DeepRay® is a detection technology designed to identify advanced and evasive malware threats directly in process memory. It focuses on analyzing runtime behavior and memory artifacts instead of relying solely on file-based detection. This approach enables the identification of packed malware and sophisticated attack techniques that attempt to avoid traditional scanning methods. Supported by machine learning models, DeepRay® evaluates potentially malicious or suspicious artifacts within the process memory. It applies advanced heuristics and rule-based detection mechanisms to uncover hidden or obfuscated threats. The technology is also capable of detecting complex attack patterns, including “Living off the Land” techniques, where legitimate system tools are misused for malicious purposes. DeepRay® is engineered to operate efficiently, combining heuristic analysis and machine learning to provide effective detection while maintaining controlled resource usage.

Key Features

Advanced In‑Memory Analysis Heuristics Analyzes process memory for malicious patterns.

• Detection of suspicious memory artifacts
• Identification of packed or obfuscated malware

IoC In‑Memory Scanning (YARA) Searches memory for known indicators of compromise.

• YARA-based rule matching
• Detection of predefined threat indicators

Custom Rules (YARA) Supports user-defined detection logic.

• Creation of custom YARA rules
• Adaptation to organization-specific threat scenarios

Machine Learning Support Enhances detection accuracy and efficiency.

• ML-assisted artifact evaluation
• Optimized balance between detection capability and resource usage

Detection of Advanced Threat Techniques Identifies sophisticated attack methods.

• Recognition of fileless attacks
• Detection of “Living off the Land” activity

Benefits

Detection of Evasive Malware Identifies threats that bypass traditional file scanning.

• Recognition of packed malware
• Analysis independent of file presence

Improved Visibility into Runtime Activity Provides insight into process memory behavior.

• Identification of suspicious in-memory artifacts
• Detection during execution phase

Customizable Threat Detection Allows adaptation to specific security requirements.

• Custom YARA rule implementation
• Flexible IoC-based scanning

Resource-Efficient Operation Maintains system performance.

• Machine learning–supported optimization
• Designed for efficient runtime analysis

Enhanced Protection Against Modern Attacks Addresses complex and fileless techniques.

• Detection of advanced persistent threats
• Coverage of “Living off the Land” scenarios