Static Analysis & Heuristics for
Minecraft Mods

Next-generation static analysis powered by an autonomous neural model that continuously inspects and learns Minecraft mod architectures. Instantly identifies re-obfuscated SilentNet RAT variants, session token stealers, hidden C2 backdoors, raw sockets, and malicious exploits before launch.

22,383
Total Scans Processed
7,957
AI Trained Mod Samples
1,991
RATs & Malware Blocked
15,935
Clean Verified Mods

Analyze a Mod for Malware & Backdoors

Autonomous static analysis with zero runtime risk. Inspect bytecode, identify token grabbers, and detect zero-day evasion techniques.

Drag & drop your .JAR file to analyze

Full neural AI inspection, SilentNet RAT signatures, network backdoors, and obfuscated payloads.

Scan time < 300ms Upload max 256MB Fabric, Forge, NeoForge
Analyzing archive package...
1. Manifest Verification
2. ASM Bytecode Parsing
3. YARA & RAT Signatures
4. Neural AI Scoring
VERIFIED CLEAN MOD

No malicious signatures or backdoors detected

File: example.jar · SHA-256: 4f8b9e...

Risk Index
0
Behavioral Signals & Flags
Signatures & YARA Rules

Global Telemetry &
Scan Origins

Interactive geospatial telemetry tracking scan volume and threat vectors across the TraceJar network. 3D coordinates and telemetry arcs represent scan origins and detected malware propagation.

🇮🇹

Italy

Milan DC Hub

Active Node
9,513 Scans Processed
12.2% Threat Ratio
12ms Node Latency

Defense Mechanisms & Detection Engine

Minecraft threats rely on multi-stage evasion (String Encryption, Flow Obfuscation, Dynamic Classloading). TraceJar neutralizes them at the bytecode level.

Autonomous AI Neural Brain

Powered by an adaptive neural network trained on 3,400+ Minecraft mod architectures. Extracts opcode frequency distributions and structural feature vectors to self-learn emerging evasion techniques and detect zero-day exploits without manual signatures.

Modpack Batch Decompression

Autonomous multi-threaded unpacking for full .minecraft/mods folders (.zip) and Modrinth modpacks (.mrpack). Inspects and ranks up to 150 mod JARs simultaneously with zero runtime sandbox risk.

SilentNet Structural Attribution

Identifies the core behavioral triad of the SilentNet RAT (Session Token exfiltration + TrustAll TLS bypass + String Decryptor) remaining resilient even when class and method names are re-obfuscated per build.

Bundled YARA Pattern Engine

Performs byte-level pattern matching across compressed archives and embedded PE executables (DLL/EXE) disguised inside JAR resources as native payloads.

Real-time Threat Intel Forwarding

Automated webhook reporting channels broadcasting neutralized threats, neural model learning updates, and verified false-positive removals directly to partner Discord security servers.

Recent Scans & Sample Database

Real-time activity log of the latest samples inspected by the TraceJar cluster.

Real-Time Activity Feed
ID Module JAR Filename Analysis Verdict Timestamp
#7150 SCANNER CorzClientCrackedBYM4 (1).jar HIGH RISK 02:37
#7149 CHEAT Bloomclient-crackedby648k.exe.jar CHEAT DETECTED 02:30
#7148 SCANNER Visual-Client-1.18.9.jar CLEAN 00:40
#7147 SCANNER mullvad-client-fabric-1.21.11.jar HIGH RISK 00:39
#7146 SCANNER aurora.jar CLEAN 00:39
#7145 SCANNER LyricMod.jar HIGH RISK 00:05
#7144 SCANNER CorzClientCrackedBYM4 (1).jar HIGH RISK 23:55
#7143 SCANNER thisisunreal-0.2.3.jar CLEAN 23:54
#7142 CHEAT CorzClientCrackedBYM4 (1).jar CHEAT DETECTED 23:53
#7141 SCANNER CustomSkinLoader_Universal-15.1.jar CLEAN 23:05