Heap Spray Attack Detection via Virtual Memory Monitoring
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Solution Overview
Problem
Current security detection techniques struggle to identify and prevent zero-day threats and heap spray attacks, which exploit new vulnerabilities in applications or operating systems, as they often rely on signature-based methods that are ineffective against unknown threats.
Innovation Solution
Implementing exploit detection based on heap spray detection techniques, including monitoring memory allocation patterns, modifying execution environments, and using virtual machines to detect and prevent malicious heap spraying by altering binary file versions or base addresses, and scanning for ROP gadgets and de-obfuscated executable artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If signature-based detection methods are used, then detection of known threats is effective, but detection of zero-day threats and heap spray attacks fails
Solution Approach 1:
The patent changes the detection parameters from static signature matching to dynamic behavioral analysis. It monitors heap allocation patterns, memory access behaviors, and program execution characteristics in real-time, enabling detection of both known and unknown threats based on their behavioral signatures rather than static code signatures.
Solution Approach 2:
The system performs preliminary actions by modifying the execution environment before the actual exploit execution. It uses virtual machines with altered binary file versions or base addresses to detect heap spray attacks in advance, allowing the system to identify malicious patterns before they can compromise the actual system.
2Reliability
If virtual machines with modified execution environments are used, then detection of heap spray attacks improves, but system complexity increases
Solution Approach 1:
The patent creates virtual machine copies with modified execution environments to detect heap spray attacks. These virtual copies serve as safe testing grounds where the system can monitor malicious behaviors without affecting the actual system, thereby improving detection reliability while isolating the complexity to controlled virtual environments.
3Measurement precision
If memory allocation patterns are monitored in real-time, then heap spray attacks are detected, but processing overhead increases
Solution Approach 1:
The system implements efficient monitoring by skipping unnecessary analysis steps and focusing directly on critical heap allocation patterns. It rapidly identifies and flags suspicious allocation sequences without performing exhaustive analysis on every memory operation, thereby maintaining high detection precision while minimizing processing overhead.
Data Source
AI summary
Various techniques for exploit detection based on heap spray detection are disclosed. In some embodiments, exploit detection based on heap spray detection includes executing a program in a virtual environment, monitoring a heap of a memory while executing the program in the virtual environment, and detecting a potential heap spray attack based on detecting a burst allocation of a first plurality of blocks in the heap of the memory, in which each of the first plurality of blocks is stored in the predefined address range of the memory.