PyPDF Security Flaw (CVE-2025-62708): Malicious PDFs Can Trigger High Memory Usage

A critical security vulnerability in the widely-used PyPDF library allows attackers to craft malicious PDFs that force a target system to consume large amounts of memory, potentially leading to denial-of-service conditions. The flaw, tracked as CVE-2025-62708, is triggered when a PDF containing a specially crafted content stream using the LZWDecode filter is parsed. This presents a direct risk to any application or service that processes untrusted PDF files using vulnerable versions of the library.

The vulnerability specifically affects the PyPDF package, a fundamental tool for Python developers working with PDF documents. The security advisory indicates that the issue was present in versions prior to 6.1.3. The update from version 6.0.0 to 6.10.0, as seen in a GitHub dependency management pull request, is a direct response to this security patch. The fix has been available since the release of PyPDF version 6.1.3, highlighting a significant gap for projects that have not yet updated their dependencies.

The implications are broad, as PyPDF is embedded in countless data processing pipelines, web applications, and automated systems. Organizations relying on outdated versions are exposed to resource exhaustion attacks. The silent nature of the attack—where a single malicious file can degrade or crash a service—makes it a potent tool for disruption. This incident underscores the persistent security risks within software supply chains and the critical importance of timely dependency updates to mitigate such memory-based exploitation vectors.