CVE-2026-111166 in libmikmod
Summary
by MITRE • 10/15/2026
libmikmod through 3.3.15 contains a heap out-of-bounds read vulnerability in the IMF_Load() loader that allows attackers to read beyond allocated memory by supplying a crafted IMF module. Attackers can enable the linear-period header flag and map notes to out-of-range samples, causing noteindex indexing far past the heap allocation and crashing applications that load the file.
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Analysis
by VulDB Data Team • 10/16/2026
The vulnerability identified in libmikmod versions through 3.3.15 represents a critical memory safety flaw within the IMF module loader, specifically located in the IMF_Load function. This library is widely utilized for playing various modular music formats on Linux and other Unix-like systems, making it a common dependency in audio processing applications and games. The core of the issue lies in how the software handles specific header flags and note-to-sample mappings defined within an IMF file structure. When a malicious actor constructs a crafted IMF module that enables the linear-period header flag while simultaneously mapping notes to sample indices that exceed the valid range, the library fails to perform adequate bounds checking before accessing memory. This oversight allows for a heap out-of-bounds read operation, where the application attempts to retrieve data from memory locations beyond those allocated for the specific audio samples associated with the module file.
From a technical perspective, this flaw is classified under CWE-125, which denotes Out-of-Bounds Read vulnerabilities. The mechanism of exploitation relies on the attacker controlling the noteindex values within the IMF header or pattern data. By setting these indices to values that are significantly larger than the number of samples actually loaded into memory, the program calculates a pointer offset that points outside the bounds of the heap allocation buffer. When the audio engine attempts to read from this invalid address to generate sound output, it accesses arbitrary memory contents. This behavior is not merely theoretical; it has been confirmed to cause immediate application crashes due to segmentation faults or access violations when the operating system detects the illegal memory access attempt.
The operational impact of this vulnerability extends beyond simple denial-of-service scenarios involving application instability. While a crash is the most direct consequence, heap out-of-bounds reads can potentially lead to information disclosure if the attacker can control the timing and frequency of the read operations to exfiltrate sensitive data residing in adjacent memory regions. Although exploitation for arbitrary code execution via this specific vector is less common than with write vulnerabilities, it remains a significant risk factor depending on how the host application handles subsequent errors or utilizes the corrupted state. In environments where libmikmod processes untrusted audio files from external sources, such as online game servers or media streaming platforms, an attacker could trigger these crashes remotely by distributing malicious IMF modules, thereby disrupting service availability and potentially destabilizing the underlying system if cascading failures occur in complex software stacks.
This vulnerability aligns with MITRE ATT&CK techniques related to resource hijacking and denial of service, specifically under tactics that aim to disrupt the availability of services or applications. The lack of proper input validation on structural elements like sample indices highlights a gap in secure coding practices regarding memory management for external inputs. To mitigate this risk, developers integrating libmikmod should ensure they are using patched versions released after version 3.3.15 where bounds checking logic has been strengthened within the IMF loader. For applications that cannot immediately upgrade, implementing strict validation of sample indices against known valid ranges before passing them to the library functions serves as a necessary defensive measure. Additionally, employing memory protection mechanisms such as Address Space Layout Randomization and heap sanitizers during development can help detect such anomalies early in the software lifecycle, preventing vulnerable binaries from reaching production environments where they could be exploited by adversaries seeking to compromise system stability or confidentiality.