--- name: analyzing-linux-elf-malware-7b94fd7da25d 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 ``` --- Source attribution: hironow Original project: https://github.com/hironow/cyber/blob/20efb3a6a2a9e7ebbde38ed32325979866110540/.agents/skills/analyzing-linux-elf-malware/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Dave AI. ## Upstream license notice Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. 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See the License for the specific language governing permissions and limitations under the License. # Dave AI resource metadata Creator / publisher: hironow Original project: https://github.com/hironow/cyber/blob/20efb3a6a2a9e7ebbde38ed32325979866110540/.agents/skills/analyzing-linux-elf-malware/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Development & Engineering Roles: Backend Developer, Data Scientist, Security Engineer Specialties: Backend, Testing Tools: Gdb, Ghidra, Ida, Radare2, Ltrace, Strace, Upx Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: b94f5679ab451f8c25f79065b30099a8047ebf0598354e834166d5de7a0d37eb