Oss Forensics
Tommy-yw/RunbookHermes
Supply chain investigation, evidence recovery, and forensic analysis for GitHub repositories.
Agent skill
Extract and analyze Windows Registry hives with tools like RegRipper and Registry Explorer to uncover user activity, installed software, autostart/persistence entries, and evidence of system…
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-registry-for-artifacts -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-windows-registry-for-artifacts --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analyzing-windows-registry-for-artifacts .claude/skills/analyzing-windows-registry-for-artifacts && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "analyzing-windows-registry-for-artifacts" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-registry-for-artifacts into .claude/skills/analyzing-windows-registry-for-artifacts/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-windows-registry-for-artifacts", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-registry-for-artifactsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-registry-for-artifacts -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-windows-registry-for-artifacts --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/analyzing-windows-registry-for-artifacts .agents/skills/analyzing-windows-registry-for-artifacts && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "analyzing-windows-registry-for-artifacts" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-registry-for-artifacts into .agents/skills/analyzing-windows-registry-for-artifacts/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-windows-registry-for-artifacts", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-registry-for-artifacts -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-windows-registry-for-artifacts --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/analyzing-windows-registry-for-artifacts .cursor/skills/analyzing-windows-registry-for-artifacts && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "analyzing-windows-registry-for-artifacts" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-registry-for-artifacts into .cursor/skills/analyzing-windows-registry-for-artifacts/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-windows-registry-for-artifacts", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git --path skills/analyzing-windows-registry-for-artifacts--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-registry-for-artifacts -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-windows-registry-for-artifacts --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/analyzing-windows-registry-for-artifacts .gemini/skills/analyzing-windows-registry-for-artifacts && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "analyzing-windows-registry-for-artifacts" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-registry-for-artifacts into .gemini/skills/analyzing-windows-registry-for-artifacts/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-windows-registry-for-artifacts", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-windows-registry-for-artifactsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-registry-for-artifacts -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/analyzing-windows-registry-for-artifacts .github/skills/analyzing-windows-registry-for-artifacts && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "analyzing-windows-registry-for-artifacts" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-registry-for-artifacts into .github/skills/analyzing-windows-registry-for-artifacts/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-windows-registry-for-artifacts", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-registry-for-artifacts -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-windows-registry-for-artifacts --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/analyzing-windows-registry-for-artifacts .opencode/skills/analyzing-windows-registry-for-artifacts && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "analyzing-windows-registry-for-artifacts" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-registry-for-artifacts into .opencode/skills/analyzing-windows-registry-for-artifacts/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-windows-registry-for-artifacts", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
analyzing-windows-registry-for-artifactsExtract and analyze Windows Registry hives with tools like RegRipper and Registry Explorer to uncover user activity, installed software, autostart/persistence entries, and evidence of system…
Analyzing Windows Registry For Artifacts is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Extract and analyze Windows Registry hives with tools like RegRipper and Registry Explorer to uncover user activity, installed software, autostart/persistence entries, and evidence of system compromise. Use when investigating registry-based persistence, reconstructing user or system activity, or performing DFIR triage on a Windows image.
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).
It sits in Security, covering Digital forensics. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3gitpipFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
github.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Analyzing Windows Registry For Artifacts loads about 2.9k tokens when it runs, and up to ~3.5k if it reads all its reference files. Until then it costs about 95 tokens; SKILL.md has 427 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 427 words, ~2,942 tokens.
