analyzing-linux-elf-malware — Claude Code skill: Linux ELF malware
A skill that walks an agent through dissecting suspicious Linux ELF binaries: headers, strings, syscalls, Ghidra. Useful when a server or container looks compromised.
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-linux-elf-malware -a claude-codeWhat analyzing-linux-elf-malware does
The skill lays out an analysis workflow for malicious ELF files: header properties and hashes first, then strings and indicators, then syscall tracing and debugging, and finally decompilation in Ghidra. It covers x86_64 and ARM samples, including botnets, cryptominers, ransomware and rootkits. Windows PE is explicitly out of scope — the skill points to PEStudio, Ghidra or IDA for that.
Inside are ready commands: file, readelf, nm, ldd, upx -t, and strings filtered for URLs, IPs, domains, shell commands and mining markers. A Python snippet using elftools computes SHA-256, checks whether symbols were stripped, and flags high-entropy sections. From there strace and ltrace trace network, process and file activity, GDB sets breakpoints on socket, connect, execve and fork, and Ghidra analysis lists what to look for in Mirai-like botnets.
Run dynamic steps in an isolated Linux VM — Ubuntu 22.04 is the recommendation — or a container. Running ldd on a binary built for another architecture gives you garbage, so check e_machine from readelf -h before you execute anything. You need Ghidra or IDA, binutils, Radare2, GDB, strace and ltrace on hand.
What it helps with
- triage a suspicious ELF binary on a compromised server
- pull IOCs and strings out of a botnet sample
- trace network and file syscalls of a cryptominer
- spot packed sections via entropy and stripped symbols
- analyze a Linux rootkit or kernel module
Example prompts for the agent
- analyze this ELF binary: start with the header and hashes, then strings and IOCs
- trace the sample's syscalls in an isolated VM and show me the network activity
- check the high-entropy sections and tell me whether the file is packed
How to install analyzing-linux-elf-malware
1Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-linux-elf-malware -a claude-code2Manually: put the files in place
~/.claude/skills/analyzing-linux-elf-malware/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/analyzing-linux-elf-malware/
1Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-linux-elf-malware -a codex2Manually: put the files in place
.agents/skills/analyzing-linux-elf-malware/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-linux-elf-malware -a cursor2Manually: put the files in place
.cursor/skills/analyzing-linux-elf-malware/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-linux-elf-malware2Manually: put the files in place
.github/skills/analyzing-linux-elf-malware/SKILL.md1Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-linux-elf-malware -a gemini-cli2Platform CLI
gemini skills install https://github.com/mukul975/Anthropic-Cybersecurity-Skills --path skills/analyzing-linux-elf-malwareManually: put the files in place
.devin/skills/analyzing-linux-elf-malware/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-linux-elf-malware -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about analyzing-linux-elf-malware
How do I install analyzing-linux-elf-malware in Claude?
Run npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-linux-elf-malware -a claude-code. The skill then lives at ~/.claude/skills/analyzing-linux-elf-malware/SKILL.md.
What does analyzing-linux-elf-malware do?
It runs Linux ELF malware analysis: static inspection of headers and strings, syscall tracing, GDB debugging and Ghidra decompilation. It targets x86_64 and ARM samples.
Does it work for Windows malware?
No. The skill itself directs Windows PE work to PEStudio, Ghidra or IDA — this one is for Linux ELF.
Source text
SKILL.md · Apache-2.0
---
name: analyzing-linux-elf-malware
description: 'Analyze malicious Linux ELF binaries — botnets, cryptominers, ransomware,
and rootkits targeting Linux servers, containers, and cloud infrastructure — through
static analysis, dynamic tracing, and reverse engineering of x86_64 and ARM samples.
Use when investigating Linux malware, triaging a suspicious ELF binary, assessing
a compromised Linux server, or analyzing container-targeted malware.
