0 or later.

Workarounds

• Use the internal to_data_frame() method as a workaround by reading data into a Table first: read_parquet(..., as_data_frame = FALSE)$to_data_frame()
• Apply the same workaround pattern to Feather and IPC file reading operations
• Restrict processing of external data files to isolated or sandboxed environments
• Implement strict allow-listing for data sources until the package can be upgraded

# Workaround configuration example
# Instead of direct reading:
# data <- read_parquet("untrusted_file.parquet")

# Use the safer two-step approach:
table <- read_parquet("untrusted_file.parquet", as_data_frame = FALSE)
data <- table$to_data_frame()