Analyzing Linux Kernel Rootkits

TL;DR

• 目的：Detect kernel-level rootkits in Linux memory dumps using Volatility3 linux plugins (check_syscall, lsmod, hidden_modules), rkhunter system s…
• 适用：恶意软件分析/逆向
• 输入：Linux 系统镜像路径或内存 dump 文件 + 内核版本
• 输出：IOC 列表 + 行为分析
• 红线：仅限授权范围内；扫描限速 -c 10 -rl 10；所有动作记 oplog
• 关联：上游：003-src-session-start → 下游：137-analyzing-malicious-pdf-with-peepdf, 138-analyzing-malicious-url-with-urlscan, 142-analyzing-pdf-malware-with-pdfid

Analyzing Linux Kernel Rootkits

Overview

Linux kernel rootkits operate at ring 0, modifying kernel data structures to hide processes, files, network connections, and kernel modules from userspace tools. Detection requires either memory forensics (analyzing physical memory dumps with Volatility3) or cross-view analysis (comparing /proc, /sys, and kernel data structures for inconsistencies). This skill covers using Volatility3 Linux plugins to detect syscall table hooks, hidden kernel modules, and modified function pointers, supplemented by live system scanning with rkhunter and chkrootkit.

When to Use

• When investigating security incidents that require analyzing linux kernel rootkits
• When building detection rules or threat hunting queries for this domain
• When SOC analysts need structured procedures for this analysis type
• When validating security monitoring coverage for related attack techniques

Prerequisites

• Volatility3 installed (pip install volatility3)
• Linux memory dump (acquired via LiME, AVML, or /proc/kcore)
• Volatility3 Linux symbol table (ISF) matching the target kernel version
• rkhunter and chkrootkit for live system scanning
• Reference known-good kernel image for comparison

Workflow

Step 1: Acquire Memory Dump

Capture Linux physical memory using LiME kernel module or AVML for cloud instances.

Step 2: Analyze with Volatility3

Run linux.check_syscall, linux.lsmod, linux.hidden_modules, and linux.check_idt plugins to detect rootkit artifacts.

Step 3: Cross-View Analysis

Compare module lists from /proc/modules, lsmod, and /sys/module to identify modules hidden from one view but present in another.

Step 4: Live System Scanning

Run rkhunter and chkrootkit to detect known rootkit signatures, suspicious files, and modified system binaries.

Output Format

JSON report containing detected syscall hooks, hidden kernel modules, modified IDT entries, suspicious /proc discrepancies, and rkhunter findings.

Example Output

$ sudo python3 rootkit_analyzer.py --memory /evidence/linux-mem.lime --profile Ubuntu2204

Linux Kernel Rootkit Analysis Report
=====================================
Memory Image: /evidence/linux-mem.lime
Kernel Version: 5.15.0-91-generic (Ubuntu 22.04 LTS)
Analysis Time: 2024-01-18 09:15:32 UTC

[+] Scanning syscall table for hooks...
    Syscall Table Base: 0xffffffff82200300
    Total syscalls checked: 449

    HOOKED SYSCALLS DETECTED:
    ┌─────────┬──────────────────┬──────────────────────┬──────────────────────┐
    │ NR      │ Syscall          │ Expected Address     │ Current Address      │
    ├─────────┼──────────────────┼──────────────────────┼──────────────────────┤
    │ 0       │ sys_read         │ 0xffffffff8139a0e0   │ 0xffffffffc0a12000   │
    │ 2       │ sys_open         │ 0xffffffff8139b340   │ 0xffffffffc0a12180   │
    │ 78      │ sys_getdents64   │ 0xffffffff813f5210   │ 0xffffffffc0a12300   │
    │ 62      │ sys_kill         │ 0xffffffff8110c4a0   │ 0xffffffffc0a12480   │
    └─────────┴──────────────────┴──────────────────────┴──────────────────────┘
    WARNING: 4 syscall hooks detected - rootkit behavior confirmed

[+] Checking for hidden kernel modules...
    Loaded modules (lsmod):         147
    Modules in kobject list:        149
    HIDDEN MODULES:
      - "netfilter_helper" at 0xffffffffc0a10000 (size: 12288)
      - "kworker_sched"    at 0xffffffffc0a14000 (size: 8192)

[+] Scanning /proc for discrepancies...
    Processes in task_struct list: 234
    Processes visible in /proc:   231
    HIDDEN PROCESSES:
      - PID 31337  cmd: "[kworker/0:3]"   (disguised as kernel thread)
      - PID 31442  cmd: "rsyslogd"         (fake, real rsyslogd is PID 892)
      - PID 31500  cmd: ""                 (unnamed process)

[+] Checking IDT entries...
    IDT entries scanned: 256
    Modified entries: 0 (clean)

[+] Running rkhunter scan...
    Checking for known rootkits:        68 variants checked
    Diamorphine rootkit:                WARNING - signatures match
    System binary checks:
      /usr/bin/ps:     MODIFIED (SHA-256 mismatch)
      /usr/bin/netstat: MODIFIED (SHA-256 mismatch)
      /usr/bin/ls:     MODIFIED (SHA-256 mismatch)
      /usr/sbin/ss:    OK

[+] Network analysis...
    Hidden connections (not in /proc/net/tcp):
      ESTABLISHED  0.0.0.0:0 -> 198.51.100.47:4443 (PID 31337)
      ESTABLISHED  0.0.0.0:0 -> 198.51.100.47:8080 (PID 31442)

Summary:
  Rootkit Type:         Loadable Kernel Module (LKM)
  Probable Family:      Diamorphine variant
  Syscall Hooks:        4 (read, open, getdents64, kill)
  Hidden Modules:       2
  Hidden Processes:     3
  Hidden Connections:   2 (C2: 198.51.100.47)
  Modified Binaries:    3 (/usr/bin/ps, netstat, ls)
  Risk Level:           CRITICAL

Tools & Systems

• Cuckoo Sandbox — Automated dynamic analysis
• CAPE Sandbox — Config extraction + evasion detection
• Any.run — Cloud-based interactive sandbox
• Ghidra — NSA's reverse engineering framework
• dnSpy — .NET assembly decompiler
• PE Studio — Static PE analysis
• Volatility — Memory forensics
• YARA — Pattern-based malware identification

Run all tools in isolated sandbox environment. Never connect to production networks.

Workflow

1. Sample acquisition — Get sample via approved channel (incident response, threat intel)
2. Static analysis — 059-performing-static-malware-analysis-with-pe-studio + 145-deobfuscating-powershell-owx-malware or equivalent
3. Dynamic analysis — 139-analyzing-malware-behavior-with-cuckoo-sandbox or 147-performing-automated-malware-analysis-with-cape
4. IOC extraction — 074-performing-malware-ioc-extraction for IOCs
5. Reporting — Document behavior, IOCs, and attribution