What Is Malware Analysis: Definition, Benefits, Types, Techniques, Tools, and Strategies for Cyber Threat Detection

Malware analysis is required for detecting, mitigating, and preventing cyber threats. This article explores its types, including static, dynamic, hybrid, and manual analysis, and their differences. It covers automated malware analysis, the four key stages of malware examination, and the most effective tools. Finally, it provides insights into selecting the right malware analysis tools for businesses, ensuring robust cybersecurity defenses against evolving threats. 

What is Malware Analysis ?

Malware analysis is the process of examining and understanding how malware behaves to detect, mitigate, and prevent cyber threats. It involves static analysis, dynamic analysis, and hybrid techniques to assess malware code, behavior, and impact without infecting live systems. 

Malware Analysis and SOC Security Operations Center collaborate to detect, investigate, and mitigate cyber threats in real time. 

What are the Key Benefits of Malware Analysis

• Early Threat Detection: Identifies new and existing malware variants, enabling proactive defense against cyber threats.
• Stronger Incident Response: Helps security teams detect indicators of compromise (IOCs) and contain malware before it spreads.
• Enhanced Threat Intelligence: Provides insights into sophisticated malware techniques to strengthen security defenses.
• Advanced Security Solutions: Aids in developing malware analysis tools, automated detection systems, and sandbox environments.
• Protection Against Targeted Attacks: Assesses whether malware is part of a broader cyber campaign, enabling tailored security policies. Security firms conducted in-depth malware analysis to understand the deployed ransomware's mechanisms, which informed the development of decryption tools and remediation strategies when the Kaseya VSA software was compromised in 2021.
• Optimized Security Operations: Automated malware analysis accelerates threat detection and reduces manual workload for analysts.

What are the types of Malware Analysis and its differences?

The types of malware analysis are: 

What is Static Malware Analysis?

• Analysis without execution – Inspects malware code without running it, reducing infection risk. The U.S. Cybersecurity and Infrastructure Security Agency (CISA) offers a Malware Analysis service that provides stakeholders with dynamic analysis of malicious code, including recommendations for malware removal and recovery. 
• Static properties analysis – Examines file metadata, headers, and embedded strings to extract IOCs. 
• Code analysis – Uses disassemblers and decompilers to reverse engineer malware code. 
• Signature-based detection – Relies on known malware signatures for identification. 
• Limitations – Ineffective against obfuscated or encrypted malware. 

What is Dynamic Malware Analysis?

• Behavioral analysis – Observes malware execution to detect file modifications and network activity. 
• Sandbox technology – Runs malware in a secure environment to analyze its actions. 
• Detecting runtime changes – Identifies system modifications and attempts to evade detection.  
• Incident response – Helps security professionals gather forensic intelligence on cyber threats. Organizations like Altran Technologies utilized dynamic analysis techniques in 2019 to understand LockerGoga's behavior, enabling them to develop decryption tools and improve their incident response strategies. 
• Limitations – Some malware detects and evades sandbox environments. 

How Does Hybrid Malware Analysis Combine Static and Dynamic Techniques?

• Combining static code analysis with behavioral insights – Examines malware code before executing it in a controlled setting. 
• Using automated tools – Platforms like Falcon Sandbox and Cuckoo Sandbox integrate both methods. 
• Addressing evasive malware – Detects hidden behaviors in malware that alters actions in sandboxes. 
• Enhanced threat intelligence – Extracts deeper insights to improve security responses. 

What is Manual Malware Analysis and When is it Used?

• Reverse engineering malware code – Uses disassemblers and debuggers to analyze malware behavior. 
• Memory analysis – Examines memory dumps for real-time malware operations. 
• Identifying custom encryption and obfuscation techniques – Uncovers hidden malicious algorithms. 
• Used in advanced investigations – Essential for analyzing zero-day threats and complex cyber attacks. 
• Time-intensive process – Requires expert knowledge and extensive manual effort. 

How Does Automated Malware Analysis Improve Efficiency?

• Fully automated analysis – AI-driven tools process large malware datasets without human intervention. 
• Identifying patterns in malware behavior – Detects recurring attack patterns across malware families. 
• Utilizing cloud-based sandboxes – Runs malware in cloud-hosted environments for scalable analysis. 
• Reducing analysis time – Speeds up malware detection and incident response. 
• Limitations – Requires human oversight to interpret complex or evasive threats. 

Comparison of Malware Analysis Techniques

What Are the Four Stages of Malware Analysis?

The stages of malware analysis involve multiple techniques to uncover how malware behaves and the potential threats it poses to an organization. The four key stages are: 

• Static Properties Analysis – This stage examines a malware file without executing it, using static analysis techniques such as hash matching, string extraction, and header analysis to identify malicious code indicators. It helps security professionals detect known threats early and determine if deeper analysis is required. 
• Interactive Behavior Analysis – Also known as dynamic malware analysis, this stage runs the malware in a sandbox environment to observe how it behaves, including network connections, file modifications, and registry changes. This method helps detect malware attempts to evade static detection and uncover hidden payloads. 
• Fully Automated Analysis – This stage leverages automated malware analysis tools to rapidly process large numbers of malware samples, providing quick threat classification and behavioral insights. It enhances incident response by integrating with security platforms to flag malicious software in real-time. 
• Manual Code Reversing – The most in-depth stage, reverse engineering involves disassembling the malware code to understand its logic, decryption methods, and embedded exploits. This technique is essential for analyzing sophisticated malware designed to evade automated detection. 

What Are the Most Effective Malware Analysis Tools?

The effectiveness of a malware analysis tool depends on the type of malware analysis performed. An article from Varonis outlines several notable tools, including PeStudio, Process Hacker, ProcMon, ProcDot, and Autoruns, each serving specific purposes in the analysis process.  

Some of the most widely used malware analysis tools include: 

• Cuckoo Sandbox – An open-source sandbox technology for executing malware files in a virtualized environment to observe behavior. 
• Falcon Sandbox – A cloud-based malware analysis service that provides automated malware analysis and integrates with threat intelligence platforms. 
• Process Hacker – A powerful tool for detecting malicious software running in system memory. 
• IDA Pro – A commercial reverse engineering tool for static malware analysis, allowing security professionals to decompile and analyze malware code. 
• Wireshark – A network analysis tool used to inspect malware-infected traffic and identify suspicious connections. 
• YARA – A tool that helps malware analysts classify and detect malware variants using predefined rules. 
• Volatility – A memory forensics tool used for malware investigations, helping analysts extract information from compromised systems. 

How Can Businesses Choose the Right Malware Analysis Tools?

Organizations must evaluate: 

• Static vs. Dynamic Analysis Needs – Choose tools based on the required analysis techniques. 
• Automation Capabilities – Opt for fully automated analysis solutions to improve efficiency. 
• Threat Intelligence Integration – Ensure compatibility with cyber threat databases. 
• Sandboxing Requirements – Verify support for sandbox technology to safely analyze malware samples.