CVE-2023-6277 in LibTIFF
Summary
by MITRE • 11/24/2023
An out-of-memory flaw was found in libtiff. Passing a crafted tiff file to TIFFOpen() API may allow a remote attacker to cause a denial of service via a craft input with size smaller than 379 KB.
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Analysis
by VulDB Data Team • 10/18/2025
The vulnerability identified as CVE-2023-6277 represents a critical out-of-memory flaw within the libtiff library, a widely used software component for handling tag image file format data. This issue manifests when the TIFFOpen() application programming interface receives a specially crafted tiff file as input, creating a scenario where memory allocation operations can spiral out of control. The vulnerability specifically affects systems that process tiff image files through the libtiff library implementation, making it particularly dangerous in environments where automated image processing or file validation occurs. Security researchers have determined that the malicious input can be as small as 379 kilobytes, demonstrating the efficiency with which this flaw can be exploited to cause system instability. The vulnerability stems from inadequate input validation and memory management within the library's parsing routines, where the software fails to properly handle malformed or crafted data structures that trigger excessive memory consumption patterns.
The technical exploitation of CVE-2023-6277 occurs when an attacker crafts a specific tiff file that contains malformed metadata or compressed data structures designed to cause the TIFFOpen() function to allocate progressively larger memory blocks during parsing operations. This flaw operates at the memory management level within the libtiff library implementation, where the software's internal buffer handling mechanisms do not adequately constrain memory allocation based on input parameters. The vulnerability's classification aligns with CWE-772, which addresses insufficient resource pool sizing, and CWE-400, which covers unspecified resource exhaustion. Attackers can leverage this weakness to perform denial of service attacks by simply providing a maliciously constructed tiff file to any application that relies on libtiff for image processing. The small size requirement of the malicious input makes this vulnerability particularly dangerous for web applications, file upload systems, and automated processing pipelines that may not perform adequate input sanitization before passing files to libtiff for parsing.
The operational impact of CVE-2023-6277 extends beyond simple denial of service, as it can disrupt critical services across multiple domains including web applications, content management systems, image processing platforms, and digital asset management solutions. When exploited, this vulnerability can cause applications to consume excessive memory resources, leading to system crashes, application hangs, or complete service unavailability. The vulnerability affects any system running software that utilizes libtiff for tiff file processing, which includes numerous enterprise applications, web servers, and multimedia processing tools. From an attack perspective, this flaw maps to ATT&CK technique T1499.004, which involves network denial of service attacks, and T1595.001, covering reconnaissance for vulnerabilities. The low resource requirement for exploitation means that attackers can quickly overwhelm systems with minimal computational overhead, making this vulnerability particularly attractive for large-scale denial of service campaigns. Organizations using libtiff in their infrastructure may experience cascading failures if multiple applications depend on the same vulnerable library instance.
Mitigation strategies for CVE-2023-6277 require immediate attention through patch management, input validation, and system hardening measures. The primary solution involves updating to the latest version of libtiff that includes fixes for this memory allocation vulnerability, with vendors releasing patches specifically addressing the out-of-memory conditions in TIFFOpen() operations. Organizations should implement input validation measures that filter or reject tiff files based on size limits and structural integrity checks before processing them through libtiff. Network segmentation and access controls can help limit the impact of potential exploitation attempts by restricting access to systems that process tiff files. Additionally, implementing memory monitoring and resource limiting mechanisms can help detect and prevent exploitation attempts before they cause complete service disruption. Security teams should also consider deploying intrusion detection systems that can identify suspicious file upload patterns or memory allocation anomalies that may indicate exploitation attempts. The vulnerability serves as a reminder of the importance of proper resource management in image processing libraries and highlights the need for comprehensive security testing of third-party components used in enterprise applications.