OS Memory Forensics for Undocumented Structure Detection

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Solution Overview

Problem

Existing cybersecurity measures struggle to effectively identify and analyze undocumented and unknown memory structures within operating systems, making it difficult to detect cyber threats such as malware, as memory audits are hindered by the lack of documentation and reliability of information retrieved via known APIs.

Innovation Solution

A cyberthreat detection system utilizing an intelligence extraction system that performs real-time, automated analytics to identify and analyze undocumented and unknown memory structures through an undocumented structure extractor logic, undocumented offset extractor logic, and algorithm selector logic, leveraging symbols, heuristics, and experiential learning to uncover potential cyber threats.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If memory audits are performed to extract reliable security information, then detection reliability is improved, but device complexity and difficulty of operation increase due to undocumented memory structures

Engineering Contradiction:

Improvedetection reliabilityVSAvoidmemory audit complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system enables self-service by automatically extracting and analyzing memory structures without requiring manual intervention or expert knowledge. The automated memory forensics system performs memory audits, extracts undocumented structures, and generates security reports independently, allowing any user to benefit from reliable detection without bearing the operational complexity.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system introduces an intermediary layer between the complex memory audit process and the end user. This intermediary component automatically handles the complexity of accessing undocumented memory structures, translating them into readable and actionable security findings, thereby maintaining high detection reliability while hiding the underlying complexity from users.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If manual memory audits are performed to classify undocumented memory structures, then detection accuracy is improved, but time consumption increases

Engineering Contradiction:

Improvedetection accuracyVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system replaces the mechanical manual analysis process with an automated computational system. Instead of human analysts manually classifying memory structures, the system uses automated algorithms to extract, analyze, and interpret undocumented memory structures, achieving high detection accuracy while dramatically reducing time consumption through computational efficiency.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables continuous automated memory forensics operations without interruption or fatigue. The automated process continuously monitors, extracts, and analyzes memory structures in real-time, maintaining constant detection accuracy without the time losses associated with manual audit cycles, breaks, and human processing limitations.

Inventive Principle:

Principle #20Continuity of useful action

3Ease of operation

If known APIs are used to extract security information, then ease of operation is improved, but reliability deteriorates due to malware tainting

Engineering Contradiction:

Improveease of information extractionVSAvoidinformation reliability

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The system introduces memory forensics as an intermediary layer that operates independently from compromised APIs. Instead of relying on potentially tainted API calls, the system directly accesses memory structures to extract security information, using the memory audit process as a mediator that bypasses malware contamination while maintaining ease of operation through automated interfaces.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system creates a copy or snapshot of memory structures for analysis, separating the extraction process from the potentially compromised live system state. By working with memory copies and forensic images rather than direct API calls to potentially infected processes, the system maintains reliability while preserving ease of operation through standardized forensic extraction interfaces.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS12511388B1System and method for operating system memory forensics

Publication Date: 2025.12.30 FIREEYE SECURITY HOLDINGS US LLC

AI summary

Disclosed herein is a cyberthreat detection system for detecting, in real-time, cyberthreats residing within a memory of a targeted computing device. The cyberthreat detection system features an undocumented structure extractor logic and an undocumented offset extractor logic. The undocumented structure extractor logic is configured to identify known, undocumented, memory structures associated with software operating on the targeted computing device. The undocumented offset extractor logic is configured to identify undocumented and unknown memory structures associated with software installed on the targeted computing device.