CVE-2026-41168 Overview
pypdf is a free and open-source pure-python PDF library used for reading, manipulating, and creating PDF files. A denial of service vulnerability exists in versions prior to 6.10.1 that allows an attacker to craft a malicious PDF document which causes excessive runtime consumption when processed. The vulnerability is triggered through specially crafted cross-reference streams containing incorrect large /Size values or object streams with incorrect large /N values.
Critical Impact
An attacker can craft a malicious PDF file that causes application hangs or resource exhaustion when processed by pypdf, potentially impacting availability of services that rely on PDF processing.
Affected Products
- pypdf versions prior to 6.10.1
- Applications and services that use pypdf for PDF processing
- Python-based document processing pipelines utilizing vulnerable pypdf versions
Discovery Timeline
- 2026-04-22 - CVE CVE-2026-41168 published to NVD
- 2026-04-22 - Last updated in NVD database
Technical Details for CVE-2026-41168
Vulnerability Analysis
This vulnerability is classified as CWE-834 (Excessive Iteration), a type of algorithmic complexity attack that falls under the Denial of Service category. The issue arises when pypdf processes PDF files containing malformed cross-reference (xref) streams or object streams with intentionally inflated size parameters.
When pypdf encounters a cross-reference stream with an excessively large /Size value, or an object stream with an abnormally large /N value, the library attempts to process these inflated parameters without proper validation. This results in extensive iteration loops and memory allocation attempts that can cause significant CPU consumption and potentially lead to application hangs or crashes.
The network-accessible nature of this vulnerability means that any web application, API endpoint, or service that accepts PDF uploads and processes them using vulnerable pypdf versions is at risk. An attacker requires no authentication or special privileges to exploit this vulnerability—they simply need to submit a crafted PDF file.
Root Cause
The root cause lies in insufficient validation of the /Size parameter in cross-reference streams and the /N parameter in object streams within the PDF parsing logic. Prior to version 6.10.1, pypdf did not properly bounds-check these values before initiating processing loops, allowing attackers to force excessive iterations through crafted parameter values.
Attack Vector
The attack vector is network-based, requiring no user interaction beyond the initial PDF file upload or submission. An attacker crafts a PDF document containing:
- Cross-reference streams with intentionally large /Size values that do not correspond to the actual number of objects in the PDF
- Object streams with inflated /N values that exceed the actual object count
When a vulnerable pypdf instance attempts to parse such a document, it enters lengthy processing loops attempting to handle the declared (but non-existent) objects, leading to denial of service through resource exhaustion.
The vulnerability mechanism involves malformed PDF structure parameters that trigger excessive iteration. When pypdf reads the cross-reference stream, it trusts the /Size value to allocate resources and iterate over expected objects. Similarly, object streams declare their object count via /N. By providing artificially large values for these parameters, an attacker forces the library into computationally expensive loops. For detailed technical implementation, refer to the GitHub Security Advisory GHSA-jj6c-8h6c-hppx.
Detection Methods for CVE-2026-41168
Indicators of Compromise
- Unusual CPU utilization spikes when processing PDF files
- Application timeouts or hangs during PDF parsing operations
- Memory usage anomalies in PDF processing services
- PDF files with abnormally large /Size or /N parameters in stream dictionaries
Detection Strategies
- Implement file analysis to detect PDF documents with suspicious cross-reference stream parameters
- Monitor application performance metrics during PDF processing to identify resource exhaustion patterns
- Deploy application-level timeouts for PDF parsing operations to prevent indefinite hangs
- Use static analysis tools to scan PDF files for malformed structure parameters before processing
Monitoring Recommendations
- Enable logging for PDF processing duration and resource consumption
- Set up alerts for PDF processing operations exceeding expected time thresholds
- Monitor memory and CPU utilization patterns for services handling PDF uploads
- Track and analyze failed or timed-out PDF processing attempts
How to Mitigate CVE-2026-41168
Immediate Actions Required
- Upgrade pypdf to version 6.10.1 or later immediately
- Implement processing timeouts for all PDF parsing operations as a defense-in-depth measure
- Review and audit all applications and services that use pypdf for PDF processing
- Consider implementing file size and complexity limits for PDF uploads
Patch Information
The vulnerability has been fixed in pypdf version 6.10.1. The fix introduces proper validation of /Size and /N parameters to prevent excessive iteration. Organizations should update their pypdf installations immediately.
For more information, see:
Workarounds
- Apply the changes from the security patch manually if immediate upgrade is not possible
- Implement application-level timeouts for PDF processing to limit resource exhaustion impact
- Use input validation to reject PDF files with suspicious stream parameters before pypdf processing
- Consider sandboxing PDF processing operations to limit resource consumption
# Upgrade pypdf to patched version
pip install --upgrade pypdf>=6.10.1
# Verify installed version
pip show pypdf | grep Version
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.
