CVE-2026-12600 in Poppler
Summary
by MITRE • 08/25/2026
Denial-of-service (DoS) vulnerability in the internal JPEG2000 (JPX) decoding implementation of the Poppler fork developed by Innodata Labs. When an application processes an untrusted PDF file containing specially crafted JPXDecode images, a remote attacker can cause uncontrolled memory consumption. The flaw occurs in the JPXStream::readCodestream() function, where values controlled from the SIZ segment (such as img.nComps) are used for the memory allocation of tiles and components without adequate validation. This allows an attacker to force excessive memory allocation and cause a resource exhaustion, ultimately causing the pdftoppm process to terminate due to out-of-memory (OOM) conditions.
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Analysis
by VulDB Data Team • 08/25/2026
The identified vulnerability represents a critical denial-of-service flaw within the internal JPEG2000 decoding implementation of the Poppler fork maintained by Innodata Labs. This security issue specifically affects applications that utilize this library to parse and render PDF documents containing embedded images encoded with the JPXDecode filter. The core technical deficiency lies in the handling of metadata extracted from the image stream, particularly within the SIZ segment which defines the characteristics of the JPEG2000 codestream. When a maliciously crafted PDF is processed, an attacker can manipulate specific fields such as img.nComps to dictate memory allocation parameters without sufficient validation or bounds checking. This lack of rigorous input sanitization allows for the exploitation of uncontrolled resource consumption during the decoding process.
The operational mechanism of this vulnerability centers on the JPXStream::readCodestream function. During the initialization phase, the decoder reads values from the SIZ segment to determine the necessary memory footprint for allocating tiles and components required for image rendering. Because these values are directly derived from untrusted external input without adequate verification against realistic limits or system constraints, an attacker can supply excessively large integers. The application subsequently attempts to allocate a corresponding amount of RAM based on these inflated parameters. This action triggers immediate and excessive memory consumption by the process responsible for converting PDFs to images, such as pdftoppm.
The impact of this vulnerability is primarily characterized by resource exhaustion leading to service disruption. As the vulnerable component attempts to fulfill the massive allocation request, it rapidly depletes available system memory resources. This scenario typically results in an out-of-memory condition that forces the operating system or the application itself to terminate the process abruptly. For services relying on continuous PDF processing, such as document management systems or web-based previewers, this can lead to significant availability issues. The attack does not require code execution but effectively denies legitimate users access to the service by crashing the underlying rendering engine through simple resource starvation techniques.
From a classification perspective, this vulnerability aligns with CWE-400 Uncontrolled Resource Consumption and CWE-789 Memory Allocation with Untrusted Input. It also maps to MITRE ATT&CK technique T1499 Endpoint Denial of Service, specifically under the sub-category of Resource Exhaustion: OOM Crash. The exploitation vector is remote if the PDF file can be delivered via network services such as email attachments or web uploads, making it a viable threat for automated denial-of-service campaigns targeting document processing infrastructure.
Mitigation strategies should focus on implementing strict validation checks within the JPXStream::readCodestream function before any memory allocation occurs. Developers must enforce upper bounds on all values derived from the SIZ segment, ensuring they do not exceed reasonable limits defined by system architecture or application requirements. Additionally, integrating resource monitoring and limiting mechanisms can help contain the impact of such attacks in production environments where patching may take time to deploy. Regular security audits of image parsing libraries are essential to identify similar patterns of unvalidated input leading to memory issues across other components of the stack.