본문으로 건너뛰기
cccskills
무료GitHub에 공개

analyzing-windows-amcache-artifacts

Analyze Windows Amcache records to investigate applications, deleted executable traces, and drivers. Extract file details, compare SHA-1 hashes with malware databases, and combine records into a timeline to support incident investigations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Parses the Windows Amcache.hve registry hive with Eric Zimmerman's AmcacheParser and Timeline Explorer to extract evidence of program execution, application installation, and driver loading, including SHA-1 hash correlation with threat intel and timeline reconstruction. Use for Amcache forensics, program execution evidence gathering, or application compatibility cache investigations in DFIR work.

설치 방법 보기

이럴 때 유용합니다

  • Investigating traces of deleted executables
  • Checking software installed during an incident
  • Comparing file hashes with malware databases
  • Building a timeline from multiple forensic records

포함된 파일(4)

  • SKILL.md10.9 KB
  • LICENSE11.0 KB
  • references/api-reference.md2.0 KB
  • scripts/agent.py6.1 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Analyzing Windows Amcache Artifacts

When to Use

  • Determining which programs have existed or executed on a Windows system during incident response
  • Correlating SHA-1 hashes from Amcache against known malware databases (VirusTotal, CIRCL, MISP)
  • Building an application installation and execution timeline for forensic investigations
  • Identifying deleted executables that leave traces in Amcache even after file removal
  • Investigating insider threats by documenting which portable or unauthorized applications were present
  • Analyzing driver loading history to detect rootkits or malicious kernel modules

Do not use as sole proof of program execution. Amcache proves file existence and metadata registration, but ShimCache (AppCompatCache) and Prefetch provide stronger execution evidence. Use all three artifacts together for conclusive analysis.

Prerequisites

  • A forensic image or live triage copy of C:\Windows\appcompat\Programs\Amcache.hve (and associated .LOG1, .LOG2 transaction logs)
  • Eric Zimmerman's AmcacheParser (AmcacheParser.exe) downloaded from https://ericzimmerman.github.io/
  • Eric Zimmerman's Timeline Explorer for viewing parsed CSV output
  • Optionally: Registry Explorer for manual hive inspection
  • A SHA-1 whitelist of known-good executables (e.g., NSRL hashset) for filtering
  • .NET 6+ runtime installed (required by current EZ tools)
  • Write access to an output directory for CSV results

Workflow

Step 1: Acquire the Amcache.hve File

Extract the Amcache hive from a forensic image or live system:

# From a live system (requires elevated privileges and raw copy tool)
# Amcache.hve is locked by the system; use a raw disk copy tool
# Option A: FTK Imager - mount image and navigate to:
# C:\Windows\appcompat\Programs\Amcache.hve
# Also collect: Amcache.hve.LOG1, Amcache.hve.LOG2

# Option B: Using KAPE for automated triage collection
kape.exe --tsource C: --tdest D:\Evidence\%m --target Amcache

# Option C: From a mounted forensic image (E: = mounted image)
copy "E:\Windows\appcompat\Programs\Amcache.hve" D:\Evidence\
copy "E:\Windows\appcompat\Programs\Amcache.hve.LOG1" D:\Evidence\
copy "E:\Windows\appcompat\Programs\Amcache.hve.LOG2" D:\Evidence\

Always collect the transaction log files (.LOG1, .LOG2) alongside the hive. AmcacheParser replays uncommitted transactions from these logs to recover the most complete data.

Step 2: Parse Amcache with AmcacheParser

Run AmcacheParser against the acquired hive:

# Basic parsing with CSV output
AmcacheParser.exe -f "D:\Evidence\Amcache.hve" --csv "D:\Evidence\Output"

# Parse with a SHA-1 whitelist to exclude known-good entries (NSRL)
AmcacheParser.exe -f "D:\Evidence\Amcache.hve" -w "D:\Whitelists\nsrl_sha1.txt" --csv "D:\Evidence\Output"

# Parse with a SHA-1 inclusion list (only show matches against known-bad hashes)
AmcacheParser.exe -f "D:\Evidence\Amcache.hve" -b "D:\IOCs\malware_sha1.txt" --csv "D:\Evidence\Output"

# Include deleted entries with high-precision timestamps
AmcacheParser.exe -f "D:\Evidence\Amcache.hve" --csv "D:\Evidence\Output" -i --mp

AmcacheParser produces multiple CSV files in the output directory:

