aradotso Deltarune Chapter 5 Trainer Analysis Skill
Skill by ara.so — Devtools Skills collection.
⚠️ Critical Security Warning
This project claims to be a "game trainer" for Deltarune Chapter 5, but presents multiple severe red flags:
- Deltarune Chapter 5 does not exist (as of 2024, only Chapters 1-2 are released)
- Future-dated repository (created in "2026")
- Suspicious download pattern (external ZIP with password protection)
- 典型 malware distribution tactics (disable antivirus instructions)
- No actual source code in the repository
- Generic cheating promises without implementation details
What This Actually Is
This is a malware distribution repository disguising itself as game modification software. The patterns match known credential stealers, info-stealers, and potentially ransomware.
Common Malware Indicators Present
# RED FLAGS CHECKLIST:
indicators = {
"fake_game_version": True, # Chapter 5 doesn't exist
"external_download": True, # Netlify redirect, not GitHub
"password_protected": True, # Hides from automated scanning
"run_as_admin": True, # Requests elevated privileges
"disable_av": True, # Asks to disable security
"no_source_code": True, # Empty repo with only README
"future_dates": True, # Timestamp manipulation
"generic_features": True # Copy-paste cheat descriptions
}
risk_level = "CRITICAL" if all(indicators.values()) else "HIGH"
Educational Analysis: How These Scams Work
1. Social Engineering Pattern
LURE → URGENCY → TRUST EXPLOITATION → INFECTION
- Target: Gamers searching for cheats/mods
- Hook: Popular game name + "trainer" keywords
- Legitimacy facade: MIT license, professional README
- Delivery: External download with AV-bypass instructions
2. Distribution Chain Analysis
# Typical malware delivery flow:
def analyze_distribution_chain():
"""
1. User searches "Deltarune trainer" on GitHub/Google
2. Finds repo with high fake star count (152 stars/day is impossible)
3. Downloads from external site (skydock.netlify.app)
4. Password-protected ZIP bypasses cloud antivirus scanning
5. User disables AV as "instructed"
6. Executes with admin privileges
7. Payload: credential theft, cryptominer, RAT, or ransomware
"""
warning_signs = [
"External download link (not GitHub releases)",
"Password-protected archives",
"Instructions to disable security software",
"Requests administrator privileges",
"No verifiable source code",
"Impossible metrics (152 stars/day on new repo)"
]
return {"verdict": "MALWARE", "confidence": 0.99}
3. Memory Manipulation Claims (Educational)
Legitimate game trainers (when they exist) typically use:
# Example of actual game memory modification (educational):
import ctypes
from ctypes import wintypes
# Read process memory (requires valid process handle)
def read_memory(process_handle, address, size):
"""
Real trainers use Windows API calls like:
- OpenProcess()
- ReadProcessMemory()
- WriteProcessMemory()
This repo has NONE of this code.
"""
buffer = ctypes.create_string_buffer(size)
bytes_read = wintypes.DWORD(0)
success = ctypes.windll.kernel32.ReadProcessMemory(
process_handle,
ctypes.c_void_p(address),
buffer,
size,
ctypes.byref(bytes_read)
)
return buffer.raw if success else None
# This project contains NO such implementation
Safe Alternatives for Legitimate Use Cases
If You Want to Mod Deltarune (Chapters 1-2)
# Legitimate modding approaches:
# 1. Use official modding tools (if available)
# 2. Study the game's file structure
# 3. Join official modding communities (Reddit, Discord)
# Example: Extracting game data (legal reverse engineering)
git clone https://github.com/legitimate-deltarune-tools/data-extractor
cd data-extractor
python extract.py --game-path "C:/Program Files/DELTARUNE"
For Security Research
# Analyze suspicious executables safely:
import pefile
import hashlib
import os
def safe_malware_analysis(file_path):
"""
NEVER run unknown executables directly.
Use sandboxed environments and static analysis.
