CVE-2023-41175: Libtiff RCE Vulnerability

CVE-2023-41175 Overview

A vulnerability was found in libtiff due to multiple potential integer overflows in raw2tiff.c. This flaw allows remote attackers to cause a denial of service or possibly execute arbitrary code via a crafted TIFF image, which triggers a heap-based buffer overflow. The vulnerability exists in the raw2tiff utility, which is used for converting raw image data into TIFF format.

Critical Impact

Remote attackers can exploit this integer overflow vulnerability to trigger a heap-based buffer overflow, potentially leading to denial of service or arbitrary code execution when processing malicious TIFF images.

Affected Products

• libtiff (all vulnerable versions)
• Fedora Project Fedora
• Red Hat Enterprise Linux 8.0 and 9.0

Discovery Timeline

• October 5, 2023 - CVE-2023-41175 published to NVD
• December 4, 2024 - Last updated in NVD database

Technical Details for CVE-2023-41175

Vulnerability Analysis

This vulnerability is classified as CWE-190 (Integer Overflow or Wraparound). The flaw resides in the raw2tiff.c source file within the libtiff library. When processing specially crafted input data, integer overflow conditions can occur during arithmetic operations that calculate buffer sizes or offsets. These integer overflows can result in smaller-than-expected memory allocations, leading to subsequent heap-based buffer overflows when data is written to these undersized buffers.

The network attack vector indicates that exploitation can occur when a user opens a malicious TIFF image received from a remote source, such as through email attachments, web downloads, or document processing workflows. User interaction is required to trigger the vulnerability, as the victim must process the malicious image file.

Root Cause

The root cause is improper handling of integer arithmetic in raw2tiff.c. When calculating memory allocation sizes based on image dimensions or other user-controlled parameters, the code fails to properly validate that the arithmetic operations do not overflow. This allows attackers to craft input that causes integer wraparound, resulting in memory allocations that are too small to hold the actual data being processed.

Attack Vector

The attack vector involves crafting a malicious TIFF image file with specially chosen parameters that trigger integer overflow conditions in the raw2tiff conversion utility. When the victim processes this crafted image—either directly using the raw2tiff tool or through applications that use libtiff for image processing—the integer overflow leads to a heap-based buffer overflow.

The exploitation flow typically involves:

1. Attacker crafts a TIFF image with specific dimension or size parameters designed to cause integer overflow
2. Victim receives and opens the malicious image file
3. The raw2tiff processing code calculates buffer sizes using the malicious parameters
4. Integer overflow occurs, resulting in undersized buffer allocation
5. Subsequent write operations overflow the heap buffer
6. Depending on heap layout and exploitation sophistication, this can result in denial of service or arbitrary code execution

Detection Methods for CVE-2023-41175

Indicators of Compromise

• Unusual crashes or segmentation faults in applications using libtiff for image processing
• Unexpected memory corruption errors when processing TIFF files
• Detection of TIFF files with abnormally large or suspicious dimension values
• Application instability when handling image conversion tasks involving raw2tiff

Detection Strategies

• Monitor for crashes in libtiff-dependent applications with heap corruption signatures
• Implement input validation to detect TIFF files with suspicious or extreme dimension parameters
• Deploy memory safety tools like AddressSanitizer in development and testing environments to detect heap overflows
• Use file integrity monitoring on systems that process untrusted TIFF images

Monitoring Recommendations

• Enable crash dump collection for applications that process TIFF images to identify potential exploitation attempts
• Monitor system logs for repeated segmentation faults or memory allocation failures in image processing workflows
• Implement network traffic analysis to detect potentially malicious TIFF files being transferred to vulnerable systems
• Track libtiff library versions across the environment to identify unpatched systems

How to Mitigate CVE-2023-41175

Immediate Actions Required

• Update libtiff to the latest patched version available for your distribution
• Apply Red Hat security errata RHSA-2024:2289 for Red Hat Enterprise Linux systems
• Restrict processing of untrusted TIFF images until patches are applied
• Review and update any custom applications that depend on libtiff for image processing

Patch Information

Red Hat has released security updates addressing this vulnerability. For Red Hat Enterprise Linux systems, administrators should apply the security errata RHSA-2024:2289. Additional details about the vulnerability are available through the Red Hat CVE-2023-41175 Details page. The issue is tracked in Red Hat Bug Report #2235264.

Workarounds

• Avoid using the raw2tiff utility to process untrusted or externally sourced image files until the patch is applied
• Implement application-level sandboxing for image processing tasks to limit the impact of potential exploitation
• Consider using alternative image processing tools that do not rely on the vulnerable libtiff components
• Deploy input validation at the application layer to reject TIFF files with suspicious characteristics before they reach libtiff

# Example: Update libtiff on Red Hat Enterprise Linux
sudo yum update libtiff

# Example: Update on Fedora
sudo dnf update libtiff

# Verify installed version
rpm -qa | grep libtiff