.claude/skills/analyzing-windows-registry-for-artifacts/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.# Mount the forensic image read-only
mkdir /mnt/evidence
mount -o ro,loop,offset=$((2048*512)) /cases/case-2024-001/images/evidence.dd /mnt/evidence
# Copy system registry hives
cp /mnt/evidence/Windows/System32/config/SAM /cases/case-2024-001/registry/
cp /mnt/evidence/Windows/System32/config/SYSTEM /cases/case-2024-001/registry/
cp /mnt/evidence/Windows/System32/config/SOFTWARE /cases/case-2024-001/registry/
cp /mnt/evidence/Windows/System32/config/SECURITY /cases/case-2024-001/registry/
cp /mnt/evidence/Windows/System32/config/DEFAULT /cases/case-2024-001/registry/
# Copy user-specific hives
cp /mnt/evidence/Users/*/NTUSER.DAT /cases/case-2024-001/registry/
cp /mnt/evidence/Users/*/AppData/Local/Microsoft/Windows/UsrClass.dat /cases/case-2024-001/registry/
# Copy transaction logs (for dirty hive recovery)
cp /mnt/evidence/Windows/System32/config/*.LOG* /cases/case-2024-001/registry/logs/
# Hash all extracted hives
sha256sum /cases/case-2024-001/registry/* > /cases/case-2024-001/registry/hive_hashes.txt# Install RegRipper
git clone https://github.com/keydet89/RegRipper3.0.git /opt/regripper
# Run RegRipper against NTUSER.DAT (user profile)
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/NTUSER.DAT \
-f ntuser > /cases/case-2024-001/analysis/ntuser_report.txt
# Run against SYSTEM hive
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SYSTEM \
-f system > /cases/case-2024-001/analysis/system_report.txt
# Run against SOFTWARE hive
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SOFTWARE \
-f software > /cases/case-2024-001/analysis/software_report.txt
# Run against SAM hive (user accounts)
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SAM \
-f sam > /cases/case-2024-001/analysis/sam_report.txt
# Run specific plugins
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/NTUSER.DAT \
-p userassist > /cases/case-2024-001/analysis/userassist.txt
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SYSTEM \
-p usbstor > /cases/case-2024-001/analysis/usbstor.txt# Using python-registry for targeted extraction
pip install python-registry
python3 << 'PYEOF'
from Registry import Registry
# Open SOFTWARE hive
reg = Registry.Registry("/cases/case-2024-001/registry/SOFTWARE")
# Check Run keys (autostart)
autorun_paths = [
"Microsoft\\Windows\\CurrentVersion\\Run",
"Microsoft\\Windows\\CurrentVersion\\RunOnce",
"Microsoft\\Windows\\CurrentVersion\\RunServices",
"Microsoft\\Windows\\CurrentVersion\\Policies\\Explorer\\Run",
"Wow6432Node\\Microsoft\\Windows\\CurrentVersion\\Run"
]
for path in autorun_paths:
try:
key = reg.open(path)
print(f"\n=== {path} (Last Modified: {key.timestamp()}) ===")
for value in key.values():
print(f" {value.name()}: {value.value()}")
except Registry.RegistryKeyNotFoundException:
pass
# Check installed services
key = reg.open("Microsoft\\Windows NT\\CurrentVersion\\Svchost")
print(f"\n=== Svchost Groups ===")
for value in key.values():
print(f" {value.name()}: {value.value()}")
PYEOF
# Check NTUSER.DAT for user-specific autorun
python3 << 'PYEOF'
from Registry import Registry
reg = Registry.Registry("/cases/case-2024-001/registry/NTUSER.DAT")
user_autorun = [
"Software\\Microsoft\\Windows\\CurrentVersion\\Run",
"Software\\Microsoft\\Windows\\CurrentVersion\\RunOnce",
"Software\\Microsoft\\Windows\\CurrentVersion\\Explorer\\StartupApproved\\Run"
]
for path in user_autorun:
try:
key = reg.open(path)
print(f"\n=== {path} (Last Modified: {key.timestamp()}) ===")
for value in key.values():
print(f" {value.name()}: {value.value()}")
except Registry.RegistryKeyNotFoundException:
pass
PYEOF# Extract UserAssist data (program execution history with ROT13 encoding)
python3 << 'PYEOF'
from Registry import Registry
import codecs, struct, datetime
reg = Registry.Registry("/cases/case-2024-001/registry/NTUSER.DAT")
ua_path = "Software\\Microsoft\\Windows\\CurrentVersion\\Explorer\\UserAssist"
key = reg.open(ua_path)
for guid_key in key.subkeys():
count_key = guid_key.subkey("Count")
print(f"\n=== {guid_key.name()} ===")
for value in count_key.values():
decoded_name = codecs.decode(value.name(), 'rot_13')
data = value.value()
if len(data) >= 16:
run_count = struct.unpack('<I', data[4:8])[0]
focus_count = struct.unpack('<I', data[8:12])[0]
timestamp = struct.unpack('<Q', data[60:68])[0] if len(data) >= 68 else 0
if timestamp > 0:
ts = datetime.datetime(1601,1,1) + datetime.timedelta(microseconds=timestamp//10)
print(f" {decoded_name}: Runs={run_count}, Focus={focus_count}, Last={ts}")
else:
print(f" {decoded_name}: Runs={run_count}, Focus={focus_count}")
PYEOF
# Extract Recent Documents (MRU lists)
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/NTUSER.DAT \
