Malware analysis is the process of examining malicious software, also known as malware, to understand its behavior, functionality, and potential impact on computer systems and networks. The goal of malware analysis is to gain insights into the inner workings of malware in order to develop effective countermeasures, detect and remove the malware from infected systems, and prevent future infections.
There are different approaches to malware analysis:
Static Analysis:
Static Analysis: This involves examining the malware without executing it. Analysts dissect the code to understand its structure, identify suspicious or malicious functions, and extract indicators of compromise (IOCs). Static analysis techniques include examining file headers, disassembling or decompiling code, and inspecting strings and embedded resources. Here are some key aspects of static analysis:
- File Analysis: The first step in static analysis is obtaining the malware file itself. This can be done by capturing it from a compromised system, receiving it through threat intelligence feeds, or acquiring it from other trusted sources. Once the malware file is obtained, it is essential to determine its file type, such as an executable file (e.g., .exe), a script file (e.g., .vbs), or a document file (e.g., .docx), as different types may require different analysis techniques.
- File Header Examination: Analyzing the file header provides initial information about the file, such as the file format, specific file markers, and other metadata. For example, in Windows executables (PE files), the file header contains information about the file's entry point, sections, and imported and exported functions. Analyzing the file header can help identify the file's format and potential malicious characteristics.
- String Analysis: Examining the strings within the malware file can reveal valuable information about its functionality and purpose. Analysts search for specific keywords, URLs, IP addresses, or other indicators of compromise (IOCs) embedded within the code. These strings may provide clues about the malware's command and control infrastructure, potential payloads, or target-specific information.
- Disassembly and Decompilation: Disassembling or decompiling the code is a crucial step in static analysis. Disassembly is the process of converting machine code instructions into human-readable assembly language instructions, while decompilation involves transforming compiled code into a higher-level programming language. These techniques enable analysts to understand the logic, control flow, and individual functions within the malware. Tools like IDA Pro, Ghidra, or radare2 are commonly used for disassembly and decompilation.
- Control Flow Analysis: Analyzing the control flow of the malware helps determine the sequence of instructions and how the code branches or loops. Understanding the control flow can reveal important behaviors such as anti-analysis techniques, encryption or obfuscation routines, and the presence of any exploits or vulnerabilities the malware may utilize.
- API and Library Calls: Malware often relies on operating system APIs (Application Programming Interfaces) and library calls to perform various actions, such as file manipulation, network communication, or process manipulation. Identifying and analyzing these API and library calls can help determine the malware's capabilities and potential malicious activities.
- Code Obfuscation and Anti-Analysis Techniques: Malware authors employ various obfuscation techniques to evade detection and hinder analysis. These techniques can include encryption, packing, code obfuscation, or anti-debugging measures. During static analysis, analysts attempt to deobfuscate or unpack the code to reveal its true nature and functionality.
- Signature Generation: Static analysis can lead to the creation of signatures or patterns that can be used by antivirus software or intrusion detection systems to detect and block similar instances of the malware. These signatures are based on unique characteristics or behavioral patterns identified during the analysis process.
Dynamic Analysis:
Dynamic Analysis: This involves executing the malware in a controlled environment, such as a virtual machine or sandbox, to observe its behavior. Analysts monitor system calls, network traffic, and file modifications to understand how the malware interacts with the system. Dynamic analysis helps identify the malware's capabilities, such as data exfiltration, command and control communication, or payload delivery. Here are the key aspects of dynamic analysis:
- Controlled Execution Environment: Dynamic analysis is typically performed in a controlled environment such as a virtual machine (VM) or a sandbox. This isolated environment provides a safe space for executing the malware without affecting the host system or network. The controlled environment allows analysts to monitor and capture various behaviors and interactions of the malware.
- Behavior Monitoring: During dynamic analysis, the actions and behaviors of the malware are observed and recorded. This includes monitoring system calls, registry modifications, file system activities, network communication, and interactions with other processes. Behavior monitoring helps analysts understand the capabilities and intentions of the malware, such as whether it attempts to modify files, establish network connections, or steal sensitive information.
- Network Traffic Analysis: Analyzing the network traffic generated by the malware is an important aspect of dynamic analysis. By capturing and inspecting the network packets, analysts can identify the communication protocols used, destination IP addresses, URLs contacted, and data exchanged between the malware and external entities. This helps in determining whether the malware establishes command and control channels, exfiltrates data, or downloads additional payloads.
- Malware Payload Analysis: Dynamic analysis allows analysts to observe and analyze the payloads delivered by the malware. Payloads may include additional files, executables, or scripts that are downloaded and executed during the malware's operation. By analyzing the payloads, analysts can understand the functionality and potential impact of the malware, such as whether it installs backdoors, encrypts files, or performs other malicious activities.
- Memory Analysis: Dynamic analysis also involves analyzing the memory of the infected system while the malware is running. This includes examining the malware's code injection techniques, process memory modifications, and runtime behavior. Memory analysis can reveal important details such as encryption keys, data structures, or sensitive information manipulated or stored by the malware.
- Anti-Analysis Evasion: Malware authors often employ techniques to evade analysis, including detecting virtualized environments, anti-debugging measures, or anti-analysis routines. During dynamic analysis, analysts may employ countermeasures or debugging techniques to overcome these evasion techniques and gain deeper insights into the malware's behavior.
