Adversaries may smuggle commands to download malicious payloads past content filters by hiding them within otherwise seemingly benign windows shortcut files. Windows shortcut files (.LNK) include many metadata fields, including an icon location field (also known as the IconEnvironmentDataBlock) designed to specify the path to an icon file that is to be displayed for the LNK file within a host directory.
Adversaries may abuse this LNK metadata to download malicious payloads. For example, adversaries have been observed using LNK files as phishing payloads to deliver malware. Once invoked (e.g., Malicious File), payloads referenced via external URLs within the LNK icon location field may be downloaded. These files may also then be invoked by Command and Scripting Interpreter/System Binary Proxy Execution arguments within the target path field of the LNK.(Citation: Unprotect Shortcut)(Citation: Booby Trap Shortcut 2017)
LNK Icon Smuggling may also be utilized post compromise, such as malicious scripts executing an LNK on an infected host to download additional malicious payloads.
Detection Strategy for LNK Icon Smuggling
Antivirus/Antimalware: Antivirus/Antimalware solutions utilize signatures, heuristics, and behavioral analysis to detect, block, and remediate malicious software, including viruses, trojans, ransomware, and spyware. These solutions continuously monitor endpoints and systems for known malicious patterns and suspicious behaviors that indicate compromise. Antivirus/Antimalware software should be deployed across all devices, with automated updates to ensure protection against the latest threats. This mitigation can be implemented through the following measures:
Signature-Based Detection:
Heuristic-Based Detection:
Behavioral Detection (Behavior Prevention):
Real-Time Scanning:
Cloud-Assisted Threat Intelligence:
Tools for Implementation:
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:
No cross-framework mappings available