Artemis Security AI

Artemis is an advanced security AI system designed to detect, analyze, and protect against various threats, including debuggers, sniffers, disassemblers, decompilers, and deobfuscators. It uses machine learning techniques and visual analysis to continuously improve its threat detection capabilities.

How Artemis Works

Process Monitoring: Artemis continuously monitors running processes on the system, comparing them against a list of known malicious processes and patterns.
Threat Analysis: When a potential threat is detected, Artemis analyzes it using a pre-trained machine learning model to determine its severity and criticality.
Visual Analysis: Artemis uses ArtemisVision to capture screenshots and compare them with known reverse engineering tool interfaces for enhanced detection.
Advanced Protection: For critical threats, Artemis implements advanced protection measures, including system isolation, IP blocking, and security patch application.
Continuous Learning: Artemis learns from each encountered threat, updating its threat model and improving its detection capabilities over time.
Anti-Emulation: The system includes measures to detect if it's running in a virtual machine or emulator, helping to prevent analysis by potential attackers.

Learning and Training Process

Initial Training Data: Artemis starts with a pre-defined set of threat data (threat_data.csv) that includes various threat types, their severity levels, and criticality.
Machine Learning Model: Using Microsoft ML.NET, Artemis trains a binary classification model to predict whether a detected threat is critical or not.
Continuous Learning: As Artemis encounters new threats or processes, it updates its threat model by:
- Adding new entries to the threat_data.csv file
- Retraining the machine learning model with the updated data
Window Title Analysis: Artemis learns to detect potential reverse engineering tools by analyzing similar window titles of detected processes.
Visual Learning: ArtemisVision captures and stores screenshots of known RE tools, continuously improving its visual detection capabilities.
Periodic Retraining: The system periodically retrains its model to incorporate newly learned threats and improve its accuracy.

Key Components

ProcessMonitor: Detects and analyzes running processes for potential threats.
ThreatAnalyzer: Uses machine learning to predict threat criticality and implement protection measures.
AntiEmulatorVM: Detects if the system is running in a virtual or emulated environment.
ArtemisVision: Captures and analyzes screenshots to detect potential RE tools visually.

Getting Started

Ensure you have the necessary dependencies installed (.NET Core, ML.NET, System.Windows.Forms).
Place the initial threat_data.csv file in the same directory as the executable.
Create a "Screenshots" folder in the same directory and add known RE tool screenshots named "KnownTool_*.png".
Run the Artemis Security AI program.

Artemis will start monitoring your system, performing visual analysis, learning from detected threats, and continuously improving its protection capabilities.

HyperionCSharp/ArtemisAI

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