A team of researchers from Ben-Gurion University of the Negev has introduced a groundbreaking framework for Unified Extensible Firmware Interface (UEFI) memory forensics, targeting vulnerabilities that threat actors exploit during the pre-operating system (OS) phase.
Traditionally, UEFI has replaced the legacy BIOS systems in modern computing, acting as a crucial bridge between hardware initialization and the OS.
However, this firmware has also emerged as a high-value target for attackers seeking persistence and elevated privileges.
Despite its growing importance in modern computing environments, the researchers highlight a notable gap in tools designed to capture and analyze volatile UEFI memory during its runtime.
The newly developed framework consists of two integral components: UefiMemDump, a memory acquisition tool, and UEFIDumpAnalysis, an extendable suite of modules for forensic analysis.
Together, these tools aim to facilitate the detection of firmware-level threats, enabling security analysts to investigate malicious activity occurring in the pre-OS phase.
Framework Design
The UefiMemDump tool is designed to capture UEFI memory snapshots during the boot phase, implemented as both a Driver Execution Environment (DXE) driver and a UEFI shell application.
This dual implementation ensures flexibility for forensic investigations in both virtualized and physical computing environments.
By generating detailed, system-wide memory dumps, the tool captures transient and persistent memory regions critical for identifying anomalous behavior.
Once memory is acquired, the UEFIDumpAnalysis module comes into play, processing the raw memory data for forensic examination.
The analysis modules include:
- Function Pointer Hooking Detection: This module scans UEFI service tables, such as the Boot Services Table, for unauthorized modifications commonly employed by threat actors to hijack execution flows.
- Inline Hooking Detection: It disassembles and scrutinizes code loaded in memory for tampering techniques like overwritten function prologues, allowing attackers to redirect execution to malicious payloads.
- UEFI Image Carving: This module extracts loaded Portable Executable (PE) images from memory dumps, enabling analysts to inspect firmware drivers and applications for malicious behavior.
The modular design of the framework allows for further extension, encouraging the cybersecurity community to contribute additional detection capabilities.
The framework’s efficacy was evaluated against sophisticated UEFI bootkits, including MoonBounce, CosmicStrand, and ThunderStrike, as well as proof-of-concept exploits like EfiGuard.
These threats exploit UEFI vulnerabilities by leveraging techniques such as function pointer and inline hooking or malicious image loading to gain deep system-level access, often bypassing Secure Boot protections.
For instance, Glupteba and the open-source EfiGuard were detected redirecting service pointers to attacker-controlled code, manipulating the Boot and Runtime Services Tables to disable critical Windows kernel protections.
Similarly, the proof-of-concept ThunderStrike bootkit, which hijacks a legitimate UEFI service (ProcessFirmwareVolume), was flagged by the framework for employing malicious hooks embedded in option ROMs.
The researchers also demonstrated the capability to extract malicious firmware images from different sources, including the EFI System Partition (ESP), option ROMs, and embedded DXE drivers.
These extracted images can be further analyzed for known malware signatures, providing significant insights for incident response.
This framework represents a major step forward in addressing the security challenges associated with UEFI firmware, an often-overlooked attack vector in traditional security models.
Its ability to analyze volatile memory during the critical pre-OS phase bridges a longstanding gap in incident response and below-OS security.
While promising, the study acknowledges limitations, particularly in the tool’s ability to resist anti-forensic techniques employed by advanced adversaries.
Future research avenues include creating tamper-resistant memory acquisition methods and refining detection capabilities to reduce false positives in inline hooking analysis.
By open-sourcing the framework, the research team aims to foster collaboration within the security community, encouraging the development of additional forensic tools tailored for UEFI memory analysis.
This initiative is expected to significantly advance understanding and detection of firmware-level threats, reinforcing trust in modern computing systems.
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