- Dynamic Hooking: Dynamic hooking involves intercepting and monitoring specific function calls made by the malware. By hooking into certain functions, analysts can intercept and modify the parameters or behavior of the malware. This technique allows analysts to observe the impact of certain actions, manipulate the malware's behavior, or analyze the data passed between the malware and the system.
Behavioral Analysis:
Behavioral Analysis: This focuses on observing the actions and interactions of malware with the host system. Analysts monitor system changes, registry modifications, file system activities, and network traffic to understand the impact and potential risks associated with the malware. Behavioral analysis helps in detecting anomalies and identifying the malware's intended actions.
- System Monitoring: Behavioral analysis involves monitoring the behavior of the malware as it interacts with the host system. This includes observing system-level changes such as file modifications, registry modifications, process creation and termination, network connections, and other system events. By monitoring these activities, analysts can gain insights into the malware's behavior patterns and identify any suspicious or malicious actions.
- Anomaly Detection: Behavioral analysis aims to detect anomalies in the behavior of the malware. This involves establishing a baseline of normal system behavior and then comparing the observed behavior of the malware against this baseline. Deviations from the normal behavior can indicate potentially malicious activities, such as unauthorized access, data exfiltration, or attempts to escalate privileges. Anomaly detection techniques can include statistical analysis, machine learning algorithms, or rule-based systems.
- Event Logging and Analysis: During behavioral analysis, events generated by the malware and the system are logged and analyzed. These event logs provide a chronological record of the actions performed by the malware and their impact on the system. By analyzing these logs, analysts can identify patterns, correlations, and dependencies between different events, helping them understand the progression of the malware's behavior.
- Network Traffic Analysis: Behavioral analysis includes analyzing the network traffic generated by the malware during its execution. This involves capturing and inspecting the packets exchanged between the malware and external entities, such as command and control servers or other compromised systems. Network traffic analysis helps in understanding the communication protocols used, the data transferred, and the potential malicious activities conducted over the network.
- Payload Analysis: Behavioral analysis also involves analyzing the payloads delivered by the malware. These payloads can include additional files, scripts, or executables that are downloaded or executed by the malware. By examining the payloads, analysts can understand the specific functionalities or capabilities introduced by the malware, such as keylogging, screen capturing, or data encryption.
- Indicators of Compromise (IOCs): Behavioral analysis helps in identifying and extracting indicators of compromise (IOCs) from the malware's behavior. IOCs can include IP addresses, URLs, file names, registry keys, or specific behavior patterns associated with the malware. These IOCs are used to develop detection signatures or rules that can be applied to identify and mitigate similar instances of the malware.
- Impact Assessment: Behavioral analysis provides insights into the potential impact of the malware on the infected system. By understanding the behavior of the malware, analysts can assess the risks posed by the malware, such as data loss, system instability, or unauthorized access. This information is crucial for developing appropriate mitigation strategies and implementing necessary security controls.
Code Reversing:
Code Reversing: This involves reverse engineering the malware's code to understand its logic and functionality. Analysts use tools like disassemblers and debuggers to analyze the code, identify algorithms, encryption techniques, and vulnerabilities that the malware exploits. Code reversing helps in understanding the malware's inner workings and can aid in developing effective countermeasures.
- Disassembly: Disassembly is the process of converting machine code, which is in binary form, into human-readable assembly language instructions. Disassemblers analyze the binary code and generate assembly instructions, which represent the low-level operations performed by the malware. Disassembly helps in understanding the control flow, function calls, and basic operations of the malware.
- Decompilation: Decompilation involves converting compiled code, such as executable files, into a higher-level programming language, such as C or C++. Decompilers analyze the binary code and attempt to reconstruct the original source code, albeit with some level of approximation. Decompilation helps in understanding the overall structure, algorithms, and logic of the malware.
- Control Flow Analysis: Analyzing the control flow of the malware involves understanding how the code branches, loops, and makes decisions during execution. This analysis helps in identifying the different paths the malware can take, conditions for execution, and how it responds to various inputs or events. Control flow analysis aids in understanding the decision-making processes and behavior of the malware.
- Function and API Analysis: Reverse engineering allows analysts to identify and analyze the functions and APIs (Application Programming Interfaces) used by the malware. By examining function calls and API interactions, analysts can determine the purpose and functionality of specific code segments, as well as identify potential system or library calls used for file manipulation, network communication, or other operations.
- Variable and Data Analysis: Reverse engineering involves analyzing the variables and data structures used by the malware. This includes identifying how the malware stores and manipulates data, such as encryption keys, configuration settings, or user input. Understanding the data structures helps in uncovering the malware's communication protocols, data storage methods, and potential vulnerabilities.
- Patching and Modification: Code reversing enables analysts to modify the code of the malware to analyze its behavior or bypass certain functionality. By patching the code, analysts can remove anti-analysis or anti-debugging techniques, disable harmful behaviors, or redirect the malware's activities to controlled environments for further analysis.
- Vulnerability Analysis: Code reversing can help identify vulnerabilities in the malware itself or in the software it targets. By understanding the code and logic of the malware, analysts can identify potential flaws, such as buffer overflows, injection points, or insecure coding practices. This information can be used to develop patches or mitigations to protect against similar vulnerabilities.
