CVE-2026-71488 in commonmark
Summary
by MITRE • 08/07/2026
league/commonmark is a PHP library for parsing and rendering CommonMark Markdown. From 0.6.0 until 2.9.0, specially crafted Markdown lines can cause the parser to have quadratic time complexity when converting, because several parsing paths repeatedly rescan growing portions of a line to translate between character positions and byte positions, and the Autolink extension can also copy and validate the remaining line at every URL-like prefix, allowing an attacker who can submit Markdown for conversion to consume disproportionate CPU time with a comparatively small request. This issue is fixed in 2.9.0.
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Analysis
by VulDB Data Team • 08/07/2026
The league/commonmark PHP library vulnerability represents a critical performance degradation issue affecting versions 0.6.0 through 2.9.0, where specially crafted markdown input can trigger quadratic time complexity during parsing operations. This vulnerability stems from fundamental flaws in how the parser handles character position and byte position conversions within markdown lines, creating a scenario where processing time increases exponentially with input size rather than linearly as expected.
The technical flaw manifests through multiple parsing paths that repeatedly rescan growing portions of input lines when performing character-to-byte position translations, combined with the Autolink extension's behavior of copying and validating remaining line content at every URL-like prefix. This dual mechanism creates a perfect storm where each additional character in the malicious input exponentially increases processing overhead, allowing attackers to consume disproportionate CPU resources with relatively small input payloads.
This vulnerability directly maps to CWE-798, which addresses the use of hard-coded credentials and weak configurations, though more specifically aligns with CWE-400, concerning unchecked resource consumption. The operational impact extends beyond simple performance degradation, as this issue enables denial-of-service attacks that can overwhelm server resources and potentially disrupt legitimate service operations. Attackers can exploit this vulnerability by submitting carefully crafted markdown content that causes the parser to consume excessive computational resources.
The Autolink extension's behavior exacerbates the situation by performing validation operations at every potential URL prefix, creating additional processing overhead that compounds with each character added to the malicious input. This design flaw allows attackers to craft inputs where the time complexity grows quadratically rather than linearly, making even modest input sizes result in substantial CPU consumption. The vulnerability affects any application that processes user-submitted markdown content through this library, particularly web applications, content management systems, and any platform accepting markdown input from untrusted sources.
Mitigation strategies should prioritize immediate upgrading to version 2.9.0 or later, which contains the necessary fixes for this vulnerability. Organizations should also implement input validation and rate limiting measures to prevent abuse of markdown parsing functionality, while monitoring for unusual CPU usage patterns that might indicate exploitation attempts. The fix addresses the core parsing inefficiencies by optimizing character position calculations and preventing redundant rescan operations, ensuring that processing time scales linearly with input size rather than exponentially.
This vulnerability demonstrates the importance of proper resource management in text parsing libraries and highlights how seemingly minor implementation details can create significant security risks. The issue aligns with ATT&CK technique T1496, which covers resource exhaustion attacks, and emphasizes the need for comprehensive testing of parsing libraries against malicious inputs to prevent such performance degradation scenarios. Security teams should conduct thorough assessments of their applications using this library to identify potential exposure points and implement appropriate safeguards to protect against this specific class of denial-of-service attacks.