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Analyzing Bootkit And Rootkit Samples

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mukul975
analyzing-bootkit-and-rootkit-samples

Analyzes bootkit and advanced rootkit malware infecting the Master Boot Record (MBR), Volume Boot Record (VBR), or UEFI firmware for below-OS persistence, covering boot sector analysis, UEFI module inspection, and anti-rootkit detection. Use when compromise survives OS reinstallation or antivirus/EDR fails to detect malware despite clear infection signs.

Overview

Publishermukul975
RepositoryAnthropic-Cybersecurity-Skills
Skill nameanalyzing-bootkit-and-rootkit-samples
Stars
32.9K
Forks
4K
Bundled files
2
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mukul975 on GitHub. Read the source before you install it.

Installation

Install the Analyzing Bootkit And Rootkit Samples AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git /tmp/Anthropic-Cybersecurity-Skills
mkdir -p .claude/skills
cp -r /tmp/Anthropic-Cybersecurity-Skills/skills/analyzing-bootkit-and-rootkit-samples .claude/skills/analyzing-bootkit-and-rootkit-samples
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Analyzing Bootkit And Rootkit Samples in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Analyzing Bootkit And Rootkit Samples on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Analyzing Bootkit And Rootkit Samples is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Analyzing Bootkit and Rootkit Samples

When to Use

  • A system shows signs of compromise that persist through OS reinstallation
  • Antivirus and EDR are unable to detect malware despite clear evidence of compromise
  • UEFI Secure Boot has been disabled or shows integrity violations
  • Memory forensics reveals rootkit behavior (hidden processes, hooked system calls)
  • Investigating nation-state level threats known to deploy bootkits (APT28, APT41, Equation Group)

Do not use for standard user-mode malware; bootkits and rootkits operate at a fundamentally different level requiring specialized analysis techniques.

Prerequisites

  • Disk imaging tools (dd, FTK Imager) for acquiring MBR/VBR sectors
  • UEFITool for UEFI firmware volume analysis and module extraction
  • chipsec for hardware-level firmware security assessment
  • Ghidra with x86 real-mode and 16-bit support for MBR code analysis
  • Volatility 3 for kernel-level rootkit artifact detection
  • Bootable Linux live USB for offline system analysis

Workflow

Step 1: Acquire Boot Sectors and Firmware

Extract MBR, VBR, and UEFI firmware for offline analysis:

bash
# Acquire MBR (first 512 bytes of disk)
dd if=/dev/sda of=mbr.bin bs=512 count=1

# Acquire first track (usually contains bootkit code beyond MBR)
dd if=/dev/sda of=first_track.bin bs=512 count=63

# Acquire VBR (Volume Boot Record - first sector of partition)
dd if=/dev/sda1 of=vbr.bin bs=512 count=1

# Acquire UEFI System Partition
mkdir /mnt/efi
mount /dev/sda1 /mnt/efi
cp -r /mnt/efi/EFI /analysis/efi_backup/

# Dump UEFI firmware (requires chipsec or flashrom)
# Using chipsec:
python chipsec_util.py spi dump firmware.rom

# Using flashrom:
flashrom -p internal -r firmware.rom

# Verify firmware dump integrity
sha256sum firmware.rom

Step 2: Analyze MBR/VBR for Bootkit Code

Examine boot sector code for malicious modifications:

bash
# Disassemble MBR code (16-bit real mode)
ndisasm -b16 mbr.bin > mbr_disasm.txt

# Compare MBR with known-good Windows MBR
# Standard Windows MBR begins with: EB 5A 90 (JMP 0x5C, NOP)
# Standard Windows 10 MBR: 33 C0 8E D0 BC 00 7C (XOR AX,AX; MOV SS,AX; MOV SP,7C00h)

python3 << 'PYEOF'
with open("mbr.bin", "rb") as f:
    mbr = f.read()

