Android Memory Forensics

The World of Mobile Memory Analysis

After spending several months exploring Android memory forensics, I wanted to share my technical insights into this critical aspect of mobile investigation. Memory forensics has fascinated me, particularly how Linux Memory Extractor (LiME) and Volatility Framework can reveal intricate details about Android's runtime environment that aren't accessible through traditional storage analysis.

Understanding the Technical Core

Memory forensics focuses on analyzing the contents of volatile memory (RAM), where we find process states, network connections, and decrypted data in Android's runtime environment. During my analyses, I've worked extensively with Android's memory structure, including its DVM (Dalvik Virtual Machine) heap, native heap allocations, and kernel memory spaces.

The kernel memory space (typically starting at 0xC0000000 in 32-bit systems) contains crucial system data structures. User space memory, where most applications run, occupies the lower memory addresses. This separation has proved vital in understanding how Android manages its resources and processes.

Technical Acquisition Process

My experience with memory acquisition has taught me the importance of proper tool configuration. When using LiME, I've found that specifying the correct compression and format parameters significantly impacts acquisition success:

The default LiME parameters I use:

insmod lime.ko "path=/sdcard/ram.dump format=raw"

Command Components:

insmod: Linux kernel module insertion command
lime.ko: The LiME (Linux Memory Extractor) kernel module
path=/sdcard/ram.dump: Specifies output location and filename
format=raw: Creates an uncompressed, raw memory dump

For complex devices, I sometimes need more specific options:

insmod lime.ko "path=/sdcard/ram.dump format=lime range=0x00000000-0xffffffff timeout=5000"

Parameter Details:

Format Options:
- format=raw: Uncompressed direct memory dump
  - Pros: Faster acquisition
  - Cons: Larger file size in the device
- format=lime: LiME's custom format
  - Pros: Includes metadata and checksums
  - Cons: Slightly slower acquisition
  - Better for integrity verification
Range Parameter:
- range=0x00000000-0xffffffff
  - Start address: 0x00000000 (beginning of memory)
  - End address: 0xffffffff (end of 32-bit address space)
  - Allows targeting specific memory regions
  - Useful for:
    - Reducing dump size
    - Focusing on specific memory areas
    - Avoiding problematic memory regions
Timeout Setting:
- timeout=5000
  - Value in milliseconds (5 seconds in this case)
  - Prevents system hangs during acquisition
  - Particularly important for:
    - Large memory dumps
    - Slower devices
    - Unstable systems
Additional Options Available:
- dio=1: Direct I/O mode
  - Bypasses the page cache
  - Reduces system memory impact
- localhostonly=1: Restricts network access
  - Enhanced security during acquisition
- digest=sha256: Adds integrity checking
  - Calculates hash values during acquisition
  - Helps verify dump integrity

Memory Mapping Insights

One of the most fascinating aspects has been understanding how Android's memory mapping works. I've observed that key evidence often resides in specific memory regions:

Heap segments (0x00000000 - 0x7FFFFFFF): Application data and runtime variables
Kernel space (0xC0000000 - 0xFFFFFFFF): System structures and drivers
Shared libraries (typically around 0x40000000): Common code used across processes

The Process Memory Structure

Android's process memory layout has proved particularly interesting. Each application runs in its own memory space with several key segments:

Text segment: Contains executable code
Data segment: Initialized variables
BSS: Uninitialized variables
Heap: Dynamic memory allocation
Stack: Runtime execution context

Technical Challenges

One significant challenge I've encountered is dealing with Android's memory compression. Modern Android devices use zRAM for memory compression, which can complicate the analysis process. I've learned to identify compressed memory regions and properly decompress them before analysis.

Memory fragmentation also presents interesting technical challenges. Android's memory allocator can spread related data across multiple memory pages, requiring careful reconstruction during analysis.

Advanced Memory Structures

Understanding Android's memory management has been crucial. Key structures I frequently analyze include:

Task Structures:

task_struct: Contains process information
mm_struct: Memory management information
files_struct: Open file handles

Memory Descriptors:

vm_area_struct: Virtual memory area information
page tables: Memory mapping information
dentry cache: Directory entry information

Note: This reflects my experience level as a newer analyst - always verify current best practices for your specific case requirements.

Author:

Hasan Hashim

Cyber Security and Digital Forensics

Page updated

Google Sites

Report abuse