'
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
mitre_f3:
version: '1.1'
tactics:
- positioning
- monetization
- reconnaissance
techniques:
- id: T1219
name: Remote Access Tools
tactic: positioning
source: attack
- id: T1555
name: Credentials from Password Stores
tactic: reconnaissance
source: attack
- id: F1018
name: Convert to Cryptocurrency
tactic: monetization
source: f3
- id: F1047
name: Transfer of funds
tactic: monetization
source: f3
---
# 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:
```bash
# 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
# 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()
with open("suspect_binary", "rb") as f:
elf = ELFFile(f)
print(f"SHA-256: {sha256}")
print(f"Class: {elf.elfclass}-bit")
print(f"Endian: {elf.little_endian and 'Little' or 'Big'}")
print(f"Machine: {elf.header.e_machine}")
print(f"Type: {elf.header.e_type}")
print(f"Entry Point: 0x{elf.header.e_entry:X}")
# Check if stripped
symtab = elf.get_section_by_name('.symtab')
print(f"Stripped: {'Yes' if symtab is None else 'No'}")
# Section entropy analysis
import math
from collections import Counter
for section in elf.iter_sections():
data = section.data()
if len(data) > 0:
entropy = -sum((c/len(data)) * math.log2(c/len(data))
for c in Counter(data).values() if c > 0)
if entropy > 7.0:
print(f" [!] High entropy section: {section.name} ({entropy:.2f})")
```
### Step 2: Extract Strings and Indicators
Search for embedded IOCs and functionality clues:
```bash
# ASCII strings
strings suspect_binary > strings_output.txt
# Search for network indicators
grep -iE "(http|https|ftp)://" strings_output.txt
grep -iE "([0-9]{1,3}\.){3}[0-9]{1,3}" strings_output.txt
grep -iE "[a-zA-Z0-9.-]+\.(com|net|org|io|ru|cn)" strings_output.txt
# Search for shell commands
grep -iE "(bash|sh|wget|curl|chmod|/tmp/|/dev/)" strings_output.txt
# Search for crypto mining indicators
grep -iE "(stratum|xmr|monero|pool\.|mining)" strings_output.txt
# Search for SSH/credential theft
grep -iE "(ssh|authorized_keys|id_rsa|shadow|passwd)" strings_output.txt
# Search for persistence mechanisms
grep -iE "(crontab|systemd|init\.d|rc\.local|ld\.so\.preload)" strings_output.txt
# FLOSS for obfuscated strings (if available)
floss suspect_binary
```
### Step 3: Analyze System Calls and Library Usage
Identify what system calls and libraries the malware uses:
```bash
# List imported functions (dynamically linked)
readelf -r suspect_binary | grep -E "socket|connect|exec|fork|open|write|bind|listen"
# Trace system calls during execution (in isolated VM only)
strace -f -e trace=network,process,file -o strace_output.txt ./suspect_binary
# Trace library calls
ltrace -f -o ltrace_output.txt ./suspect_binary
# Key system calls to watch:
# Network: socket, connect, bind, listen, accept, sendto, recvfrom
# Process: fork, execve, clone, kill, ptrace
# File: open, read, write, unlink, rename, chmod
# Persistence: inotify_add_watch (file monitoring)
```
### Step 4: Dynamic Analysis with GDB
Debug the malware to observe runtime behavior:
```bash
# Start GDB with the binary
gdb ./suspect_binary
# Set breakpoints on key functions
(gdb) break main
(gdb) break socket
(gdb) break connect
(gdb) break execve
(gdb) break fork
# Run and analyze
(gdb) run
(gdb) info registers # View register state
(gdb) x/20s $rdi # Examine string argument
(gdb) bt # Backtrace
(gdb) continue
# For stripped binaries, break on entry point
(gdb) break *0x400580 # Entry point from readelf
(gdb) run
# Monitor network connections during execution
# In another terminal:
ss -tlnp # List listening sockets
ss -tnp # List established connections
```
### Step 5: Reverse Engineer with Ghidra
Perform deep code analysis on the ELF binary:
```
Ghidra Analysis for Linux ELF:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1. Import: File -> Import -> Select ELF binary
- Ghidra auto-detects ELF format and architecture
- Accept default analysis options
2. Key analysis targets:
- main() function (or entry point if stripped)
- Socket creation and connection functions
- Command dispatch logic (switch/case on received data)
- Encryption/encoding routines
- Persistence installation code
- Self-propagation/scanning functions
3. For Mirai-like botnets, look for:
- Credential list for brute-forcing (telnet/SSH)
- Attack module selection (UDP flood, SYN flood, ACK flood)
- Scanner module (port scanning for vulnerable devices)
- Killer module (killing competing botnets)
4. For cryptominers, look for:
- Mining pool connection (stratum protocol)
- Wallet address strings
- CPU/GPU utilization functions
- Process hiding techniques
```
### Step 6: Analyze Linux-Specific Persistence
Check for persistence mechanisms:
```bash
# Check for LD_PRELOAD rootkit
strings suspect_binary | grep "ld.so.preload"
