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Vulnerability Database/CVE-2026-40386

CVE-2026-40386: Libexif DOS Vulnerability

CVE-2026-40386 is a denial of service flaw in Libexif caused by an integer underflow in MakerNote decoding that enables crashes and information leaks. This article covers technical details, affected versions, and mitigation.

Published:

CVE-2026-40386 Overview

CVE-2026-40386 is an integer underflow vulnerability in libexif through version 0.6.25. The flaw exists in the size checking logic for Fuji and Olympus MakerNote decoding, where improper boundary validation could allow attackers to crash applications or leak sensitive information from programs using the libexif library.

Critical Impact

Attackers can exploit this integer underflow to cause denial of service or extract sensitive information from applications processing maliciously crafted EXIF metadata.

Affected Products

  • libexif through version 0.6.25
  • Applications and libraries that depend on libexif for EXIF metadata parsing
  • Image processing tools using libexif for Fuji and Olympus camera metadata

Discovery Timeline

  • 2026-04-12 - CVE CVE-2026-40386 published to NVD
  • 2026-04-14 - Last updated in NVD database

Technical Details for CVE-2026-40386

Vulnerability Analysis

This vulnerability is classified as CWE-191 (Integer Underflow). The flaw resides in the MakerNote parsing functions for both Fuji and Olympus camera metadata within libexif. The root issue occurs in the boundary check condition used to validate array indices before accessing MakerNote entry data.

The vulnerable code used the expression i > n->count -1 for bounds checking. When n->count is 0 (an unsigned integer), subtracting 1 causes an integer underflow, wrapping the value to the maximum unsigned integer value (typically UINT_MAX). This causes the bounds check to incorrectly pass, allowing out-of-bounds memory access.

Applications processing untrusted EXIF data from image files are at risk. An attacker could craft a malicious image with specially constructed MakerNote metadata to trigger the vulnerability when the image is parsed by any application using libexif.

Root Cause

The vulnerability stems from unsafe arithmetic operations on unsigned integers in boundary condition checks. The expression n->count - 1 when n->count equals 0 underflows to UINT_MAX, rendering the bounds check ineffective. This is a classic integer underflow pattern in C code where the subtraction operation is performed before the comparison.

Attack Vector

The attack vector is local, requiring the victim to process a maliciously crafted image file. The attacker must construct an image containing EXIF metadata with Fuji or Olympus MakerNote entries where the count field is set to 0 or manipulated to trigger the underflow condition. When a vulnerable application parses this image, the integer underflow allows out-of-bounds memory reads, potentially causing:

  1. Application crash - Accessing invalid memory regions leading to segmentation faults
  2. Information disclosure - Reading memory contents beyond the intended buffer boundaries
c
// Vulnerable code pattern in exif-mnote-data-fuji.c and exif-mnote-data-olympus.c
 	ExifMnoteDataFuji *n = (ExifMnoteDataFuji *) d;
 
 	if (!d || !val) return NULL;
-	if (i > n->count -1) return NULL;
+	if (i >= n->count) return NULL;
/*
	exif_log (d->log, EXIF_LOG_CODE_DEBUG, "ExifMnoteDataFuji",
		  "Querying value for tag '%s'...",

Source: GitHub Commit dc6eac6

Detection Methods for CVE-2026-40386

Indicators of Compromise

  • Unexpected crashes in applications processing EXIF metadata from image files
  • Segmentation faults in libexif-dependent applications when handling Fuji or Olympus camera images
  • Anomalous memory access patterns during image metadata parsing operations
  • Core dumps indicating out-of-bounds reads in exif-mnote-data-fuji.c or exif-mnote-data-olympus.c

Detection Strategies

  • Monitor application logs for crashes related to EXIF metadata parsing functions
  • Implement memory sanitizer tools (ASan, MSan) in development and testing environments to detect out-of-bounds access
  • Deploy file integrity monitoring on systems processing untrusted image uploads
  • Use static analysis tools to identify vulnerable libexif versions in deployed applications

Monitoring Recommendations

  • Audit deployed applications and libraries for libexif versions 0.6.25 and earlier
  • Implement crash reporting and monitoring for applications that process user-uploaded images
  • Monitor for unusual memory consumption patterns in image processing services
  • Track software composition analysis (SCA) alerts for vulnerable libexif dependencies

How to Mitigate CVE-2026-40386

Immediate Actions Required

  • Update libexif to a patched version that includes commit dc6eac6e9655d14d0779d99e82d0f5f442d2f34b
  • Audit all applications and dependencies that use libexif for EXIF metadata processing
  • Implement input validation for image files before processing with libexif
  • Consider sandboxing or isolating image processing services that handle untrusted content

Patch Information

The fix has been committed to the libexif repository. The patch modifies the boundary check from i > n->count -1 to i >= n->count, which correctly handles the case when n->count is 0 without causing an integer underflow. This fix was applied to both the Fuji MakerNote handler (exif-mnote-data-fuji.c) and the Olympus MakerNote handler (exif-mnote-data-olympus.c).

Review the security patch commit for complete details.

Workarounds

  • Avoid processing untrusted image files with vulnerable libexif versions until patching is complete
  • Implement application-level sandboxing for image processing operations to limit impact of exploitation
  • Use memory-safe alternatives or wrappers when parsing EXIF data from untrusted sources
  • Deploy Web Application Firewalls (WAF) rules to filter suspicious image uploads where applicable
bash
# Check installed libexif version
pkg-config --modversion libexif

# Verify if the patch is applied (look for the fixed comparison)
grep -r "i >= n->count" /path/to/libexif/source/

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

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