What is Malware Analysis?
Malware analysis is the technique of assessing and understanding malicious software. This involves identifying the malware's form, objective, and capabilities, assessing how it grows and infects systems, and recognizing the attacker's intentions and goals.
It involves looking deeply at malicious software to determine how it works, acts, and what it might do to systems. This process enables cyber security professionals to establish effective preventative measures, boost threat detection, and safeguard your organization's digital assets through the use of malware analysis tools and automated analysis techniques.
According to Techopedial in 2023, 3 million fresh malware cases are generated daily, 92% distributed via email, with an average of 49 days to be observed.
5 Types of Malware Analysis
Malware examination is vital in understanding, separating, and combating malicious software risks. There are different kinds of analysis, and each has a distinct way of determining how malware works and what it might do.
| Type of Analysis | Description |
|---|---|
| Static Analysis | Examining the malware's code, structure, and other characteristics without executing it. |
| Dynamic Analysis | Executing the malware in a controlled sandbox environment to monitor its behavior and interactions. |
| Behavioral Analysis | Analyzing the actions and system interactions of the malware during runtime. |
| Code Analysis | Analyzing the actual code of the malware to understand its internal logic and processes. |
| Memory Analysis | Evaluating the contents of a system's memory while the malware is actively running. |
Static Analysis
Static analysis involves examining the malware despite operating it. Analysts examine the malware's code, structure, and other characteristics to determine its performance, shortcomings, and behavior. This analysis examines binary code and reverse engineering and finds malware patterns and signatures.
Dynamic Analysis
Dynamic analysis includes performing the malware in a regulated setting, like a virtual machine or sandbox, to track its behavior, an approach often utilized in hybrid analysis. Reviewers monitor what the software does, how it interacts with the system, communicates to the network, and the changes it makes.
Dynamic malware analysis assists in identifying the malware's runtime behavior, features, and potential effects on an operating system through dynamic and interactive behavior analysis.
Behavioral Analysis
Behavioral analysis aims to determine what malware operates when it interacts with a machine. This includes tracking methods established by the malware, file adaptations, database changes, network connections, and system interactions.
By monitoring the malware's behavior, examiners can identify its motives, potential data theft or damage, and the processes it uses to achieve its goals.
Code Analysis
Code analysis includes analyzing the actual code of the malware to comprehend its internal processes, logic, and strategies, a process greatly aided by advanced analysis tools and techniques for code reversing. This type of analysis frequently requires reverse technical expertise to decompile, remove, or troubleshoot the malware's code.
Analysts can identify the malware's particular features, encryption methods, obstruction techniques, and any potential vulnerabilities that could be exploited by identifying the code using static properties analysis tools.
Memory Analysis
Memory analysis emphasizes evaluating the contents of a system's memory while the malware is actively running. This analysis can reveal malicious code injected into legitimate processes, attachments or modifications to system operations, and encryption keys or private information the malware may be manipulating in memory.
Memory analysis is a great way to find advanced, subtle malware that might be made to avoid traditional analysis methods.
Stages of Malware Analysis
Malware analysis examines malicious software (malware) to comprehend its operation, performance, and potential impact, often involving automated and interactive behavior analysis. Cybersecurity researchers, investigators, and defenders must understand malware and develop countermeasures. The stages typically include the following:
Stage 1: Collection
Obtain the malware sample for assessment. This can be done with honeypots, email attachments, malicious URLs, or compromised system files.
Stage 2: Documentation
Record data about how the malware was obtained, its origin, and any associated details. This documentation helps maintain a transparent chain of custody and assists other assessors working with the same sample.
Stage 3: Static Analysis:
- File Hashing: Create codes (MD5, SHA-1, SHA-256) to identify the sample and match it with known malware correctly.
- File Type Identification: Assess the file type (executable, records, code, etc.).
- Strings Analysis: Extract and analyze human-readable characters within the binary data, which offer details about its purpose.
- File Header Analysis: Check the file header to determine how it works collectively and if any signs have been breached.
Stage 4: Dynamic Analysis:
- Sandboxing: Execute the malware in controlled conditions (sandbox) to monitor its behavior without influencing the computer's operating system. This identifies file system, network, and registry changes.
- Behavior Analysis: Check the malware's actions, interactions, and system calls to determine its purpose and impact.
- Network Traffic Analysis: Capture and analyze network interactions started by the malware to find contact with command and control services or data exfiltration.
Stage 5: Code Analysis:
- Disassembly/Decompilation: Transform machine code into assembly or high-level computer languages that individuals can read to determine how the software works and operates, leveraging malware analysis tools for better code reversing.
- Function and API Calls Analysis: See how the malware works by identifying its functions and API calls.