# Check MBR signature (bytes 510-511 should be 0x55AA)
if mbr[510:512] == b'\x55\xAA':
    print("[*] Valid MBR signature (0x55AA)")
else:
    print("[!] Invalid MBR signature")

# Check for known bootkit signatures
bootkit_sigs = {
    b'\xE8\x00\x00\x5E\x81\xEE': "TDL4/Alureon bootkit",
    b'\xFA\x33\xC0\x8E\xD0\xBC\x00\x7C\x8B\xF4\x50\x07': "Standard Windows MBR (clean)",
    b'\xEB\x5A\x90\x4E\x54\x46\x53': "Standard NTFS VBR (clean)",
}

for sig, name in bootkit_sigs.items():
    if sig in mbr:
        print(f"[{'!' if 'clean' not in name else '*'}] Signature match: {name}")

# Check partition table entries
print("\nPartition Table:")
for i in range(4):
    offset = 446 + (i * 16)
    entry = mbr[offset:offset+16]
    if entry != b'\x00' * 16:
        boot_flag = "Active" if entry[0] == 0x80 else "Inactive"
        part_type = entry[4]
        start_lba = int.from_bytes(entry[8:12], 'little')
        size_lba = int.from_bytes(entry[12:16], 'little')
        print(f"  Partition {i+1}: Type=0x{part_type:02X} {boot_flag} Start=LBA {start_lba} Size={size_lba} sectors")
PYEOF

Step 3: Analyze UEFI Firmware for Implants

Inspect UEFI firmware volumes for unauthorized modules:

bash
# Extract UEFI firmware components with UEFITool
# GUI: Open firmware.rom -> Inspect firmware volumes
# CLI:
UEFIExtract firmware.rom all

# List all DXE drivers (most common target for UEFI implants)
find firmware.rom.dump -name "*.efi" -exec file {} \;

# Compare against known-good firmware module list
# Each UEFI module has a GUID - compare against vendor baseline

# Verify Secure Boot configuration
python chipsec_main.py -m common.secureboot.variables

# Check SPI flash write protection
python chipsec_main.py -m common.bios_wp

# Check for known UEFI malware patterns
yara -r uefi_malware.yar firmware.rom
Known UEFI Bootkit Detection Points:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
LoJax (APT28):
  - Modified SPI flash
  - Added DXE driver that drops agent to Windows
  - Persists through OS reinstall and disk replacement

BlackLotus:
  - Exploits CVE-2022-21894 to bypass Secure Boot
  - Modifies EFI System Partition bootloader
  - Installs kernel driver during boot

CosmicStrand:
  - Modifies CORE_DXE firmware module
  - Hooks kernel initialization during boot
  - Drops shellcode into Windows kernel memory

MoonBounce:
  - SPI flash implant in CORE_DXE module
  - Modified GetVariable() function
  - Deploys user-mode implant through boot chain

ESPecter:
  - Modifies Windows Boot Manager on ESP
  - Patches winload.efi to disable DSE
  - Loads unsigned kernel driver

Step 4: Detect Kernel-Level Rootkit Behavior

Analyze the running system for rootkit artifacts:

bash
# Memory forensics for rootkit detection
# SSDT hook detection
vol3 -f memory.dmp windows.ssdt | grep -v "ntoskrnl\|win32k"

# Hidden processes (DKOM)
vol3 -f memory.dmp windows.psscan > psscan.txt
vol3 -f memory.dmp windows.pslist > pslist.txt
# Diff to find hidden processes

# Kernel callback registration (rootkits register callbacks for filtering)
vol3 -f memory.dmp windows.callbacks

# Driver analysis
vol3 -f memory.dmp windows.driverscan
vol3 -f memory.dmp windows.modules

# Check for unsigned drivers
vol3 -f memory.dmp windows.driverscan | while read line; do
    driver_path=$(echo "$line" | awk '{print $NF}')
    if [ -f "$driver_path" ]; then
        sigcheck -nobanner "$driver_path" 2>/dev/null | grep "Unsigned"
    fi
done

