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CVE Vulnerability Database
Vulnerability Database/CVE-2022-24614

CVE-2022-24614: Metadata-extractor DoS Vulnerability

CVE-2022-24614 is a denial of service vulnerability in Metadata-extractor that allows attackers to cause out-of-memory errors via crafted JPEG files. This article covers technical details, affected versions, and mitigation.

Published: February 17, 2026

CVE-2022-24614 Overview

CVE-2022-24614 is a Denial of Service (DoS) vulnerability in the metadata-extractor library affecting versions up to and including 2.16.0. When processing a specially crafted JPEG file, the library can be manipulated to allocate excessive amounts of memory, ultimately triggering an out-of-memory error. This resource exhaustion attack can be executed with very small input files, making it particularly effective against services that process user-uploaded images.

Critical Impact

Services using metadata-extractor for image processing are vulnerable to denial of service attacks through malicious JPEG files that can crash applications by exhausting available memory.

Affected Products

  • metadata-extractor versions up to and including 2.16.0
  • Applications and services integrating metadata-extractor for JPEG metadata parsing
  • Image processing pipelines using the affected library versions

Discovery Timeline

  • 2022-02-24 - CVE-2022-24614 published to NVD
  • 2025-09-12 - Last updated in NVD database

Technical Details for CVE-2022-24614

Vulnerability Analysis

This vulnerability is classified under CWE-770 (Allocation of Resources Without Limits or Throttling). The metadata-extractor library fails to properly validate or limit memory allocation when parsing certain JPEG file structures. An attacker can craft a malicious JPEG file that, when processed by the library, causes disproportionately large memory allocations relative to the actual file size.

The vulnerability enables a resource exhaustion attack where even minimal-sized malicious inputs can consume all available system memory. This asymmetric resource consumption makes the attack highly efficient for adversaries, as they can cause significant service disruption with minimal bandwidth or storage requirements.

Root Cause

The root cause stems from improper resource allocation handling within the JPEG parsing routines of metadata-extractor. The library does not implement adequate bounds checking or memory allocation limits when processing JPEG metadata segments. Malformed or specially crafted JPEG headers can specify dimensions or data structures that trigger excessive memory allocation without corresponding actual data, leading to memory exhaustion.

Attack Vector

The attack requires local access with user interaction, meaning an attacker must convince a user or automated system to process a malicious JPEG file. Common attack scenarios include:

  • Uploading malicious JPEG files to image processing services
  • Sending crafted images via file sharing or messaging platforms
  • Including malicious images in archives or documents processed by vulnerable applications

The attack results in high availability impact, causing the target application or service to crash or become unresponsive due to memory exhaustion. For detailed technical information about the vulnerability mechanism, refer to the GitHub Issue #561.

Detection Methods for CVE-2022-24614

Indicators of Compromise

  • Sudden spikes in memory usage when processing JPEG files
  • Application crashes with out-of-memory errors during image metadata extraction
  • Unusually small JPEG files triggering disproportionate resource consumption
  • Service unavailability following image upload or processing operations

Detection Strategies

  • Monitor application memory usage patterns during JPEG file processing operations
  • Implement alerting for out-of-memory exceptions in services using metadata-extractor
  • Analyze incoming JPEG files for anomalous metadata structures before processing
  • Deploy application performance monitoring to detect resource exhaustion patterns

Monitoring Recommendations

  • Set up memory consumption thresholds with automated alerts for services processing images
  • Log and analyze failed image processing operations for patterns indicating attack attempts
  • Monitor heap memory allocation rates in JVM-based applications using the vulnerable library
  • Track application restart frequency as an indicator of potential DoS attacks

How to Mitigate CVE-2022-24614

Immediate Actions Required

  • Identify all applications and services using metadata-extractor library versions up to 2.16.0
  • Upgrade metadata-extractor to a patched version that addresses the memory allocation issue
  • Implement input validation and file size limits before processing JPEG files
  • Consider implementing memory limits or sandboxing for image processing operations

Patch Information

Organizations should upgrade metadata-extractor to a version newer than 2.16.0 that contains fixes for this memory allocation vulnerability. Check the GitHub Issue #561 for information about fixed versions and patch details. Review your dependency management configurations (Maven, Gradle, etc.) to ensure the updated library version is properly integrated.

Workarounds

  • Implement strict file size limits on uploaded JPEG files before metadata extraction
  • Add memory allocation limits or timeouts for image processing operations
  • Process untrusted images in isolated containers with resource constraints
  • Validate JPEG file structure and headers before passing to metadata-extractor
  • Deploy rate limiting on file upload endpoints to reduce potential attack impact
bash
# Example JVM memory limits for containerized image processing services
# Set maximum heap size to prevent unbounded memory consumption
java -Xmx512m -Xms256m -jar image-processing-service.jar

# Docker resource constraints example
docker run --memory="512m" --memory-swap="512m" image-processor

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

  • Vulnerability Details
  • TypeDOS

  • Vendor/TechMetadata Extractor

  • SeverityMEDIUM

  • CVSS Score5.5

  • EPSS Probability0.28%

  • Known ExploitedNo
  • CVSS Vector
  • CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H
  • Impact Assessment
  • ConfidentialityLow
  • IntegrityNone
  • AvailabilityHigh
  • CWE References
  • CWE-770
  • Technical References
  • GitHub Issue #561
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