A flaw was found in FFmpeg’s TensorFlow backend within the libavfilter/dnn_backend_tf.c source file. The issue occurs in the dnn_execute_model_tf() function, where a task object is freed multiple times in certain error-handling paths. This redundant memory deallocation can lead to a double-free condition, potentially causing FFmpeg or any application using it to crash when processing TensorFlow-based DNN models. This results in a denial-of-service scenario but does not allow arbitrary code execution under normal conditions.
This vulnerability carries a LOW severity rating with a CVSS v3.1 score of 3.3, requiring local system access to exploit with relatively low complexity though user interaction is required and does not require pre-existing privileges . The vulnerability impacts and limited availability for affected systems. Impacting 1 product from ffmpeg organizations running these solutions should prioritize assessment and patching.
Reported in 2026, this vulnerability emerged during an era marked by increased sophistication in supply chain attacks, cloud infrastructure vulnerabilities, and software-as-a-service (SaaS) security challenges. Security practices during this period emphasized zero-trust architectures, container security, and API protection.
2026-02-18T21:16:20.453
2026-02-26T22:32:44.470
Analyzed
CVSSv3.1: 3.3 (LOW)
SecUtils normalizes and enriches National Vulnerability Database (NVD) records by standardizing vendor and product identifiers, aggregating vulnerability metadata from both NVD and MITRE sources, and providing structured context for security teams. For ffmpeg's affected products, we extract Common Platform Enumeration (CPE) data, Common Weakness Enumeration (CWE) classifications, CVSS severity metrics, and reference data to enable rapid vulnerability prioritization and asset correlation. This record contains no exploit code, proof-of-concept instructions, or attack methodologies—only defensive intelligence necessary for patch management, risk assessment, and security operations.