# IDT hook detection
vol3 -f memory.dmp windows.idt

Step 5: Boot Process Integrity Verification

Verify the integrity of the entire boot chain:

bash
# Verify Windows Boot Manager signature
sigcheck -a C:\Windows\Boot\EFI\bootmgfw.efi

# Verify winload.efi
sigcheck -a C:\Windows\System32\winload.efi

# Verify ntoskrnl.exe
sigcheck -a C:\Windows\System32\ntoskrnl.exe

# Check Measured Boot logs (if TPM is available)
# Windows: BCDEdit /enum firmware
bcdedit /enum firmware

# Verify Secure Boot state
Confirm-SecureBootUEFI  # PowerShell cmdlet

# Check boot configuration for tampering
bcdedit /v

# Look for boot configuration changes
# testsigning: should be No
# nointegritychecks: should be No
# debug: should be No
bcdedit | findstr /i "testsigning nointegritychecks debug"

Step 6: Document Bootkit/Rootkit Analysis

Compile comprehensive analysis findings:

Analysis should document:
- Boot sector (MBR/VBR) integrity status with hex comparison
- UEFI firmware module inventory and integrity verification
- Secure Boot status and any bypass mechanisms detected
- Kernel-level hooks (SSDT, IDT, IRP, inline) identified
- Hidden processes, drivers, and files discovered
- Persistence mechanism (SPI flash, ESP, MBR, kernel driver)
- Boot chain integrity verification results
- Attribution to known bootkit families if possible
- Remediation steps (reflash firmware, rebuild MBR, replace hardware)

Key Concepts

TermDefinition
BootkitMalware that infects the boot process (MBR, VBR, UEFI) to execute before the operating system loads, gaining persistent low-level control
MBR (Master Boot Record)First 512 bytes of a disk containing bootstrap code and partition table; MBR bootkits replace this code with malicious loaders
UEFI (Unified Extensible Firmware Interface)Modern firmware interface replacing BIOS; UEFI bootkits implant malicious modules in firmware volumes or modify the ESP
Secure BootUEFI security feature verifying digital signatures of boot components; bootkits like BlackLotus exploit vulnerabilities to bypass it
SPI FlashFlash memory chip storing UEFI firmware; advanced bootkits like LoJax and MoonBounce modify SPI flash for firmware-level persistence
DKOM (Direct Kernel Object Manipulation)Rootkit technique modifying kernel structures to hide processes, files, and network connections without hooking functions
Driver Signature Enforcement (DSE)Windows security feature requiring kernel drivers to be digitally signed; bootkits disable DSE during boot to load unsigned rootkit drivers

Tools & Systems

  • UEFITool: Open-source UEFI firmware image editor and parser for inspecting firmware volumes, drivers, and modules
  • chipsec: Intel hardware security assessment framework for verifying SPI flash protection, Secure Boot, and UEFI configuration
  • Volatility: Memory forensics framework with SSDT, IDT, callback, and driver analysis plugins for kernel rootkit detection
  • GMER: Windows rootkit detection tool scanning for SSDT hooks, IDT hooks, hidden processes, and modified kernel modules
  • Bootkits Analyzer: Specialized tool for analyzing MBR/VBR code including disassembly and comparison against known-good baselines

Common Scenarios

Scenario: Investigating Persistent Compromise Surviving OS Reinstallation

Context: An organization reimaged a compromised workstation, but the same C2 beaconing resumed within hours. Standard disk forensics finds no malware. UEFI bootkit is suspected.

