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Memory Forensics Concepts

Lesson 23/47 | Study Time: 20 Min

Course: Computer and Cyber Forensics Professional – Course

Memory forensics concepts involve capturing and analyzing volatile RAM contents to uncover runtime system states, processes, malware artifacts, and encryption keys that disappear upon shutdown, complementing disk-based investigations with live evidence.

This discipline reveals hidden threats like fileless malware, injected code, and network connections invisible on persistent storage, requiring specialized acquisition and parsing techniques for defensible results.

Memory Acquisition Fundamentals

Memory acquisition creates forensic copies of physical RAM using methods that minimize system impact.

Live acquisition occurs on running systems via software injectors or hardware readers, prioritizing speed to preserve volatiles. Tools generate raw dumps (.raw, .mem) verified by hashes; challenges include 64-bit address spaces and anti-debugging malware altering dumps.

Workflow: Inject → Dump → Hash → Offline storage.

Memory Structure and Parsing

RAM organizes into kernel/user space, process address spaces, and pools holding executables, heaps, stacks.

Profiles map OS-specific structures (e.g., Windows _EPROCESS, Linux task_struct); frameworks load dumps against profiles for parsing. Analysis scans pools for artifacts using signatures or offsets.

Core Analysis Objectives

Investigations target runtime evidence across categories.

Process enumeration identifies injected/hidden malware via anomaly detection (unlinked lists, DKOM). Network analysis extracts sockets, connections from tcpip.sys equivalents. Code recovery dumps process images for disassembly; credential dumping targets LSASS equivalents.

Common Artifacts and Detection

Runtime traces reveal compromise indicators.

1. Process hollowing: Legit parent with malicious child imagebase.

2. API hooks: Inline/patch modifications in ntdll.dll.

3. Rootkits: Hidden kernel modules via SSDT/IDT scans.

4. Fileless attacks: PowerShell/AMSIBuffer in memory streams.

Timelines merge from process creation times, socket states.

Frameworks and Tooling

Workflow: Acquire → Profile → Enumerate → Scan anomalies → Dump suspects → YARA scan.

Challenges and Anti-Forensics Countermeasures

Volatility, address space randomization, and evasion complicate analysis.

1. Large dumps (32-128GB): Use targeted scans.

2. Profile mismatches: Custom offsets or symbol tables.

3. Anti-forensics: Memory wiping detected via pattern anomalies.

Best practices: Multiple profiles, cross-validation with disk artifacts, live acquisition scripting.

Memory forensics bridges runtime/disk gaps, detecting advanced threats through structured RAM dissection essential for 2025 incident response.

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Alexander Cruise

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Class Sessions

1- Evolution of Digital Crime and Cyber Forensics 2- Key Terminology and Scope 3- Digital Evidence Lifecycle and Forensic Principles 4- Legal, Regulatory, and Standards Context 5- Roles and Career Paths in Computer and Cyber Forensics 6- Structured Digital Investigation Methodologies 7- Scoping and Planning an Investigation 8- Evidence Sources in Enterprise Environments 9- Documentation, Case Notes, and Evidence Tracking 10- Working with Multidisciplinary Teams 11- Computer and Storage Architecture for Investigators 12- File System Structures and Artifacts 13- File and Artifact Recovery 14- Common User-Activity Artifacts 15- Principles of Forensically Sound Acquisition 16- Acquisition Strategies 17- Volatile vs Non-Volatile Data Acquisition 18- Handling Encrypted and Locked Systems 19- Evidence Handling, Transport, and Storage 20- Windows Forensics Essentials 21- Linux and Unix-Like System Forensics 22- macOS and Modern Desktop Environments 23- Memory Forensics Concepts 24- Timeline Construction Using OS and Memory Artifacts 25- Network Forensics Fundamentals 26- Enterprise Logging and Telemetry 27- Cloud Forensics (IaaS, PaaS, SaaS) 28- Email and Messaging Investigations 29- Timeline Building from Heterogeneous Logs 30- Modern Malware and Ransomware Landscape 31- Malware Forensics Concepts 32- Host-Level Artifacts of Compromise 33- Ransomware Incident Artifacts 34- Dark Web and Anonymous Network Forensics 35- Common Anti-Forensics Techniques 36- Detection of Anti-Forensics 37- Countering Anti-Forensics 38- Resilient Evidence Collection Strategies 39- Incident Response Frameworks and Phases 40- Forensics-Driven Incident Response 41- Threat Hunting Linked with Forensics 42- Post-Incident Activities 43- Forensic Report Structure 44- Writing for Multiple Audiences 45- Presenting and Defending Findings 46- Ethics, Confidentiality, and Professional Conduct 47- Continuous Learning and Certification Pathways