CVE-2025-57810: Parall jsPDF DOS Vulnerability

CVE-2025-57810 Overview

CVE-2025-57810 is a denial of service vulnerability in jsPDF, a popular JavaScript library used to generate PDF documents. Prior to version 3.0.2, the library's addImage method is vulnerable to resource exhaustion attacks when processing maliciously crafted PNG files. An attacker who can control the first argument passed to this method can supply a harmful image file that triggers excessive CPU utilization, leading to denial of service conditions in applications using the vulnerable library.

Critical Impact

Applications processing user-supplied images through jsPDF's addImage method are vulnerable to CPU exhaustion attacks, potentially causing complete service unavailability.

Affected Products

• jsPDF versions prior to 3.0.2
• Node.js applications using the parall:jspdf package
• Web applications implementing jsPDF for client-side PDF generation

Discovery Timeline

• 2025-08-26 - CVE-2025-57810 published to NVD
• 2025-09-09 - Last updated in NVD database

Technical Details for CVE-2025-57810

Vulnerability Analysis

This vulnerability stems from improper input validation (CWE-20) in the jsPDF library's image processing functionality. The addImage method, which is commonly used to embed images into generated PDF documents, does not adequately validate or sanitize image data before processing. When an attacker supplies a specially crafted PNG file, the processing logic enters a computationally expensive operation that consumes excessive CPU resources.

The attack is network-exploitable, requiring no authentication or user interaction to trigger. The impact is limited to availability—the vulnerability does not allow for confidentiality or integrity breaches, but can effectively render affected applications unresponsive.

Root Cause

The root cause of CVE-2025-57810 is inadequate input validation when processing image data passed to the addImage method. The library fails to implement proper checks on PNG file structure and content, allowing malformed or maliciously constructed image data to trigger resource-intensive processing loops. This improper validation of image data enables attackers to exploit algorithmic complexity issues in the image parsing routines.

Attack Vector

The attack vector is network-based and requires the ability to supply image data to an application using jsPDF. Common attack scenarios include:

1. File upload functionality - Applications that accept user-uploaded images for PDF generation
2. URL-based image inclusion - Applications that fetch images from user-supplied URLs
3. API endpoints - Backend services that accept image data as parameters for PDF creation

An attacker crafts a malicious PNG file designed to exploit the vulnerability and submits it through any interface that passes image data to the addImage method. The vulnerability documentation indicates that both direct image data and URLs can be exploited, making this attack applicable to various application architectures.

The vulnerability mechanism involves supplying unsanitized image data to the addImage method's first argument. When jsPDF processes a maliciously crafted PNG file, the parsing logic consumes excessive CPU cycles, causing denial of service. For technical implementation details, refer to the GitHub Security Advisory.

Detection Methods for CVE-2025-57810

Indicators of Compromise

• Abnormal CPU utilization spikes in processes running jsPDF or Node.js applications
• Application timeouts or unresponsiveness during PDF generation operations
• Repeated requests containing PNG image data to PDF generation endpoints
• Process hangs or memory pressure in JavaScript runtime environments

Detection Strategies

• Monitor for unusual CPU consumption patterns in Node.js worker processes or browser contexts using jsPDF
• Implement request rate limiting on endpoints that accept image uploads for PDF generation
• Deploy application performance monitoring to detect anomalous processing times for PDF creation
• Audit application dependencies to identify vulnerable jsPDF versions using software composition analysis tools

Monitoring Recommendations

• Configure alerting thresholds for CPU utilization in containerized or serverless environments running PDF generation workloads
• Implement logging for image processing operations including file sizes and processing duration
• Deploy real-time monitoring for JavaScript runtime health metrics in production environments
• Track and correlate failed or timed-out PDF generation requests with source IP addresses

How to Mitigate CVE-2025-57810

Immediate Actions Required

• Upgrade jsPDF to version 3.0.2 or later immediately
• Audit all applications using jsPDF to identify vulnerable deployments
• Implement server-side timeouts for PDF generation operations as a temporary safeguard
• Consider input validation and sanitization for any user-supplied image data before passing to jsPDF

Patch Information

The vulnerability was addressed in jsPDF version 3.0.2. The fix implements proper validation of image data before processing, preventing maliciously crafted PNG files from triggering excessive CPU consumption. Organizations should review the GitHub commit for technical details on the patch implementation and the official release notes for upgrade guidance.

Workarounds

• Implement server-side image validation using dedicated image parsing libraries before passing data to jsPDF
• Set processing timeouts for PDF generation operations to limit impact of potential exploitation
• Restrict image upload functionality to authenticated users only to reduce attack surface
• Deploy web application firewalls with rules to detect and block malformed PNG files

# Upgrade jsPDF to patched version
npm update jspdf@3.0.2

# Verify installed version
npm list jspdf