-p recentdocs > /cases/case-2024-001/analysis/recentdocs.txt
# Extract typed URLs (browser)
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/NTUSER.DAT \
-p typedurls > /cases/case-2024-001/analysis/typedurls.txt
# Extract typed paths in Explorer
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/NTUSER.DAT \
-p typedpaths > /cases/case-2024-001/analysis/typedpaths.txt# Computer name and OS version from SYSTEM hive
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SYSTEM \
-p compname > /cases/case-2024-001/analysis/system_info.txt
# Network interfaces and configuration
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SYSTEM \
-p nic2 >> /cases/case-2024-001/analysis/system_info.txt
# Wireless network history
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SOFTWARE \
-p networklist > /cases/case-2024-001/analysis/network_history.txt
# Timezone configuration
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SYSTEM \
-p timezone > /cases/case-2024-001/analysis/timezone.txt
# Shutdown time
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SYSTEM \
-p shutdown > /cases/case-2024-001/analysis/shutdown.txt
# Installed software from Uninstall keys
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SOFTWARE \
-p uninstall > /cases/case-2024-001/analysis/installed_software.txt| Concept | Description |
|---|---|
| Registry hive | Binary file storing a section of the registry (SAM, SYSTEM, SOFTWARE, NTUSER.DAT) |
| MRU (Most Recently Used) | Lists tracking recently accessed files, commands, and search terms |
| UserAssist | ROT13-encoded registry entries tracking program execution with timestamps |
| ShimCache | Application compatibility cache recording executed programs |
| AmCache | Detailed execution history including SHA-1 hashes of executables |
| BAM/DAM | Background/Desktop Activity Moderator tracking program execution in Win10+ |
| Last Write Time | Timestamp on registry keys indicating when they were last modified |
| Transaction logs | Journal files allowing recovery of registry state after improper shutdown |
| Tool | Purpose |
|---|---|
| RegRipper | Automated registry artifact extraction with plugin architecture |
| Registry Explorer | Eric Zimmerman GUI tool for interactive registry analysis |
| python-registry | Python library for programmatic registry hive parsing |
| RECmd | Eric Zimmerman command-line registry analysis tool |
| yarp | Yet Another Registry Parser for Python-based analysis |
| AppCompatCacheParser | Dedicated ShimCache/AppCompatCache parser |
| AmcacheParser | Dedicated AmCache.hve analysis tool |
| ShellBags Explorer | Specialized tool for analyzing ShellBag artifacts |
Scenario 1: Malware Persistence Investigation Extract SOFTWARE and NTUSER.DAT hives, check all Run/RunOnce keys for unauthorized entries, examine services for suspicious additions, check scheduled tasks registry keys, correlate autorun timestamps with malware execution timeline.
Scenario 2: User Activity Reconstruction Analyze UserAssist for program execution history, examine RecentDocs for accessed files, check TypedPaths for Explorer navigation, extract ShellBags for folder access patterns, build a timeline of user activity around the incident window.
Scenario 3: Unauthorized Software Detection Parse Uninstall keys for all installed applications, compare against approved software baseline, check BAM/DAM for recently executed programs not in approved list, examine AppCompatCache for execution evidence even after uninstallation.
Scenario 4: USB Data Exfiltration Investigation Extract USBSTOR entries from SYSTEM hive for connected devices, correlate device serial numbers with MountedDevices, check NTUSER.DAT MountPoints2 for user access to removable media, examine SetupAPI logs for first-connection timestamps.
Registry Analysis Summary:
System: DESKTOP-ABC123 (Windows 10 Pro Build 19041)
Timezone: Eastern Standard Time (UTC-5)
Last Shutdown: 2024-01-18 23:45:12 UTC
Autorun Entries:
HKLM Run: 5 entries (1 suspicious: "updater.exe" -> C:\ProgramData\svc\updater.exe)
HKCU Run: 3 entries (all legitimate)
Services: 142 entries (2 unknown: "WinDefSvc", "SysMonAgent")
User Activity (NTUSER.DAT):
UserAssist Programs: 234 entries
Recent Documents: 89 entries
Typed URLs: 45 entries
Typed Paths: 12 entries
USB Devices Connected:
- Kingston DataTraveler (Serial: 0019E06B4521) - First: 2024-01-10, Last: 2024-01-18
- WD My Passport (Serial: 575834314131) - First: 2024-01-15, Last: 2024-01-15
Installed Software: 127 applications
Suspicious Findings: 3 items flagged for review© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 3 other files (scripts, references) in skills/analyzing-windows-registry-for-artifacts of mukul975/Anthropic-Cybersecurity-Skills.
