CVE-2026-118446 in pybddisasm
Summary
by MITRE • 11/03/2026
A use-after-free vulnerability in the pybddisasm Python bindings affects array-valued members of INSTRUX objects, including ND_OPERAND arrays. These arrays are exposed as Python lists whose elements reference memory owned by the parent INSTRUX object. Retaining a list or an element does not keep the parent allocation alive. Accessing an element after the parent INSTRUX object has been freed therefore accesses freed memory. Depending on how the element is used and whether the freed allocation has been reused, this may expose process memory or cause the Python process to crash. Exploitation requires an application to retain and subsequently access an array element after the parent object has been freed. The pybddisasm package is no longer maintained.
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Analysis
by VulDB Data Team • 11/03/2026
The vulnerability identified in the pybddisasm Python bindings represents a critical memory safety failure rooted in improper resource management within the interface between C-based disassembly libraries and the Python runtime environment. Specifically, this use-after-free flaw affects array-valued members of INSTRUX objects, with particular emphasis on ND_OPERAND arrays which are exposed to developers as standard Python lists. The core technical deficiency lies in how memory ownership is handled during object lifecycle management. When these arrays are converted into Python list structures, the individual elements within those lists maintain references to underlying memory allocations that belong exclusively to their parent INSTRUX object. However, the garbage collection mechanism and reference counting logic fail to establish a strong dependency between the child array elements and the parent container. Consequently, retaining a reference to an element or the entire list does not increment the reference count of the parent allocation, leading to a scenario where the parent can be deallocated while children remain active references in memory.
From a technical perspective, this flaw allows for access to freed memory when an application retains and subsequently accesses an array element after the parent INSTRUX object has been destroyed by Python's garbage collector or explicit deletion calls. The operational impact of such a vulnerability is severe and multifaceted depending on the execution context and heap state. If the freed memory allocation has not yet been reallocated for other purposes, accessing it may result in reading stale data that could expose sensitive process memory contents to an attacker. This scenario aligns with CWE-416, Use After Free, which describes situations where a pointer is used after it has become invalid due to being released without updating the pointer value. In more volatile heap environments, if the freed block has been reused by other allocations, accessing the stale reference can lead to unpredictable behavior, including data corruption or immediate termination of the Python process through segmentation faults or access violations.
The exploitation vector for this vulnerability requires a specific sequence of operations where an application must first obtain a reference to an array element from an INSTRUX object and then allow that parent object to be freed before attempting to read or write to the retained element. This condition suggests that while the vulnerability is present in the library's core logic, successful exploitation depends on the timing and usage patterns within the consuming Python script. Given that pybddisasm is no longer maintained, there are no official patches available to rectify this memory management defect. The lack of active development means that users relying on this package for disassembly tasks face persistent risks without a clear path to remediation through vendor updates.
Mitigation strategies must therefore focus on architectural changes and defensive coding practices rather than simple patching. Organizations currently using pybddisasm should prioritize migrating to actively maintained alternatives such as Capstone or other supported disassembly frameworks that enforce strict memory ownership models between native libraries and Python bindings. For applications where migration is not immediately feasible, developers can implement wrapper layers that ensure the parent INSTRUX object remains alive for the duration of any operation involving its child arrays. This involves manually managing reference counts or using context managers to guarantee lifecycle alignment. Additionally, employing static analysis tools and dynamic memory checkers like Valgrind during development phases can help identify similar patterns in custom bindings before they reach production environments.
This incident highlights broader implications for software security regarding the integration of low-level system libraries with high-level managed languages. It underscores the importance of adher to industry standards such as CWE-416 and considering ATT&CK techniques related to memory corruption, specifically those involving exploitation of binary vulnerabilities to gain unauthorized access or cause denial of service. Security teams should treat unmaintained third-party dependencies with heightened scrutiny, recognizing that known flaws in these libraries remain unpatched indefinitely. Regular audits of dependency trees are essential to identify such risks early. By transitioning to well-maintained tools and enforcing strict memory safety protocols during the development of custom bindings, organizations can significantly reduce their attack surface related to use-after-free vulnerabilities and improve overall system resilience against exploitation attempts targeting disassembly components.