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| Section | Weight | Objectives |
|---|---|---|
| Module 1: Computer Forensics in Today's World | 5% | - Forensic Readiness and Professional Conduct - Fundamentals of Computer Forensics - Cybercrimes and Legalities |
| Module 7: Network Forensics | 10% | - Network Traffic Analysis - Network Forensics Fundamentals - Incident Detection and Response - Log Analysis |
| Module 8: Investigating Web-Based Attacks | 5% | - Web Application Forensics - Browser Forensics - Tracking Web Attacks |
| Module 5: Defeating Anti-Forensic Techniques | 10% | - Artifact Wiping and Countermeasures - Data Deletion and Encryption - Steganography Detection - Anti-Forensics Overview |
| Module 3: Understanding Hard Disks and File Systems | 15% | - File System Analysis - Hard Disk Drive Basics - Disk Partitions and Boot Process - File Systems (FAT, NTFS, ext2/3/4) |
| Module 9: Database Forensics | 5% | - Database Forensics Process - Database Fundamentals - Log Analysis and Recovery |
| Module 4: Data Acquisition and Duplication | 15% | - Acquisition Methods and Tools - Validation and Verification - Acquisition Best Practices - Data Acquisition Fundamentals |
| Module 6: Operating System Forensics | 15% | - Linux Forensics - Windows Forensics - System Artifacts Analysis - Mac OS Forensics |
| Module 10: Cloud Forensics | 5% | - Cloud Computing Fundamentals - Cloud Evidence Collection - Cloud Forensics Challenges |
| Module 11: Malware Forensics | 5% | - Malware Detection and Removal - Static and Dynamic Analysis - Malware Analysis Fundamentals |
| Module 2: Computer Forensics Investigation Process | 10% | - Post-Investigation Process - Investigation Process Overview - Investigation Phase - Pre-Investigation Phase |
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NEW QUESTION # 39
An organization decided to strengthen the security of its network by studying and analyzing the behavior of attackers. For this purpose, Steven, a security analyst, was instructed to deploy a device to bait attackers.
Steven selected a solution that appears to contain very useful information to lure attackers and find their locations and techniques.
Identify the type of device deployed by Steven in the above scenario.
Answer: C
Explanation:
Ahoneypotis a deliberately deployed decoy system or service designed toattract attackersby appearing valuable or vulnerable, thereby enabling defenders to observe malicious behavior in a controlled manner.
Digital forensics and incident response references describe honeypots as tools forthreat intelligence and evidence collection, because they can record interaction details such as connection sources, exploited services, commands executed, malware dropped, and attempted privilege escalation. This directly matches the scenario: Steven deployed something that "appears to contain very useful information" tolure attackersand help identify theirlocations and techniques. Honeypots are typically instrumented with extensive logging and monitoring, making them especially useful for building timelines, extracting indicators of compromise, and understanding adversary tactics, techniques, and procedures.
The other options do not align with the "bait attackers" goal. AnIDSprimarily detects and alerts on suspicious activity but is not intended to impersonate a valuable target. Afirewallenforces access control rules to block
/allow traffic, not entice attackers. Arouterforwards packets and provides network connectivity; it is not a deception platform. Therefore, the device type described is aHoneypot (C).
NEW QUESTION # 40
James, a forensic specialist, was appointed to investigate an incident in an organization. As part of the investigation, James is attempting to identify whether any external storage devices are connected to the internal systems. For this purpose, he employed a utility to capture the list of all devices connected to the local machine and removed suspicious devices.
Identify the tool employed by James in the above scenario.
Answer: D
NEW QUESTION # 41
Bob, a forensic specialist at a newly established NGO, discovered a security loophole in the NGO's web application, which unintentionally reveals early enrolled NGO members' biodata to attackers. Bob immediately employed a content filtering mechanism to protect all the NGO's data sources and prevent further damage.
Identify the web application threat identified by Bob in the above scenario.
Answer: A
Explanation:
The scenario describes a web application thatunintentionally reveals sensitive member biodatato attackers.
This is a classic case ofinformation leakage, where confidential or private data becomes exposed due to poor access control, improper output handling, verbose error messages, misconfigured endpoints, insecure direct object references, or unintended exposure through pages, APIs, backups, or logs. In forensic and web security documentation, information leakage is defined by theunauthorized disclosure of data, even if the attacker does not alter the system. The key indicator here is that the application is "revealing" biodata-meaning confidentiality is breached.
Bob's response-using acontent filtering mechanism-also aligns with mitigating data exposure. Content filtering can prevent sensitive fields from being returned, mask personally identifiable information, restrict responses based on user role, and sanitize outputs before they leave the server.
The other options do not match the described impact.Buffer overflowis a low-level memory corruption vulnerability, typically associated with native code execution rather than accidental biodata exposure.
Authentication hijackinginvolves taking over sessions/credentials, andcookie poisoninginvolves manipulating cookie values to gain privileges or alter behavior-neither is explicitly indicated. Therefore, the identified threat isInformation leakage (B).
NEW QUESTION # 42
Given below are different steps involved in event correlation.
Event masking
Event aggregation
Root cause analysis
Event filtering
Identify the correct sequence of steps involved in event correlation.
Answer: C
Explanation:
In event correlation (as applied in SOC/SIEM-driven investigations), the workflow typically starts byreducing complexityandnormalizing what "one incident" looks likebefore attempting conclusions about causality.Event aggregation (2)is performed early to combine multiple low-level, related events (for example repeated authentication failures, repeated firewall denies, or multiple IDS hits for the same signature) into higher-level
"grouped" records. This prevents analysts from treating every raw log line as a separate incident and makes correlation computationally and operationally feasible.
Next,event masking (1)suppresses events that are already known to be irrelevant or repetitive in a way that does not add investigative value (for example, routine scheduled scans, approved admin tools, or duplicate alerts already represented in the aggregated set). After masking,event filtering (4)further removes remaining noise using rules, thresholds, whitelists, time windows, or relevance criteria (scope, asset criticality, and known-benign sources), leaving a cleaner dataset that represents probable security-relevant activity.
Only after the dataset is consolidated and noise-reduced doesroot cause analysis (3)become reliable, because RCA depends on a clear chain of correlated events to identify the initiating action and propagation path.
Hence the correct sequence is2 # 1 # 4 # 3 (Option B).
NEW QUESTION # 43
Which of the following MAC forensic data components saves file information and related events using a token with a binary structure?
Answer: A
Explanation:
On macOS, theBasic Security Module (BSM)provides the system'saudit framework, which records security- relevant activity such asfile access, process execution, authentication events, privilege changes, and other system calls. A key forensic characteristic of BSM auditing is that events are written asbinary audit records composed of "tokens."Each token represents a structured piece of the event (for example: subject/user identity, process ID, command arguments, path, return value, timestamps), and tokens are assembled into complete audit records. Because these audit logs arebinary and tokenized, they are compact, consistent, and designed for reliable parsing and evidentiary reconstruction-important when building timelines of file- related actions and attributing them to specific users and processes.
The other options do not match the "binary token" description.Command-line inputsmay be stored in shell history files but are plain text and not tokenized binary audit records.User accountartifacts (e.g., directory services, plist files) describe identities and settings, not tokenized event logs.Kexts(kernel extensions) are drivers/modules; while they can affect system behavior, they are not the macOS component that stores file
/event records in a binary token format. Therefore, the correct answer isBasic Security Module (C).
NEW QUESTION # 44
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