CVE-2026-107168 in Red Hat
Summary
by MITRE • 10/07/2026
A flaw was found in m17n-lib. By providing crafted input containing an invalid UTF-8 character sequence, an attacker can cause the text parsing function to enter an infinite loop. This issue leads to sustained high CPU utilization, resulting in a Denial of Service (DoS) for the affected application.
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Analysis
by VulDB Data Team • 10/07/2026
The vulnerability identified within m17n-lib represents a significant reliability risk due to improper input validation mechanisms during character encoding processing. Specifically, the flaw resides in how the library handles text parsing when it encounters malformed UTF-8 sequences. In standard software development practices, parsers are expected to validate incoming byte streams against defined encoding standards before proceeding with further operations. However, in this instance, the logic governing the detection and handling of invalid UTF-8 character sequences contains a logical error that fails to terminate gracefully upon encountering corrupted data. Instead of raising an exception or returning an error code indicative of malformed input, the parsing function enters an infinite loop. This behavior is particularly dangerous because it allows any entity capable of supplying crafted input to trigger this state, effectively bypassing normal execution flows and consuming system resources indefinitely.
From a technical perspective, this issue aligns with CWE-835, which describes loops that do not terminate or consume excessive resources due to logic errors in loop conditions. The root cause is likely an off-by-one error or incorrect boundary checking within the UTF-8 decoding routine. When the parser encounters a byte sequence that does not conform to valid UTF-8 rules, it should ideally reject the input immediately. Instead, the flawed logic causes the pointer or index variable used for iteration to either decrement incorrectly or fail to advance past the problematic bytes, resulting in repeated processing of the same invalid data segment. This creates an infinite loop where CPU cycles are continuously consumed without making progress toward completing the parsing task. Such vulnerabilities are often categorized under CWE-20 Improper Input Validation because the system fails to verify that input meets specified requirements before using it.
The operational impact of this vulnerability is primarily a Denial of Service, corresponding to MITRE ATT&CK technique T1499 Endpoint Denial of Service. By exploiting this flaw, an attacker can cause sustained high CPU utilization on the host running the affected application. This resource exhaustion prevents legitimate users from accessing services or performing tasks that require processing power. In web applications or network-facing services that utilize m17n-lib for text normalization and encoding conversion, a single crafted request could hang a worker thread indefinitely. If multiple such requests are sent concurrently, it can lead to complete service unavailability as all available threads become occupied with the infinite loops. This not only disrupts business continuity but also increases infrastructure costs due to wasted computational resources and potential need for manual intervention or restart of affected services.
Mitigation strategies must focus on both immediate remediation and long-term defensive coding practices. The most effective solution is for developers to update m17n-lib to a patched version that corrects the loop termination logic and ensures strict validation of UTF-8 sequences before processing. For applications unable to upgrade immediately, input sanitization at the application layer can serve as a temporary workaround by filtering out or rejecting strings containing non-standard byte patterns before they reach the vulnerable library function. Additionally implementing timeouts for text parsing operations can limit the impact of such attacks by forcibly terminating processes that exceed expected execution durations. Security teams should also monitor system metrics for anomalous CPU spikes associated with specific application endpoints, which may indicate active exploitation attempts. Regular code audits focusing on input validation and loop conditions are essential to prevent similar logic errors in future development cycles.