CVE-2026-15308 in Python
Summary
by MITRE • 07/09/2026
The incremental HTML parser (html.parser.HTMLParser) allows for CPU denial-of-service through repeated unterminated markup declarations when processing uncontrolled data.
If you want to get best quality of vulnerability data, you may have to visit VulDB.
Analysis
by VulDB Data Team • 07/09/2026
The vulnerability in question involves the incremental HTML parser implementation within Python's standard library, specifically the html.parser.HTMLParser class which is susceptible to CPU denial-of-service attacks when encountering malformed or uncontrolled input data containing repeated unterminated markup declarations. This flaw represents a critical security concern as it allows an attacker to consume excessive computational resources through carefully crafted malicious input that causes the parser to enter inefficient processing loops.
The technical implementation of this vulnerability stems from how the HTMLParser handles markup declarations without proper termination sequences. When the parser encounters repeated unterminated declarations such as incomplete comments, processing instructions, or doctype declarations, it enters a state where it continuously attempts to parse and reparse these malformed elements. This behavior creates an infinite loop or extremely long processing time that consumes CPU cycles rapidly, effectively causing a denial-of-service condition for applications relying on this parser.
From a cybersecurity perspective, this vulnerability aligns with CWE-400, which categorizes unchecked resource consumption as a weakness leading to denial-of-service conditions. The attack pattern follows typical resource exhaustion methodologies described in MITRE ATT&CK framework under the T1499 category for resource exhaustion attacks. The vulnerability demonstrates how seemingly benign parsing operations can become weaponized when processing untrusted input data without proper validation or rate limiting mechanisms.
The operational impact of this vulnerability extends beyond simple service disruption to potentially affect application availability and system stability. Applications that process user-generated content, web scraping services, or any system relying on HTML parsing for data ingestion become vulnerable to this attack vector. The computational overhead can escalate rapidly depending on the input size and complexity of malformed markup sequences, potentially causing cascading failures in high-traffic systems where multiple concurrent parsing operations occur simultaneously.
Organizations should implement multiple mitigation strategies to address this vulnerability effectively. Input validation represents the primary defense mechanism, requiring applications to sanitize or reject any input containing suspicious markup patterns before processing with HTMLParser. Additionally, implementing timeout mechanisms and resource limits for parsing operations can prevent indefinite CPU consumption. The Python standard library itself has addressed similar issues in recent versions through improved parser behavior and enhanced error handling. System administrators should also consider monitoring for unusual CPU usage patterns that might indicate exploitation attempts, while developers should regularly update their Python environments to benefit from security patches and improved parsing algorithms that mitigate these resource exhaustion scenarios.