detecting-rootkit-activity
Helps your agent detect rootkits, which are hidden malicious programs. It looks for hidden processes and system modifications that common tools cannot see.
What it does
This tool helps find hidden malicious programs (rootkits) on computers. It analyzes the system's memory to detect suspicious activities that normal tools can't see.
When to use it
- ✓When a computer seems infected, but security software finds nothing.
- ✓If you suspect a program is hiding within the system.
- ✓After a cleanup attempt that didn't solve the problem.
Example of what to ask your AI
“Check for rootkits on my computer.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
It examines the computer's memory for hidden processes, network connections, and files. It compares this information with what should be normal to find anomalies.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-rootkit-activityOr download just the file:
curl -L https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/main/skills/detecting-rootkit-activity/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Detecting Rootkit Activity
When to Use
- System shows signs of compromise but standard tools (Task Manager, netstat) show nothing abnormal
- Antivirus/EDR detects rootkit signatures but cannot identify the specific hiding mechanism
- Memory forensics reveals discrepancies between kernel data structures and user-mode tool output
- Investigating a persistent threat that survives remediation attempts and system reboots
- Validating system integrity after a suspected kernel-level compromise
Do not use as a first-line detection method; start with standard malware triage and escalate to rootkit analysis when hiding behavior is suspected.
Prerequisites
- Volatility 3 for memory forensics and kernel structure analysis
- GMER or Rootkit Revealer (Windows) for live system scanning
- rkhunter and chkrootkit (Linux) for filesystem and process integrity checks
- Sysinternals tools (Process Explorer, Autoruns, RootkitRevealer) for Windows analysis
- Memory dump from the suspected system (WinPmem, LiME)
- Clean baseline of the OS for comparison (known-good kernel module hashes)
Workflow
Step 1: Cross-View Detection for Hidden Processes
Compare process lists from different data sources to find discrepancies:
# Volatility: Compare process enumeration methods
# pslist - walks ActiveProcessLinks (EPROCESS linked list - what rootkits manipulate)
vol3 -f memory.dmp windows.pslist > pslist_output.txt
# psscan - scans physical memory for EPROCESS pool tags (rootkit-resistant)
vol3 -f memory.dmp windows.psscan > psscan_output.txt
# Compare outputs to find hidden processes
python3 << 'PYEOF'
pslist_pids = set()
psscan_pids = set()
with open("pslist_output.txt") as f:
for line in f:
parts = line.split()
if len(parts) > 1 and parts[1].isdigit():
pslist_pids.add(int(parts[1]))
with open("psscan_output.txt") as f:
for line in f:
parts = line.split()
if len(parts) > 1 and parts[1].isdigit():
psscan_pids.add(int(parts[1]))
hidden = psscan_pids - pslist_pids
if hidden:
print(f"[!] HIDDEN PROCESSES DETECTED (in psscan but not pslist):")
for pid in hidden:
print(f" PID: {pid}")
else:
print("[*] No hidden processes detected via cross-view analysis")
PYEOF
Step 2: Detect System Call Hooking
Identify hooks in the System Service Descriptor Table (SSDT) and Import Address Tables:
# Check SSDT for hooked system calls
vol3 -f memory.dmp windows.ssdt
# Identify hooks pointing outside ntoskrnl.exe or win32k.sys
vol3 -f memory.dmp windows.ssdt | grep -v "ntoskrnl\|win32k"
# Check for Inline hooks (detour patching)
vol3 -f memory.dmp windows.apihooks --pid 4 # System process
# IDT (Interrupt Descriptor Table) analysis
vol3 -f memory.dmp windows.idt
# Check for IRP (I/O Request Packet) hooking on drivers
vol3 -f memory.dmp windows.driverscan
vol3 -f memory.dmp windows.driverirp
Types of Rootkit Hooks:
━━━━━━━━━━━━━━━━━━━━━
SSDT Hook: Modifies System Service Descriptor Table entries to redirect
system calls through rootkit code (filters process/file listings)
IAT Hook: Patches Import Address Table of a process to intercept API calls
before they reach the kernel
Inline Hook: Overwrites the first bytes of a function with a JMP to rootkit code
(detour/trampoline technique)
IRP Hook: Intercepts I/O Request Packets to filter disk/network operations
at the driver level
DKOM: Direct Kernel Object Manipulation - unlinking structures like
EPROCESS from the ActiveProcessLinks list without hooking
Step 3: Analyze Kernel Modules and Drivers
Identify unauthorized kernel drivers that may be rootkit components:
# List all loaded kernel modules
vol3 -f memory.dmp windows.modules
# Scan for drivers in memory (including hidden/unlinked)
vol3 -f memory.dmp windows.driverscan
# Compare module lists to find hidden drivers
vol3 -f memory.dmp windows.modscan > modscan.txt
vol3 -f memory.dmp windows.modules > modules.txt
# Check driver signatures and verify against known-good baselines
vol3 -f memory.dmp windows.verinfo
# Dump suspicious driver for static analysis
vol3 -f memory.dmp windows.moddump --base 0xFFFFF80012340000 --dump
Step 4: Detect File and Registry Hiding
Identify files and registry keys hidden by the rootkit:
…
FAQ
What is a rootkit?
It's a type of malicious program designed to hide itself from users and security software, allowing other bad activities to occur undetected.
Why use this tool instead of antivirus?
Rootkits are designed to fool antivirus programs. This tool uses more advanced techniques to find them, even when they are well hidden.
Do I need technical knowledge to use it?
Yes, this tool is for those with some experience in computer security analysis, as it requires examining technical data.
Details
Original description by the author
Detects rootkit presence on compromised systems by identifying hidden processes, hooked system calls, modified kernel structures, and covert network connections using Volatility memory forensics, cross-view detection, and tools like GMER, rkhunter, chkrootkit, and RootkitRevealer. Use when standard tools (Task Manager, netstat, AV/EDR) show nothing abnormal but compromise is suspected. '
Popularity
- GitHub stars
- 35k
- Ranking position
- #5705
- License
- Apache-2.0
- Updated
- 8/31/2026
Comments
- …
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