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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Cloud Forensics | 7% | - Cloud service models and environments - Challenges in cloud forensics - Legal and compliance aspects - Collecting evidence from cloud platforms |
| Topic 2: Network Forensics | 9% | - Investigating network intrusions and attacks - Analyzing network logs and devices - Packet capture and reconstruction - Network protocols and traffic analysis |
| Topic 3: Investigating Web Attacks | 7% | - Common web attack types - Web application architecture - Analyzing web server logs and artifacts - Forensics for web-based evidence |
| Topic 4: Computer Forensics Investigation Process | 8% | - First response and evidence collection - Reporting and presenting findings - Evidence preservation and chain of custody - Investigation planning and documentation |
| Topic 5: Database Forensics | 5% | - Recovering and analyzing database records - Audit logs and transaction analysis - Database systems and structures |
| Topic 6: Data Acquisition and Duplication | 8% | - Acquiring data from damaged or encrypted media - Verifying data integrity and hashing - Hardware and software acquisition tools - Forensic imaging methods |
| Topic 7: Computer Forensics in Today's World | 7% | - Legal and ethical frameworks - Roles and responsibilities of forensic investigators - Overview of computer forensics - Types of cybercrimes and digital evidence |
| Topic 8: Windows Forensics | 10% | - Registry analysis - Recovering deleted files and partitions - File system and artifact analysis - Windows architecture and boot process - Browser and application forensics |
| Topic 9: Linux and Mac Forensics | 8% | - Linux file systems and structure - macOS file systems and artifacts - Log files and user activity analysis - Command-line and forensic tools |
| Topic 10: Defeating Anti-Forensics Techniques | 6% | - Countermeasures and detection techniques - Data hiding and obfuscation - Common anti-forensic methods |
| Topic 11: Dark Web Forensics | 5% | - Dark web structure and technologies - Tools and techniques for dark web forensics - Investigating activities on dark networks |
| Topic 12: Malware Forensics | 8% | - Analyzing malicious code and behavior - Recovering from malware incidents - Types and characteristics of malware - Static and dynamic analysis techniques |
| Topic 13: Investigating Email Crimes | 5% | - Email protocols and structure - Tracking email origins and paths - Investigating phishing and spam - Analyzing email headers and content |
| Topic 14: Understanding Hard Disks and File Systems | 9% | - File systems: FAT, NTFS, EXT, HFS+ - Disk structure and partitioning - File metadata and timestamps - Storage media types and characteristics |
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NEW QUESTION # 221
A forensic analyst has been tasked with investigating unusual network activity inside a retail company's network. Employees complain of not being able to access services, frequent rebooting, and anomalies in log files. The investigator requested log files from the IT administrator and after carefully reviewing them, he finds the following log entry:
What type of attack was performed on the companies' web application?
Answer: A
NEW QUESTION # 222
During a forensic investigation on an iOS device, you are tasked with retrieving geolocation data for various applications and system services. After examining the device, you come across several files. Which of the following files contains the geolocation data of applications and system services on iOS devices?
Answer: B
Explanation:
According to the CHFI v11 Mobile and IoT Forensics objectives, iOS devices maintain geolocation-related artifacts through the location services subsystem (locationd) . One of the key forensic artifacts associated with this subsystem is Clients.plist .
The Clients.plist file stores information about applications and system services that have requested or used location services . It contains identifiers for apps, service names, permission states, and timestamps indicating when location data was accessed. This makes it highly valuable for investigators attempting to determine which apps accessed location data and when , which is crucial in cases involving surveillance, stalking, fraud, or physical movement reconstruction.
The other files listed do not store geolocation data. Cookies.plist contains browser cookie information, Sms.
db stores SMS and iMessage content, and DraftMessage.plist holds unsent message drafts. None of these files are related to GPS or location services.
CHFI v11 emphasizes correlating Clients.plist with other artifacts such as location caches, application logs, and timestamps to reconstruct user movement and application behavior on iOS devices.
Therefore, the file that contains geolocation data of applications and system services on iOS devices-fully aligned with CHFI v11-is Clients.plist , making Option D the correct answer.
NEW QUESTION # 223
Amid a live intrusion at a utility provider in Phoenix, Arizona, responders identify an active backdoor on a control system. System logs show that evidence is in the process of being deleted.
To prevent the loss of critical runtime artifacts, investigators must act immediately. Under which condition may a search proceed without first obtaining a warrant?
Answer: A
Explanation:
A warrantless search may be justified under exigent circumstances when waiting to obtain a warrant would create an immediate risk that critical evidence will be destroyed, altered, or lost.
Here, active deletion of evidence creates the urgent condition needed for immediate action.
NEW QUESTION # 224
Chloe is a forensic examiner who is currently cracking hashed passwords for a crucial mission and hopefully solve the case. She is using a lookup table used for recovering a plain text password from cipher text; it contains word list and brute-force list along with their computed hash values. Chloe Is also using a graphical generator that supports SHA1.
a. What password technique is being used?
b. What tool is Chloe using?
Answer: B
NEW QUESTION # 225
Bob works as information security analyst for a big finance company. One day, the anomaly- based intrusion detection system alerted that a volumetric DDOS targeting the main IP of the main web server was occurring. What kind of attack is it?
Answer: A
NEW QUESTION # 226
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