Cisco Cybersecurity Certifications - CyberOps Professional
1 Introduction to CyberOps
1-1 Understanding CyberOps
1-2 Role of a CyberOps Analyst
1-3 CyberOps Professional Certification Overview
2 Cyber Threat Landscape
2-1 Types of Cyber Threats
2-2 Threat Actors and Motives
2-3 Threat Intelligence Sources
3 Network Fundamentals
3-1 OSI and TCPIP Models
3-2 Network Devices and Their Functions
3-3 Network Addressing (IP, MAC)
3-4 Subnetting and VLANs
4 Security Fundamentals
4-1 CIA Triad (Confidentiality, Integrity, Availability)
4-2 Security Policies and Procedures
4-3 Risk Management and Mitigation
5 Network Security Devices
5-1 Firewalls
5-2 Intrusion Detection Systems (IDS)
5-3 Intrusion Prevention Systems (IPS)
5-4 Next-Generation Firewalls (NGFW)
6 Security Information and Event Management (SIEM)
6-1 SIEM Architecture and Components
6-2 Log Management and Analysis
6-3 Correlation Rules and Alerts
6-4 Reporting and Dashboards
7 Incident Response
7-1 Incident Response Process (IRP)
7-2 Preparation and Detection
7-3 Containment, Eradication, and Recovery
7-4 Post-Incident Activity and Lessons Learned
8 Threat Hunting
8-1 Threat Hunting Concepts
8-2 Threat Hunting Techniques
8-3 Tools and Platforms for Threat Hunting
8-4 Case Studies and Real-World Scenarios
9 Malware Analysis
9-1 Types of Malware
9-2 Malware Analysis Techniques
9-3 Tools for Malware Analysis
9-4 Case Studies and Real-World Scenarios
10 Cloud Security
10-1 Cloud Security Concepts
10-2 Cloud Security Models (IaaS, PaaS, SaaS)
10-3 Cloud Security Best Practices
10-4 Cloud Security Tools and Platforms
11 Automation and Orchestration
11-1 Automation Concepts in CyberOps
11-2 Orchestration Tools and Platforms
11-3 Use Cases for Automation and Orchestration
11-4 Security Automation Best Practices
12 CyberOps Professional Capstone Project
12-1 Project Planning and Requirements
12-2 Implementation and Execution
12-3 Testing and Validation
12-4 Documentation and Presentation
9 Malware Analysis Explained

9 Malware Analysis Explained

1. Static Analysis

Static analysis involves examining the characteristics of malware without executing it. This includes examining the file's metadata, code structure, and other static features to identify potential threats.

Example: Think of static analysis as inspecting a car's engine without starting it. By examining the engine's components and structure, you can identify potential issues without running the risk of starting a malfunctioning engine.

2. Dynamic Analysis

Dynamic analysis involves executing the malware in a controlled environment, such as a virtual machine, to observe its behavior. This method helps in understanding how the malware interacts with the system and what actions it performs.

Example: Consider dynamic analysis as test-driving a car. By driving the car, you can observe its performance, handling, and any unusual behaviors that may indicate a problem.

3. Behavioral Analysis

Behavioral analysis focuses on monitoring the actions and activities performed by the malware during execution. This includes tracking network communications, file modifications, and other system interactions to understand the malware's objectives.

Example: Think of behavioral analysis as observing a person's daily routine. By tracking their activities, you can understand their habits and intentions, just as behavioral analysis helps in understanding the malware's intentions.

4. Code Disassembly

Code disassembly involves converting the malware's machine code into assembly language, making it easier to understand the underlying logic and functionality of the malware. This process helps in identifying specific functions and potential vulnerabilities.

Example: Consider code disassembly as translating a foreign language. Just as translating a foreign language helps you understand its meaning, disassembling code helps you understand the malware's logic and functions.

5. Code Decompilation

Code decompilation involves converting the malware's compiled code back into a higher-level language, such as C or C++. This process provides a more readable and understandable representation of the malware's code, aiding in analysis.

Example: Think of code decompilation as transcribing a musical score. Just as transcribing a score helps musicians understand the music, decompiling code helps analysts understand the malware's structure and logic.

6. Network Traffic Analysis

Network traffic analysis involves monitoring the network communications generated by the malware. This includes examining the types of data sent and received, the protocols used, and the destinations involved to identify potential command-and-control (C2) servers or data exfiltration attempts.

Example: Consider network traffic analysis as monitoring a postal service. Just as you can track the flow of mail to identify suspicious packages, network traffic analysis helps in identifying suspicious communications generated by malware.

7. File System Analysis

File system analysis involves examining the changes made to the file system by the malware. This includes identifying new files created, existing files modified, and directories accessed to understand the malware's impact on the system.

Example: Think of file system analysis as inspecting a library's catalog. Just as you can track the addition and modification of books, file system analysis helps in tracking the changes made by malware to the system's files.

8. Memory Analysis

Memory analysis involves examining the contents of the system's memory (RAM) to identify malware that may be running in memory. This method helps in detecting and analyzing advanced persistent threats (APTs) that may not leave traces on the file system.

Example: Consider memory analysis as examining a restaurant's kitchen. Just as you can identify ingredients being used by examining the kitchen, memory analysis helps in identifying malware by examining the system's memory.

9. Indicators of Compromise (IOCs)

Indicators of Compromise (IOCs) are specific pieces of evidence that indicate a security breach or an attempted breach. These can include file hashes, IP addresses, domain names, and other artifacts that can be used to detect and respond to malware.

Example: Think of IOCs as fingerprints at a crime scene. Just as fingerprints can identify a suspect, IOCs can identify the presence of malware and help in tracking its origin and impact.

By understanding these nine key concepts of malware analysis, you can effectively identify, analyze, and mitigate the impact of malware, enhancing your organization's cybersecurity posture.