detecting-rootkit-activity
Detects rootkit presence on compromised systems by identifying hidden processes, hooked system calls, modified kernel structures, and covert network…
Skill by mukul975
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: productivity
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Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/detecting-rootkit-activity/dev/shm/var/tmp
What's inside
- Skill name
detecting-rootkit-activity- Description
- 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.
- License
- Apache-2.0
- Instructions
- 283 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (4)
- LICENSE
- SKILL.md
- api-reference.md · references/
- agent.py · scripts/
SKILL.md (first lines)
# 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:
```bash
# 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:
```bash
# 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:
```bash
# 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 baselinesFrom mukul975/Anthropic-Cybersecurity-Skills, Apache-2.0.
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Signals
- Stars
- 34,941
- Forks
- 4,256
- Open issues
- 24
- Last commit (this folder)
- Aug 2, 2026 (2 months ago)
- Last release
- Jun 22, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
detecting-rootkit-activity skill. Agent Mart. https://agentmart.dev/skills/mukul975-detecting-rootkit-activity (last updated 2026-10-24)