Approach:

  1. Boot from a Linux live USB to avoid executing any compromised OS components
  2. Dump the SPI flash firmware using chipsec or flashrom for offline analysis
  3. Dump the MBR and VBR sectors with dd for boot sector analysis
  4. Copy the EFI System Partition for bootloader integrity verification
  5. Open the SPI dump in UEFITool and compare module GUIDs against vendor-provided firmware
  6. Look for additional or modified DXE drivers that should not be present
  7. Analyze any suspicious modules with Ghidra (x86_64 UEFI module format)
  8. Verify Secure Boot configuration and check for exploit-based bypasses

Pitfalls:

  • Analyzing the system while the compromised OS is running (rootkit may hide from live analysis)
  • Not checking SPI flash (only analyzing disk-based boot components misses firmware-level implants)
  • Assuming Secure Boot prevents all bootkits (known bypasses exist, e.g., CVE-2022-21894)
  • Not preserving the original firmware dump before reflashing (critical evidence for attribution)

Output Format

BOOTKIT / ROOTKIT ANALYSIS REPORT
====================================
System:           Dell OptiPlex 7090 (UEFI, TPM 2.0)
Firmware Version: 1.15.0 (Dell)
Secure Boot:      ENABLED (but bypassed)
Capture Method:   Linux Live USB + chipsec SPI dump

MBR/VBR ANALYSIS
MBR Signature:    Valid (0x55AA)
MBR Code:         MATCHES standard Windows 10 MBR (clean)
VBR Code:         MATCHES standard NTFS VBR (clean)

UEFI FIRMWARE ANALYSIS
Total Modules:    287
Vendor Expected:  285
Extra Modules:    2 UNAUTHORIZED
  [!] DXE Driver GUID: {ABCD1234-...} "SmmAccessDxe_mod" (MODIFIED)
      Original Size: 12,288 bytes
      Current Size:  45,056 bytes (32KB ADDED)
      Entropy: 7.82 (HIGH - encrypted payload)

  [!] DXE Driver GUID: {EFGH5678-...} "UefiPayloadDxe" (NEW - not in vendor firmware)
      Size: 28,672 bytes
      Function: Drops persistence agent during boot

BOOT CHAIN INTEGRITY
bootmgfw.efi:     MODIFIED (hash mismatch, Secure Boot bypass via CVE-2022-21894)
winload.efi:      MODIFIED (DSE disabled at load time)
ntoskrnl.exe:     CLEAN (but unsigned driver loaded after boot)

KERNEL ROOTKIT COMPONENTS
Driver:           C:\Windows\System32\drivers\null_mod.sys (unsigned, hidden)
SSDT Hooks:       3 (NtQuerySystemInformation, NtQueryDirectoryFile, NtDeviceIoControlFile)
Hidden Processes: 2 (PID 6784: beacon.exe, PID 6812: keylog.exe)
Hidden Files:     C:\Windows\System32\drivers\null_mod.sys

ATTRIBUTION
Family:           BlackLotus variant
Confidence:       HIGH (CVE-2022-21894 exploit, ESP modification pattern matches)

REMEDIATION
1. Reflash SPI firmware with clean vendor image via hardware programmer
2. Rebuild EFI System Partition from clean Windows installation media
3. Reinstall OS from verified media
4. Enable all firmware write protections
5. Update firmware to latest version (patches CVE-2022-21894)

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Analyzing Bootkit And Rootkit Samples AI skill do?

Analyzes bootkit and advanced rootkit malware infecting the Master Boot Record (MBR), Volume Boot Record (VBR), or UEFI firmware for below-OS persistence, covering boot sector analysis, UEFI module inspection, and anti-rootkit detection. Use when compromise survives OS reinstallation or antivirus/EDR fails to detect malware despite clear infection signs.

Why use Analyzing Bootkit And Rootkit Samples on TypingMind?

Because you install it once and use it with any model. Analyzing Bootkit And Rootkit Samples is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Analyzing Bootkit And Rootkit Samples in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-bootkit-and-rootkit-samples. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Analyzing Bootkit And Rootkit Samples?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Analyzing Bootkit And Rootkit Samples?

As many as you like. As long as a model supports skills, you can use Analyzing Bootkit And Rootkit Samples with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Analyzing Bootkit And Rootkit Samples AI skill free?

Yes. It is published on GitHub by mukul975 under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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