analyzing-linux-elf-malware

name	analyzing-linux-elf-malware
description	Analyzes malicious Linux ELF (Executable and Linkable Format) binaries including botnets, cryptominers, ransomware, and rootkits targeting Linux servers, containers, and cloud infrastructure. Covers static analysis, dynamic tracing, and reverse engineering of x86_64 and ARM ELF samples. Activates for requests involving Linux malware analysis, ELF binary investigation, Linux server compromise assessment, or container malware analysis.
domain	cybersecurity
subdomain	malware-analysis
tags	["malware","Linux","ELF","reverse-engineering","server-malware"]
version	1.0.0
author	mahipal
license	Apache-2.0
nist_csf	["DE.AE-02","RS.AN-03","ID.RA-01","DE.CM-01"]
mitre_attack	["T1027","T1059.004","T1620","T1574.006"]
source	https://github.com/mukul975/Anthropic-Cybersecurity-Skills
source_commit	04450304b12645cb2b974ab96d28c0664758a88d
note	Vendored verbatim from an external Apache-2.0 security-skill library, pinned by commit. Exceeds the internal 300-line skill guideline (agent-code-constraints.md) -- kept as-is because this is vendored reference material (forensics/threat-intel procedure), not Yana AI-authored content, and trimming would damage technical accuracy.

Analyzing Linux ELF Malware

When to Use

• A Linux server or container has been compromised and suspicious ELF binaries are found
• Analyzing Linux botnets (Mirai, Gafgyt, XorDDoS), cryptominers, or ransomware
• Investigating malware targeting cloud infrastructure, Docker containers, or Kubernetes pods
• Reverse engineering Linux rootkits and kernel modules
• Analyzing cross-platform malware compiled for Linux x86_64, ARM, or MIPS architectures

Do not use for Windows PE binary analysis; use PEStudio, Ghidra, or IDA for Windows malware.

Prerequisites

• Ghidra or IDA with Linux ELF support for disassembly and decompilation
• Linux analysis VM (Ubuntu 22.04 recommended) with development tools installed
• strace, ltrace, and GDB for dynamic analysis and debugging
• readelf, objdump, and nm from GNU binutils for static inspection
• Radare2 for quick binary triage and scripted analysis
• Docker for isolated container-based malware execution

Workflow

Step 1: Identify ELF Binary Properties

Examine the ELF header and basic properties:

# File type identification
file suspect_binary

# Detailed ELF header analysis
readelf -h suspect_binary

# Section headers
readelf -S suspect_binary

# Program headers (segments)
readelf -l suspect_binary

# Symbol table (if not stripped)
readelf -s suspect_binary
nm suspect_binary 2>/dev/null

# Dynamic linking information
readelf -d suspect_binary
ldd suspect_binary 2>/dev/null  # Only on matching architecture!

# Compute hashes
md5sum suspect_binary
sha256sum suspect_binary

# Check for packing/UPX
upx -t suspect_binary

# Python-based ELF analysis
from elftools.elf.elffile import ELFFile
import hashlib

with open("suspect_binary", "rb") as f:
    data = f.read()
    sha256 = hashlib.sha256(data).hexdigest()

 (, )  f:
    elf = ELFFile(f)

    ()
    ()
    ()
    ()
    ()
    ()

    
    symtab = elf.get_section_by_name()
    ()

    
     math
     collections  Counter
     section  elf.iter_sections():
        data = section.data()
         (data) > :
            entropy = -((c/(data)) * math.log2(c/(data))
                           c  Counter(data).values()  c > )
             entropy > :
                ()