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Vulnerability Database/CVE-2025-70303

CVE-2025-70303: GPAC Heap Overflow DoS Vulnerability

CVE-2025-70303 is a heap overflow vulnerability in GPAC v2.4.0 that enables attackers to trigger a Denial of Service through malicious MP4 files. This article covers technical details, affected versions, and mitigation.

Published:

CVE-2025-70303 Overview

A heap overflow vulnerability exists in the uncv_parse_config() function of GPAC v2.4.0. This memory corruption flaw allows attackers to cause a Denial of Service (DoS) condition by supplying a specially crafted MP4 file to the affected application. GPAC is a widely-used open-source multimedia framework for encoding, streaming, and processing audio/video content.

Critical Impact

Processing malicious MP4 files can trigger a heap overflow, leading to application crashes and service disruption for multimedia processing workflows.

Affected Products

  • GPAC v2.4.0
  • Applications and services using GPAC v2.4.0 for multimedia processing
  • Systems processing untrusted MP4 files with vulnerable GPAC versions

Discovery Timeline

  • 2026-01-15 - CVE CVE-2025-70303 published to NVD
  • 2026-01-16 - Last updated in NVD database

Technical Details for CVE-2025-70303

Vulnerability Analysis

This vulnerability is classified as CWE-122 (Heap-based Buffer Overflow), a memory corruption issue where data is written beyond the boundaries of allocated heap memory. The flaw resides specifically in the uncv_parse_config() function, which handles parsing of uncv (uncompressed video) configuration data within MP4 container files.

When GPAC processes a maliciously crafted MP4 file, the uncv_parse_config() function fails to properly validate the size of configuration data before copying it to a heap-allocated buffer. This allows an attacker to provide oversized or malformed configuration parameters that overflow the allocated memory region, corrupting adjacent heap structures and ultimately causing the application to crash.

The attack requires local access and user interaction, meaning the victim must open or process the malicious MP4 file. While the vulnerability does not enable code execution or data theft, it poses a significant availability risk, particularly for automated multimedia processing pipelines that handle untrusted content.

Root Cause

The root cause is insufficient bounds checking in the uncv_parse_config() function when parsing configuration atoms from MP4 files. The function allocates a fixed-size buffer on the heap but does not adequately validate that incoming configuration data fits within the allocated space before performing memory copy operations. This missing boundary validation allows heap memory corruption when processing specially crafted input.

Attack Vector

The attack vector requires local access with user interaction. An attacker must craft a malicious MP4 file containing oversized or malformed uncv configuration data and convince a user or automated system to process this file using GPAC v2.4.0. The exploitation occurs during the file parsing phase when the vulnerable uncv_parse_config() function processes the malformed configuration atom.

The vulnerability mechanism involves crafting an MP4 file with a malformed uncv configuration atom that specifies or contains more data than the allocated heap buffer can accommodate. When GPAC parses this file, the overflow occurs during the memory copy operation in uncv_parse_config(), corrupting heap metadata and causing an application crash. Technical details and proof-of-concept documentation are available in the GitHub PoC Documentation.

Detection Methods for CVE-2025-70303

Indicators of Compromise

  • Application crashes in GPAC processes, particularly during MP4 file processing operations
  • Heap corruption error messages or memory-related exceptions in GPAC logs
  • Unusual MP4 files with malformed uncv configuration atoms in processing queues
  • Repeated crash patterns tied to specific MP4 files being processed

Detection Strategies

  • Monitor for GPAC process crashes and analyze crash dumps for heap corruption signatures in uncv_parse_config()
  • Implement file integrity checks and sandboxing for MP4 files before processing with GPAC
  • Deploy application-level monitoring to detect abnormal terminations of multimedia processing services
  • Use heap canary or guard page mechanisms to detect heap overflow attempts at runtime

Monitoring Recommendations

  • Configure process monitoring to alert on unexpected GPAC service terminations
  • Enable core dump collection for post-mortem analysis of crash events
  • Monitor file ingestion pipelines for MP4 files with unusual metadata structures
  • Implement logging around multimedia file processing operations to correlate crashes with specific input files

How to Mitigate CVE-2025-70303

Immediate Actions Required

  • Upgrade GPAC to a patched version that addresses the heap overflow in uncv_parse_config()
  • Restrict processing of untrusted MP4 files until the update is applied
  • Implement input validation to reject MP4 files from untrusted sources
  • Deploy GPAC in sandboxed environments to limit the impact of exploitation

Patch Information

Organizations should monitor the GPAC project for security updates addressing this heap overflow vulnerability. Check the official GPAC repository and release notes for patched versions. For technical details about the vulnerability, refer to the GitHub PoC Documentation.

Workarounds

  • Avoid processing MP4 files from untrusted or unknown sources until a patch is available
  • Run GPAC in a containerized or sandboxed environment to contain potential crashes
  • Implement file validation using alternative tools before passing MP4 files to GPAC
  • Consider temporarily disabling uncv codec support if not required for operations
bash
# Example: Running GPAC in a restricted environment
# Use containerization to limit impact of potential crashes
docker run --rm --read-only --memory="512m" --cpus="1" \
    -v /path/to/trusted/files:/input:ro \
    gpac/gpac:latest MP4Box -info /input/video.mp4

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

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