Persistence Probing Startup Hook Detection
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Solution Overview
Problem
Current malware detection methods are inadequate in effectively identifying and eradicating malware that uses persistence techniques to maintain its presence across reboots, as these methods often fail to distinguish between legitimate and malicious startup hooks.
Innovation Solution
The technique involves monitoring and removing startup hooks on a programmable device, observing if they are restored, and using this behavior to determine if malware is present, as legitimate software rarely reinstates such hooks, thereby identifying potential infections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional malware detection methods (file inspection, reputation checking, behavioral monitoring) are used, then detection coverage is improved, but malware continues to evade detection through persistence techniques
Solution Approach 1:
The system performs preliminary action by removing startup hooks before malware can execute, and by proactively monitoring for hook restoration attempts. The anti-malware software deletes suspected startup hooks and waits for a predetermined period to see if they are restored, catching malware before it can fully persist.
Solution Approach 2:
The system uses feedback by monitoring whether removed startup hooks are restored after deletion. If hooks are restored within the predetermined period, this feedback indicates malware persistence and triggers further detection actions. The system continuously monitors the startup environment for hook restoration attempts.
2Reliability
If startup hooks are removed to eliminate malware persistence, then malware detection improves, but legitimate software that uses startup hooks may be affected
Solution Approach 1:
The system applies local quality by treating different startup hooks differently based on their characteristics. It analyzes specific attributes of hooks (such as their location, timing, and behavior) to distinguish between legitimate and malicious ones, applying removal only to suspected malicious hooks while preserving legitimate ones.
Solution Approach 2:
The system uses parameter changes by monitoring temporal parameters - specifically, whether hooks are restored within a predetermined time period after removal. This time-based parameter helps distinguish malware (which restores hooks quickly to maintain persistence) from legitimate software (which does not restore hooks after deletion).
3Reliability
If continuous monitoring of startup hooks is implemented, then detection capability improves, but system overhead increases
Solution Approach 1:
The system implements periodic action by monitoring startup hooks at specific intervals rather than continuously. It performs monitoring during startup events and at predetermined time periods after hook removal, rather than maintaining constant surveillance, thereby reducing overhead while maintaining detection capability.
Solution Approach 2:
The system performs preliminary monitoring actions during startup events before full system operation begins. By catching and analyzing startup hooks at this early stage, the system reduces the need for continuous monitoring throughout system operation, lowering overall overhead.
Data Source
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AI summary
A technique for detecting malware looks at startup hooks that may be created by malware to assist in ensuring that the malware is started upon a reboot of a programmable device. After enumerating startup hooks in the system, startup hooks associated with untrusted executables are deleted. If the startup hook is restored, that is an indication that the untrusted executable may be malware. An indication may then be passed to an anti-malware software to analyze the executable further.