# Malware writing to /etc/ld.so.preload can hook all dynamic library calls
# Check for crontab persistence
strings suspect_binary | grep -i "cron"
# Check for systemd service creation
strings suspect_binary | grep -iE "systemd|\.service|systemctl"
# Check for init script creation
strings suspect_binary | grep -iE "init\.d|rc\.local|update-rc"
# Check for SSH key injection
strings suspect_binary | grep -i "authorized_keys"
# Check for kernel module (rootkit) loading
strings suspect_binary | grep -iE "insmod|modprobe|init_module"
# Check for process hiding
strings suspect_binary | grep -iE "proc|readdir|getdents"
```
## Key Concepts
| Term | Definition |
|------|------------|
| **ELF (Executable and Linkable Format)** | Standard binary format for Linux executables, shared libraries, and core dumps containing headers, sections, and segments |
| **Stripped Binary** | ELF binary with debug symbols removed, making reverse engineering more difficult as function names are lost |
| **LD_PRELOAD** | Linux environment variable specifying shared libraries to load before all others; abused by rootkits to intercept system library calls |
| **strace** | Linux system call tracer that logs all system calls and signals made by a process, revealing file, network, and process operations |
| **GOT/PLT** | Global Offset Table and Procedure Linkage Table; ELF structures for dynamic linking that can be hijacked for function hooking |
| **Statically Linked** | Binary compiled with all library code included; common in IoT malware to run on systems without matching shared libraries |
| **Mirai** | Prolific Linux botnet targeting IoT devices via telnet brute-force; source code leaked, leading to many variants |
## Tools & Systems
- **Ghidra**: NSA reverse engineering tool with full ELF support for x86, x86_64, ARM, MIPS, and other Linux architectures
- **Radare2**: Open-source reverse engineering framework with command-line interface for quick binary analysis and scripting
- **strace**: Linux system call tracing tool for observing binary behavior including file, network, and process operations
- **GDB**: GNU Debugger for setting breakpoints, examining memory, and stepping through Linux binary execution
- **pyelftools**: Python library for parsing ELF files programmatically for automated analysis pipelines
## Common Scenarios
### Scenario: Analyzing a Cryptominer Found on a Compromised Linux Server
**Context**: A cloud server shows 100% CPU usage. Investigation reveals an unknown binary running from /tmp with a suspicious name. The binary needs analysis to confirm it is a cryptominer and identify the attacker's wallet and pool.
**Approach**:
1. Copy the binary to an analysis VM and compute SHA-256 hash
2. Run `file` and `readelf` to identify architecture and linking type
3. Extract strings and search for mining pool addresses (stratum+tcp://) and wallet addresses
4. Run with strace in a sandbox to observe network connections (mining pool connection)
5. Import into Ghidra to identify the mining algorithm and configuration extraction
6. Check for persistence mechanisms (crontab, systemd service, SSH keys)
7. Document all IOCs including pool address, wallet, C2 for updates, and persistence artifacts
**Pitfalls**:
- Running `ldd` on malware outside a sandbox (ldd can execute code in the binary)
- Not checking for ARM/MIPS architecture before attempting x86_64 execution
- Missing companion scripts (.sh files) that may handle persistence and cleanup
- Ignoring the initial access vector (how the miner was deployed: SSH brute force, web exploit, container escape)
## Output Format
```
LINUX ELF MALWARE ANALYSIS REPORT
====================================
File: /tmp/.X11-unix/.rsync
SHA-256: e3b0c44298fc1c149afbf4c8996fb924...
Type: ELF 64-bit LSB executable, x86-64
Linking: Statically linked (all libraries embedded)
Stripped: Yes
Size: 2,847,232 bytes
Packer: UPX 3.96 (unpacked for analysis)
CLASSIFICATION
Family: XMRig Cryptominer (modified)
Variant: Custom build with C2 update mechanism
FUNCTIONALITY
[*] XMR (Monero) mining via RandomX algorithm
[*] Stratum pool connection for work submission
[*] C2 check-in for configuration updates
[*] Process name masquerading (argv[0] = "[kworker/0:0]")
[*] Competitor process killing (kills other miners)
[*] SSH key injection for re-access
NETWORK INDICATORS
Mining Pool: stratum+tcp://pool.minexmr[.]com:4444
C2 Server: hxxp://update.malicious[.]com/config
Wallet: 49jZ5Q3b...Monero_Wallet_Address...
PERSISTENCE
[1] Crontab entry: */5 * * * * /tmp/.X11-unix/.rsync
[2] SSH key added to /root/.ssh/authorized_keys
[3] Systemd service: /etc/systemd/system/rsync-daemon.service
[4] Modified /etc/ld.so.preload for process hiding
PROCESS HIDING
LD_PRELOAD: /usr/lib/.libsystem.so
Hook: readdir() to hide /tmp/.X11-unix/.rsync from ls
Hook: fopen() to hide from /proc/*/maps reading
```
© mahipal · Apache-2.0 · mukul975/Anthropic-Cybersecurity-Skills