Malware is the combination of two words, “malicious” and “software,” that infiltrate, damage, or disable computers, networks, or devices. In response to this dynamic threat, malware analysis has emerged as one of the most important practices that strive to split open malicious code to know what it can do, where it came from, and how it affects the computing device or network.
Types of Malware:
Viruses – Infect files and proliferate to others
Worms- Self-replicate across networks without human interaction
Trojans – Disguise like an ordinary program but perform malicious activities like opening backdoors.
Ransomware- Encrypt files or systems and demand money for decryption.
Spyware – Collects sensitive information without the user’s knowledge.
Adware – Display unwanted advertisements, often slowing down systems.
Rootkits – Provides unauthorized root-level access of a system to the attacker, allowing them to hide their presence and cover their malicious activities.
Knowledge of such types of malware gives analysts an understanding of the behaviour and intent of the code they are working with.
Purpose of Malware Analysis
• Threat identification: What kind of malware it is and how it works.
• Impact assessment: How much has the situation changed or will change?
• Countermeasures: Strategies to detect future attacks and defend against those attacks.
• Attribution: Who produced the malware or who conducted the attack?
The Malware Analysis Process
Malware analysis can be understood through statically and dynamically segmented techniques, both of which are quite important to determine the code and subsequently nullify its impact.
Static Analysis:
Malware inspection without the execution of the malware or its code is described as static analysis.
Main objective: To scan the binary or the executable code in order to collect valuable information about the code’s behaviour.
To perform static analysis, analysts generally use:
1. Hashing: Compute hash with MD5, SHA256, to identify known malware using databases like VirusTotal.
2. Disassemblers: Using tools such as IDA Pro, Ghidra decompiles or breaks down the binary into a human-readable format by translating machine code into something understandable.
3. Strings: The “strings” utility can expose an unknown number of embedded texts, URLs and potential IoCs (Indicators of Compromise), such as IP addresses or domains.
4. Header and metadata analysis: When the analyst is scanning through the headers of the executable, like the PE (Portable Executable) files, they can find related data about the compiler used, the file format, and much more.
Static analysis is harmless since the malware does not execute; however, there are also some disadvantages. For example, some complex malware may use encryption or packing techniques to make the static analysis difficult.
Dynamic Analysis:
This includes running the malware in a controlled environment called a sandbox, where it is executed and its behaviour is monitored live.
This technique proves to be effective when analyzing:
1. Changes in the file system: Some malware creates new files or modifies and deletes existing ones.
2. Changes in the registry: Some specific malware creates new registry keys or modifies already available keys for persistence on system reboot.
3. Network activity: Analysts note if the malware tries to connect to C2 servers or other external destinations.
4. System performance: The malware utilization level of the CPU and memory would indicate its consumption and also what it could possibly do.
Dynamic analysis is attained using the following tools:
•Cuckoo Sandbox: This is an extremely popular free, open-source platform for the automatic analysis of malicious programs.
•Wireshark: This helps monitor, capture, and analyze network traffic for the discovery of malicious communications.
• ProcMon: This tool tracks system-level transitions in real time and traces activities within the registry, file system, and processes.
Dynamic analysis is deeper but riskier because it might execute malware, even on a sandbox, thus potentially causing unintended changes to the system if proper isolation is not enforced.
Automated vs. Manual Malware Analysis
With the terrible increase in the daily flow of new malware samples, automated analysis tools are simply invaluable. They are useful when malware analysts want to categorize large quantities of malware and gain initial information. However, manual analysis is still critical to understanding complex malware strains that apply evasion techniques to avoid detection.
Automated Tools
Sandboxing: Automated sandboxes, such as Cuckoo or Any. Run, provide rapid behavioural analysis.
Threat intelligence integration: Some services, like AlienVault OTX or MISP, can provide contextual information by relating indicators observed with known families of malware.
While automated tools are incredibly useful for efficiency, no automated system can pick a complex attack or an unknown virus. That is why human expertise is needed to identify these sophisticated attacks or zero-day malware that automated systems may fail to pick.
Key Challenges in Malware Analysis
•Obfuscation and packing: Attackers may often encrypt or compress the malware so that the malicious functionality is not easily discovered. Thus, it cannot easily be detected and analyzed using the antivirus.
•Anti-debugging Techniques: Some malware can check if it is running on a secured and modified environment like sandbox or debugger and, based on that, stop execution, or change its functionality.
•Polymorphism and metamorphism: The malware can alter its code each time it infects the system (polymorphism), or it can rewrite itself (metamorphism) to evade signature-based detection.
Best Practices for Malware Analysis
Cybersecurity experts follow certain best practices to make sure that malware analysis is effective yet secure:
•Use isolated environments: Malware shall be analyzed only in a sandbox or VM without internet access.
•Tools are continually updated: Malware is changing extremely fast, and the tools for analysis need to be updated regularly to identify the latest threats.
•Document and share your findings: Analysts document their findings and contribute them to the broader cybersecurity communities. For example, threat intelligence platforms would be an excellent means of exchanging information.
•Multi-layered defence: Static and dynamic analysis, when combined, provides the best knowledge of malware.