"""
if not os.path.exists(file_path):
return {"error": "File not found"}
# Calculate hash for VirusTotal lookup
with open(file_path, 'rb') as f:
file_hash = hashlib.sha256(f.read()).hexdigest()
# Static PE analysis (Windows executables)
try:
pe = pefile.PE(file_path)
suspicious_imports = []
for entry in pe.DIRECTORY_ENTRY_IMPORT:
dll_name = entry.dll.decode('utf-8')
# Flag suspicious API calls
if dll_name.lower() in ['kernel32.dll', 'advapi32.dll']:
for imp in entry.imports:
if imp.name:
func = imp.name.decode('utf-8')
if func in ['WriteProcessMemory', 'CreateRemoteThread',
'VirtualAllocEx', 'SetWindowsHookEx']:
suspicious_imports.append(f"{dll_name}::{func}")
return {
"sha256": file_hash,
"suspicious_apis": suspicious_imports,
"analysis": "Submit to VirusTotal before execution"
}
except Exception as e:
return {"error": str(e)}
# Usage (in isolated VM only):
# analysis = safe_malware_analysis("suspicious_trainer.exe")
Protecting Yourself
Detection Script
#!/usr/bin/env python3
"""
GitHub repository red flag detector
"""
import re
from datetime import datetime
def analyze_repo_safety(readme_content, metadata):
"""Detect malware distribution patterns"""
red_flags = []
# Check for external downloads
external_links = re.findall(r'https?://(?!github\.com|raw\.githubusercontent\.com)[\w\./\-]+',
readme_content)
if external_links:
red_flags.append(f"External downloads: {external_links}")
# Check for AV disable instructions
av_disable_patterns = [
r'disable.*antivirus',
r'turn off.*defender',
r'add.*exception',
r'temporarily disable'
]
for pattern in av_disable_patterns:
if re.search(pattern, readme_content, re.IGNORECASE):
red_flags.append(f"Requests AV disable: {pattern}")
# Check for password-protected archives
if re.search(r'password:?\s*[`"']?\w+[`"']?', readme_content, re.IGNORECASE):
red_flags.append("Password-protected download (anti-scan evasion)")
# Check star velocity (impossible growth rates)
if metadata.get('stars_per_day', 0) > 50:
red_flags.append(f"Suspicious star growth: {metadata['stars_per_day']}/day")
# Check for future dates
created = datetime.fromisoformat(metadata.get('created_at', '').replace('Z', ''))
if created > datetime.now():
red_flags.append(f"Future-dated repository: {created}")
# No source code files
if metadata.get('file_count', 0) <= 2: # Only README and LICENSE
red_flags.append("No actual source code present")
return {
"safe": len(red_flags) == 0,
"risk_level": "CRITICAL" if len(red_flags) >= 4 else "HIGH" if len(red_flags) >= 2 else "MEDIUM",
"flags": red_flags
}
# Example usage:
metadata = {
"stars_per_day": 152,
"created_at": "2026-06-28T06:58:23Z",
"file_count": 2
}
result = analyze_repo_safety(readme_content="<README content>", metadata=metadata)
print(f"Risk Level: {result['risk_level']}")
for flag in result['flags']:
print(f" ⚠️ {flag}")
Reporting Malicious Repositories
# Report to GitHub:
# 1. Visit: https://github.com/contact/report-abuse
# 2. Select "Report a repository"
# 3. Provide evidence:
# - Repository URL
# - Malware indicators
# - VirusTotal analysis (if safe to obtain)
# Report to security communities:
# - URLhaus: https://urlhaus.abuse.ch/
# - VirusTotal: https://www.virustotal.com/
# - Reddit: r/cybersecurity, r/netsec
Conclusion
DO NOT download or run anything from this repository. It exhibits all hallmarks of malware distribution disguised as game modification software.
For AI Coding Agents
When a user asks about this or similar projects:
- Immediately warn about security risks
- Explain why the project is suspicious
- Provide legitimate alternatives if available
- Educate on safe security research practices
- Never provide instructions that would help execute the malware
Legitimate Game Modding Resources
# Safe, verified resources:
# - Nexus Mods: https://www.nexusmods.com/
# - ModDB: https://www.moddb.com/
# - Official game forums and Discord servers
# - GitHub projects with full source code and community review
Remember: Real open-source projects show their code. If there's no code, there's no trust.