Stage 6: Reverse Engineering:
Code reconstruction is the process of putting together the source code from the code that has been disassembled or decompiled.
Logic Analysis: If present, understand the malware's logic flows, decision points, and encryption mechanisms.
Stage 7: Behavioural Analysis:
- Payload Analysis: Recognize any payloads the malware delivers, such as additional executables, scripts, or data files.
- Malicious Actions: Determine whether the malware steals data, spreads, or damages files.
Stage 8: Artifacts Extraction:
- Indicators of Compromise (IOCs): Find unique patterns, network signatures, or artifacts that can be used to find similar malware in the future and protect against it.
- Techniques, Techniques, and Procedures (TTPs): Record the malware's methods to understand the attacker's strategies.
Stage 9: Report Generation:
Summarize the research results, including how the software acts, what it can do, how bad it could be, and any suggested defenses. Create a comprehensive report to share with other analysts, researchers, or security teams.
Stage 10: Threat Intelligence Sharing:
Share the results with safety groups, companies, and communities to help everyone learn more about new threats.
Malware Analysis Use Cases
Malware analysis examines malicious software's behavior, features, and impact, aligning with the definition that malware analysis is the process of understanding the full nature of the malware. It helps cybersecurity professionals, researchers, and incident responders understand risks and create viable defenses. Here are some frequent use cases:
Threat Intelligence
Analyzing malware assists security analysts in identifying emerging risks, their attack vectors, and target possibilities. This information can be shared with other groups and security communities to improve data about threats.
Incident Response
When a security incident occurs, analyzing the malware helps responders understand the attack's dimension, data compromise, and system infiltration. This information is essential for reducing the issue and resolving it.
Signature Creation
Malware signatures detect and prevent known threats in antivirus and intrusion detection systems. Malware analysis provides these signatures, allowing systems to detect and block future malware.
Behavior Analysis
Malware frequently displays specific behaviors when executed. Analysts can understand the activities of malware by analyzing its behavior in a duplicated scenario. These activities include modifying files, communicating via networks, modifying systems, and stealing data. This information helps to create signatures and detection mechanisms.
These also help security professionals understand how malware works, what commands it sends, and what data it seeks.
Reverse Engineering
Reverse engineering malware code can help to understand its functions and mechanisms. This helps find vulnerabilities that can be fixed and determine how the malware talks to its control and command servers.
Payload Analysis
Malware payloads contain data theft, remote access, and system manipulation. Analyzing the malicious code helps in understanding the potential influence of the malware on the system that was attacked, a fundamental component of malware analysis tools.
Attribution
Specific analysis offers perspectives into threat actors' strategies, techniques, and processes (TTPs), benefitting from code reversing and automated analysis methodologies. This information leads to threat intelligence, assisting entities in identifying potential attackers and their objectives.
Criminal Profiling
Analysts can make profiles of different threat actors or groups by studying the techniques, tactics, and procedures (TTPs) used by different malware campaigns. This helps them track and predict what these entities will do next.
Vulnerability Research
To get into systems, malware frequently exploits weaknesses in the software. Researchers in information security examine malware samples to discover new or unidentified vulnerabilities that must be secured to stop further attacks.
Honeypot Development
Honeypots are fake systems designed to draw attention and gather information about hackers and their strategies. Evaluating the activities of malware that attack honeypots helps understand current attack techniques and the nature of the malware. This can help analysts design and improve honeypots, which attract and trap attackers for analysis and better understand
Forensics and Legal Proceedings
When performing digital forensics, malware analysis helps gather proof concerning the source of an attack, its impact on systems, and the acts performed by the attackers. This evidence is essential in legal processes and may assist law enforcement authorities in investigating cybercriminals.
Security Research and Awareness
Researchers and analysts use malware analysis to understand better-developing structures, attack vectors, and new malware families. This information is shared across the security community to make more people aware of new and emerging dangers.
Leveraging Cybersecurity Services for Effective Malware Analysis
Malware analysis requires knowledge, the right resources, and tools, including static properties analysis and fully automated analysis systems. This is where partnering with a dedicated Cybersecurity Provider or utilizing third-party cybersecurity services may provide a significant impact, especially when they employ fully automated analysis and hybrid analysis in their approach.
Cybersecurity providers specialize in analyzing the latest threats and have in-depth knowledge of attack vectors and evasion techniques. They utilize cutting-edge tools like Cuckoo Sandbox to dissect complex malware. Rapid response services, utilizing automated malware analysis tools, aid quick recovery from attacks.
Providers offer proactive defense through vulnerability assessments, threat hunting, and continuous monitoring. They help maintain compliance by providing thorough analysis reports and demonstrating commitment to security. Leveraging these services mitigates risks without substantial capital expenditure on resources and expertise.
