Adversaries may abuse the <code>KernelCallbackTable</code> of a process to hijack its execution flow in order to run their own payloads.(Citation: Lazarus APT January 2022)(Citation: FinFisher exposed ) The <code>KernelCallbackTable</code> can be found in the Process Environment Block (PEB) and is initialized to an array of graphic functions available to a GUI process once <code>user32.dll</code> is loaded.(Citation: Windows Process Injection KernelCallbackTable)
An adversary may hijack the execution flow of a process using the <code>KernelCallbackTable</code> by replacing an original callback function with a malicious payload. Modifying callback functions can be achieved in various ways involving related behaviors such as Reflective Code Loading or Process Injection into another process.
A pointer to the memory address of the <code>KernelCallbackTable</code> can be obtained by locating the PEB (ex: via a call to the <code>NtQueryInformationProcess()</code> Native API function).(Citation: NtQueryInformationProcess) Once the pointer is located, the <code>KernelCallbackTable</code> can be duplicated, and a function in the table (e.g., <code>fnCOPYDATA</code>) set to the address of a malicious payload (ex: via <code>WriteProcessMemory()</code>). The PEB is then updated with the new address of the table. Once the tampered function is invoked, the malicious payload will be triggered.(Citation: Lazarus APT January 2022)
The tampered function is typically invoked using a Windows message. After the process is hijacked and malicious code is executed, the <code>KernelCallbackTable</code> may also be restored to its original state by the rest of the malicious payload.(Citation: Lazarus APT January 2022) Use of the <code>KernelCallbackTable</code> to hijack execution flow may evade detection from security products since the execution can be masked under a legitimate process.
Detection Strategy for Hijack Execution Flow through the KernelCallbackTable on Windows.
Behavior Prevention on Endpoint: Behavior Prevention on Endpoint refers to the use of technologies and strategies to detect and block potentially malicious activities by analyzing the behavior of processes, files, API calls, and other endpoint events. Rather than relying solely on known signatures, this approach leverages heuristics, machine learning, and real-time monitoring to identify anomalous patterns indicative of an attack. This mitigation can be implemented through the following measures:
Suspicious Process Behavior:
Unauthorized File Access:
Abnormal API Calls:
OpenProcess and WriteProcessMemory and terminates the offending process.Exploit Prevention: