Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
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Detect kernel-level rootkits in Linux memory dumps using Volatility3 linux plugins (check_syscall, lsmod, hidden_modules), rkhunter system scanning, and /proc vs /sys discrepancy analysis to identify hooked syscalls, hidden kernel modules, and tampered system structures.
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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.
Capture Linux physical memory using LiME kernel module or AVML for cloud instances.
Run linux.check_syscall, linux.lsmod, linux.hidden_modules, and linux.check_idt plugins to detect rootkit artifacts.
Compare module lists from /proc/modules, lsmod, and /sys/module to identify modules hidden from one view but present in another.
Run rkhunter and chkrootkit to detect known rootkit signatures, suspicious files, and modified system binaries.
JSON report containing detected syscall hooks, hidden kernel modules, modified IDT entries, suspicious /proc discrepancies, and rkhunter findings.
$ 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
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Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
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Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
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Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.
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Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.
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Analyze advanced persistent threat (APT) group techniques using MITRE ATT&CK Navigator to create layered heatmaps of adversary TTPs for detection gap analysis and threat-informed defense.
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Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query to detect suspicious administrative operations, impossible travel, privilege escalation, and resource modifications. Builds KQL queries for threat hunting in Azure environments. Use when investigating suspicious Azure tenant activity or building cloud SIEM detections.
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