Output FileContents
Amcache_AssociatedFileEntries.csvFile entries with SHA-1 hashes, paths, sizes, and timestamps
Amcache_UnassociatedFileEntries.csvOrphaned file entries from older Amcache format
Amcache_ProgramEntries.csvInstalled program metadata (name, publisher, version, install date)
Amcache_DeviceContainers.csvUSB and device connection history
Amcache_DevicePnps.csvPlug-and-Play device driver information
Amcache_DriverBinaries.csvLoaded driver binaries with paths and hashes

Step 3: Analyze File Entries for Suspicious Programs

Open the AssociatedFileEntries.csv in Timeline Explorer and examine key columns:

Key columns to review:
- ProgramId          : Links file to its parent program entry
- SHA1               : Hash for threat intel lookups
- FullPath           : Original file location on disk
- FileSize           : Size of the executable
- FileKeyLastWriteTimestamp : When the Amcache entry was last updated
- Name               : File name
- Publisher           : Code signing publisher (blank = unsigned)
- BinProductVersion  : Version string from the PE header
- LinkDate           : PE compilation timestamp (useful for detecting timestomping)

Filter for suspicious indicators:

# In Timeline Explorer, apply these filters:

# 1. Find unsigned executables (potentially malicious)
Publisher column = (empty)

# 2. Find executables from suspicious paths
FullPath contains: \temp\, \appdata\, \downloads\, \public\, \programdata\

# 3. Find executables with recent timestamps during incident window
FileKeyLastWriteTimestamp between: 2026-03-15 00:00:00 and 2026-03-16 00:00:00

# 4. Find executables with suspicious compilation dates (timestomping)
LinkDate year < 2015 AND FileKeyLastWriteTimestamp year = 2026

Step 4: Correlate SHA-1 Hashes with Threat Intelligence

Extract SHA-1 hashes and check against malware databases:

# Extract unique SHA-1 hashes from the parsed output
# Using PowerShell to extract the SHA1 column
Import-Csv "D:\Evidence\Output\Amcache_AssociatedFileEntries.csv" |
  Select-Object -ExpandProperty SHA1 -Unique |
  Where-Object { $_ -ne "" } |
  Out-File "D:\Evidence\Output\extracted_hashes.txt"

# Check hashes against VirusTotal using vt-cli
foreach ($hash in Get-Content "D:\Evidence\Output\extracted_hashes.txt") {
    vt file $hash --format json | Select-Object -Property meaningful_name, last_analysis_stats
}

# Check hashes against CIRCL hashlookup
foreach ($hash in Get-Content "D:\Evidence\Output\extracted_hashes.txt") {
    Invoke-RestMethod -Uri "https://hashlookup.circl.lu/lookup/sha1/$hash"
}

# Cross-reference with NSRL to identify known-good vs. unknown
# Unknown hashes that are not in NSRL warrant closer investigation

Step 5: Analyze Program Entries for Unauthorized Installations

Review the ProgramEntries.csv for software the attacker may have installed:

Key columns in ProgramEntries:
- ProgramName        : Display name of installed application
- ProgramVersion     : Version string
- Publisher          : Software publisher
- InstallDate        : When the program was installed
- Source             : Installation source (msi, exe, etc.)
- UninstallKey       : Registry uninstall path
- PathsList         : Installation directories

Look for:

  • Remote access tools (AnyDesk, TeamViewer, ngrok, Chisel)
  • Hacking tools (Mimikatz, PsExec, Cobalt Strike)
  • Tunneling utilities (plink, socat, WireGuard)
  • Programs installed during the incident window
  • Programs installed to non-standard locations

Step 6: Analyze Driver Binaries for Rootkit Evidence

Review the DriverBinaries.csv for suspicious loaded drivers:

Key columns in DriverBinaries:
- DriverName         : Name of the driver
- DriverInBox        : Whether it shipped with Windows (false = third-party)
- DriverSigned       : Whether the driver has a valid signature
- DriverTimeStamp    : Compilation timestamp
- Product            : Product associated with the driver
- ProductVersion     : Driver version
- SHA1               : Hash of the driver binary

Filter for DriverInBox = false and DriverSigned = false to find unsigned third-party drivers that may be rootkits or vulnerable drivers used in BYOVD (Bring Your Own Vulnerable Driver) attacks.

