E-Samarthak - (Multistage Attack Prediction using Machine Learning)

Modern Cyber Security threats such as Ransomware, Advanced Persistent Threats (APT), botnets, and other malware variants are increasingly categorized under Multistage attacks. It utilizes machine learning models and the MITRE ATT&CK Framework to detect and predict multistage attacks. These models are trained on top features and datasets aligned with adversary techniques, offering a comprehensive view of end-to-end attacks. The platform supports static and dynamic analysis of malware samples and provides in-depth analysis reports.

Use Cases

E-Samarthak is used to analyze Windows malware samples and its corresponding use cases are given below:-

• Provides Static and Dynamic Analysis.

• Static Analysis examines malware samples without execution, leveraging machine learning models to detect malicious binaries and align them with the MITRE Framework.

• Dynamic Analysis offers a Customizable sandbox environment for executing malicious executables, with options for various customizations.

• Dynamic Analysis collects artifacts for manual inspection or feeds them to offline ML models for malware identification.

Salient Features

• Identify Indicators of Compromise (IoC) linked to different adversary techniques

• Visualize attacks by mapping them to the MITRE ATT&CK Framework

• Analyze binaries and processes for deeper insights

• Leverage machine learning for detecting multistage attacks

• Predicts the cyber-attacks to strategize the early mitigation