Open the folder on GitHubat commit 54a7988
Analyzing Windows Registry For Artifacts next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Analyzing Windows Registry For Artifacts this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Oss ForensicsTommy-yw/RunbookHermes | 546 | 3 repos | ~5k | Automated safety check: Pass | MIT | |
| Ctf Malwareljagiello/ctf-skills | 3.4k | — | ~2.1k | Automated safety check: Notes | MIT | |
| Dfirtransilienceai/communitytools | 563 | — | ~1.5k | Automated safety check: Pass | MIT | |
| TShark Traffic AnalysisAgentSecOps/SecOpsAgentKit | 220 | 1 repos | ~4.8k | Automated safety check: Notes | Custom licence | |
| Runtime Memory Sample Acquisitiondslsdzc/rev-skills | 135 | — | ~2k | Automated safety check: Pass | Apache-2.0 |
Tommy-yw/RunbookHermes
Supply chain investigation, evidence recovery, and forensic analysis for GitHub repositories.
ljagiello/ctf-skills
Provides malware analysis and network traffic techniques for CTF challenges.
transilienceai/communitytools
Digital forensics and incident response - Windows event log analysis, PCAP forensics, filesystem artifact analysis, AD attack detection, and timeline correlation.
AgentSecOps/SecOpsAgentKit
Guides authorized packet capture and analysis with TShark, Wireshark's command-line tool, for security investigations, malware detection and forensic examination of network traffic.
dslsdzc/rev-skills
Captures an analyzable sample from a live system when the target leaves no file on disk, by finding abnormal executable memory and the execution context that reached it.
zhaoxuya520/reverse-skill
A skill your agent uses for authorized digital forensics including memory dumps, disk timelines, PCAP investigation, artifact triage, and IR evidence preservation.
mukul975/Anthropic-Cybersecurity-Skills
Weighs infrastructure, TTP, malware code and timing evidence with the Diamond Model and competing hypotheses to reach a confidence-rated attribution.
mukul975/Anthropic-Cybersecurity-Skills
Walks through reverse engineering Go-compiled malware in Ghidra: parsing buildinfo and pclntab, recovering stripped function names and extracting dependencies.
mukul975/Anthropic-Cybersecurity-Skills
Guides forensic analysis of Windows LNK shortcut files and Jump Lists with LECmd, JLECmd and manual parsing to show file access and program execution.
mukul975/Anthropic-Cybersecurity-Skills
Hunts Windows malware persistence with Sysinternals Autoruns, covering run keys, services, scheduled tasks and drivers, with baseline comparison.
mukul975/Anthropic-Cybersecurity-Skills
Guides a Windows forensic examination of the NTFS Master File Table to recover deleted-file evidence, build timelines and spot timestomping.
mukul975/Anthropic-Cybersecurity-Skills
Detects DNS tunneling, ICMP exfiltration and HTTP-based covert channels in packet captures and DNS logs when hunting for hidden command-and-control traffic.
Categories
Extract and analyze Windows Registry hives with tools like RegRipper and Registry Explorer to uncover user activity, installed software, autostart/persistence entries, and evidence of system…. Analyzing Windows Registry For Artifacts is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Extract and analyze Windows Registry hives with tools like RegRipper and Registry Explorer to uncover user activity, installed software, autostart/persistence entries, and evidence of system compromise.
Analyzing Windows Registry For Artifacts fits situations like: investigating registry-based persistence; reconstructing user; system activity; performing DFIR triage on a Windows image.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-registry-for-artifacts -a claude-code`. Or copy the skill folder (skills/analyzing-windows-registry-for-artifacts in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/analyzing-windows-registry-for-artifacts in your project. Claude Code loads it when a task matches its description.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-registry-for-artifacts -a codex`. Or copy the skill folder (skills/analyzing-windows-registry-for-artifacts in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/analyzing-windows-registry-for-artifacts in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-registry-for-artifacts -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyzing-windows-registry-for-artifacts, .gemini/skills/analyzing-windows-registry-for-artifacts, .github/skills/analyzing-windows-registry-for-artifacts and .opencode/skills/analyzing-windows-registry-for-artifacts in your project.
Going by SKILL.md and its folder, Analyzing Windows Registry For Artifacts needs Python for the scripts in its folder and the command-line tools its instructions call (python3, git and pip). Our summary lists: Python 3.
SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Analyzing Windows Registry For Artifacts is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 534 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Analyzing Windows Registry For Artifacts: Oss Forensics (Tommy-yw/RunbookHermes, 546 stars), Ctf Malware (ljagiello/ctf-skills, 3.4k stars), Dfir (transilienceai/communitytools, 563 stars) and TShark Traffic Analysis (AgentSecOps/SecOpsAgentKit, 220 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.
Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.