CVE-2026-92822 in Red Hat
Summary
by MITRE • 10/22/2026
A flaw was found in libmodulemd. When parsing module metadata, the xmd field is converted into nested GVariant values through recursive YAML mapping and sequence helpers without a recursion-depth or node-count limit. An attacker who can supply crafted modulemd YAML with deeply nested xmd content can cause stack exhaustion or excessive resource consumption, resulting in a denial of service.
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Analysis
by VulDB Data Team • 10/22/2026
The vulnerability identified in libmodulemd represents a critical input validation failure rooted in the handling of untrusted data during the parsing of module metadata files. Specifically, the flaw resides within the processing logic for the xmd field, which is designed to store arbitrary extension metadata. When this field contains YAML content, the library employs recursive helper functions to map and sequence these values into nested GVariant structures. This architectural decision allows for complex hierarchical data representation but introduces a significant security risk when depth or volume constraints are not enforced. The absence of recursion-depth limits or node-count thresholds means that the parser will continue to allocate stack space and memory resources indefinitely as long as the input YAML maintains its nested structure, regardless of how impractical or malicious such nesting may be.
From a technical perspective, this issue is classified under CWE-787: Out-of-bounds Write if it leads to buffer overflows due to stack exhaustion, though more commonly in modern managed contexts like GVariant handling, it manifests as CWE-400: Uncontrolled Resource Consumption or CWE-125: Out-of-Bounds Read depending on the specific memory management implementation details of the underlying C library. The core mechanism involves recursive function calls that expand with each level of YAML nesting. Without a counter to track recursion depth or a maximum node limit, an attacker can craft a modulemd file where the xmd field contains deeply nested lists and mappings. As libmodulemd processes this input, it pushes frames onto the call stack for every layer of indentation. In environments with limited default stack sizes, such as many Linux distributions running dnf or rpm-based package managers, this rapid accumulation quickly exceeds available memory, leading to a segmentation fault or immediate process termination.
The operational impact of this vulnerability is primarily focused on availability rather than confidentiality or integrity. An attacker who can supply crafted modulemd YAML files—potentially through malicious repositories, compromised mirrors, or social engineering tactics involving the installation of specific software modules—can trigger a denial of service condition. This results in the crash of applications that rely on libmodulemd for metadata parsing, such as DNF (Dandified YUM) and RPM tools used for package management on Fedora, RHEL, CentOS, and other Red Hat-based distributions. In automated environments or systems with strict uptime requirements, repeated exploitation attempts could lead to service instability or require manual intervention to clear corrupted states or restart affected services. While the vulnerability does not directly allow remote code execution in this context, it effectively neutralizes the package management infrastructure by rendering it unusable during parsing operations involving maliciously crafted inputs.
This behavior aligns with ATT&CK technique T1496: Resource Hijacking, specifically sub-technique T1496.002: Cloud Infrastructure Discovery or more accurately in this local context, resource exhaustion leading to service disruption. It also reflects common pitfalls described in CWE-755: Improper Handling of Unexpected Data Type if the parser fails to reject deeply nested structures that exceed expected complexity bounds. The lack of sanitization for structural depth is a classic example of insufficient input validation where the system assumes metadata will remain reasonably shallow, failing to account for adversarial inputs designed specifically to exploit recursive processing limits.
Mitigation strategies must address both immediate remediation and long-term defensive coding practices. For end-users, updating libmodulemd to a patched version that implements strict recursion depth limits is essential. Developers integrating or maintaining similar libraries should enforce maximum nesting levels during YAML parsing, rejecting any input that exceeds predefined thresholds for key-value pairs or array depths. Implementing explicit counters in recursive functions and returning early with an error code when these limits are breached prevents stack overflow scenarios. Additionally, adopting safer parsing alternatives that do not rely on deep recursion, such as iterative parsers or stream-based processing where feasible, can further reduce the attack surface. Security testing pipelines should include fuzzing campaigns targeting metadata parsers to detect similar unbounded resource consumption issues before they reach production environments.