Step 7: Build a Timeline from Amcache Data

Combine Amcache data with other artifacts for a comprehensive timeline:

# Merge Amcache CSV with other EZ Tools output using Timeline Explorer
# Load the following CSVs into Timeline Explorer:
# - Amcache_AssociatedFileEntries.csv (file evidence)
# - Amcache_ProgramEntries.csv (install evidence)
# - Prefetch output from PECmd.exe (execution evidence)
# - ShimCache output from AppCompatCacheParser.exe (execution evidence)

# Sort all entries by timestamp to reconstruct the attack sequence
# Timeline Explorer supports multi-file loading and column-based sorting

# Export the combined timeline
# File > Save to CSV > combined_timeline.csv

Key Concepts

TermDefinition
Amcache.hveA Windows registry hive at C:\Windows\appcompat\Programs\Amcache.hve that stores metadata about applications, files, and drivers for application compatibility purposes
Associated File EntryAn Amcache record linked to a specific program installation, containing file path, size, hash, and timestamps
Unassociated File EntryAn orphaned Amcache record from an older format that is not linked to a program entry; common on Windows 7/8 systems
Program EntryAmcache record containing installation metadata: program name, version, publisher, install date, and uninstall key
SHA-1 HashCryptographic hash stored in Amcache for each registered file, enabling malware identification through threat intelligence lookups
LinkDateThe PE compilation timestamp embedded in the executable header; discrepancy with file system timestamps may indicate timestomping
Transaction Logs.LOG1 and .LOG2 files containing uncommitted registry transactions that AmcacheParser replays for complete data recovery
NSRL (National Software Reference Library)NIST-maintained database of SHA-1 hashes for known commercial software, used as a whitelist to filter benign entries

Verification

  • Amcache.hve and transaction logs (LOG1, LOG2) were collected from the forensic image
  • AmcacheParser produced all expected CSV output files without errors
  • SHA-1 hashes were extracted and checked against VirusTotal or CIRCL hashlookup
  • Unsigned executables in suspicious paths have been flagged for further analysis
  • Program entries show all software installations within the incident window
  • Driver binaries have been checked for unsigned or out-of-box entries
  • LinkDate vs. FileKeyLastWriteTimestamp comparison has been performed to detect timestomping
  • Amcache findings are correlated with Prefetch and ShimCache for execution confirmation
  • Final timeline integrates Amcache data with other forensic artifacts

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Assess exposure of Windows secrets protected by DPAPI, the operating system’s data protection service, during authorized security tests. Guide examination and decryption of saved credentials and browser data using available user sessions, credentials, or backup keys.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Assessing saved credential exposure in authorized tests
  • Examining collected DPAPI files offline
  • Reviewing protected browser and RDP credentials
mukul975/Anthropic-Cybersecurity-Skills3.5만2026년 8월 31일 업데이트

Assess Shadow Credentials account takeover during authorized Active Directory testing. Examine permissions that allow public key registration, validate authentication without a password reset, and document credential cleanup, detection opportunities, and access control changes needed for remediation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Assessing risky permissions identified in BloodHound
  • Validating account takeover without resetting a password
  • Generating directory change records during security exercises
mukul975/Anthropic-Cybersecurity-Skills3.5만2026년 8월 31일 업데이트

Prepare for CMMC Level 2, a cybersecurity certification for defense contractors. Define the systems handling controlled information, review security requirements, calculate the SPRS assessment score, and organize remediation plans and evidence into a readiness report.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Define the assessment scope for systems handling controlled information
  • Calculate an SPRS score and prioritize unmet security requirements
  • Prepare security plans, remediation milestones, and assessment evidence
mukul975/Anthropic-Cybersecurity-Skills3.5만2026년 8월 31일 업데이트

Create disk images for investigations using dd or dcfldd on Linux. The workflow covers write protection, bit-for-bit copying, hash checks to verify integrity, and documentation of the acquisition process.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Preserving a suspect drive before investigation
  • Creating evidence copies of USB devices or memory cards
  • Verifying that a disk image matches its source
mukul975/Anthropic-Cybersecurity-Skills3.5만2026년 8월 31일 업데이트

Review Active Directory permissions with ldap3, a Python library for directory queries. Identify excessive access granted to non-administrative accounts, explain potential privilege escalation paths, and produce a JSON report with affected objects and remediation recommendations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Auditing excessive Active Directory permissions
  • Investigating privilege escalation paths from ordinary accounts
  • Reporting affected objects and permission remediation recommendations
mukul975/Anthropic-Cybersecurity-Skills3.5만2026년 8월 31일 업데이트

Inspect suspicious Android APK files without running them. Analyze permissions, app components, suspicious code patterns, and network indicators, then produce a JSON risk report to support malware triage and detection rule development.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Triage suspicious APK files without running them
  • Inspect dangerous permission combinations and suspicious API calls
  • Extract network indicators for malware detection rules
mukul975/Anthropic-Cybersecurity-Skills3.5만2026년 8월 31일 업데이트

mukul975의 스킬 모두 보기

이 스킬의 문제 신고