This question aligns with CHFI v11 objectives under Operating System Forensics and File Type and Encoding Analysis . In digital forensics, file signature analysis-also known as magic number analysis -is a critical technique used to identify the true file type regardless of its extension. Attackers often rename or disguise files to evade detection, making hex-level inspection essential during forensic examinations.
Each file format begins with a unique hexadecimal header that identifies its structure. The hex value "89 50
4E 47" corresponds to the ASCII representation of ‰PNG , which is the standard file signature for Portable Network Graphics (PNG) files. CHFI v11 specifically emphasizes the use of hex editors to analyze file headers and detect file extension mismatches during investigations.
The other options have different signatures: PDF files start with 25 50 44 46 (%PDF) , JPEG files typically begin with FF D8 FF , and BMP files start with 42 4D (BM) . Since the observed hex value matches the PNG signature, the correct identification is PNG. This technique is vital for uncovering hidden or obfuscated evidence and ensuring accurate file classification in forensic investigations.

According to the CHFI v11 Forensic Investigation Process and Event Correlation objectives , the forensic technique that enables investigators to reconstruct the sequence of events and determine the root cause of an incident is data analysis . Data analysis is the phase where collected evidence is examined, correlated, and interpreted to extract meaningful insights about attacker behavior.
During data analysis, investigators examine logs, timestamps, file system metadata, registry entries, network traffic, memory artifacts, and security alerts to perform timeline analysis , event correlation , and kill chain reconstruction . CHFI v11 explicitly highlights techniques such as timeline creation, event deconfliction, and correlation analysis as essential for identifying the time of attack , vulnerabilities exploited , methods used , and actions performed by the attacker .
The other options represent different forensic phases but do not directly achieve the stated goal. Data acquisition focuses on collecting evidence in a forensically sound manner, not interpreting it. Data duplication involves creating forensic copies to preserve evidence integrity. Photographing the crime scene applies primarily to physical forensics and documentation, not digital event reconstruction.
CHFI v11 emphasizes that without proper data analysis , raw evidence remains unstructured and cannot support attribution, root cause analysis, or legal prosecution. Therefore, to uncover the complete sequence of malicious activities and generate an accurate incident timeline, Data analysis is the most effective forensic technique.
Hence, the correct and CHFI-verified answer is Option C .

According to theCHFI v11 Operating System and Malware Forensics objectives,Windows Event ID 5156 is generated by theWindows Filtering Platform (WFP)and indicates that a network connection has been permitted. This event is highly valuable in malware investigations because it records detailed information aboutprocess-level network activity, which is a common indicator of compromise.
Event ID 5156 logs typically include:
* Process name and Process ID (PID)that initiated the network connection
* Source and destination IP addresses
* Source and destination ports
* Protocol used (TCP/UDP)
* Direction of the connection (inbound or outbound)
CHFI v11 explicitly highlights the importance ofWindows Security Event Logsin tracing malware behavior, especially for identifyingcommand-and-control (C2) communications, data exfiltration attempts, and lateral movement. By analyzing Event ID 5156, investigators can directly correlate aspecific executable or malicious processwithexternal IP addresses, helping establish attacker infrastructure and timelines.
The other options are incorrect because Event ID 5156 does not record credentials, file deletion paths, or registry modification details. Those artifacts are found in other event IDs or forensic sources such as registry hives, file system metadata, or Sysmon logs.
Therefore, the key forensic value ofEvent ID 5156lies in revealingthe process responsible for the network communication and the IP address it connected to, makingOption Dthe correct and CHFI v11-verified answer.

This question aligns with CHFI v11 objectives underOperating System Forensics, specificallyWindows Registry forensics and binary data analysis. Windows registry hive files (such as SYSTEM, SOFTWARE, SAM, and NTUSER.DAT) are stored inbinary formatand contain valuable forensic artifacts related to user activity, program execution, persistence mechanisms, and system configuration. CHFI v11 emphasizes that forensic investigators must use tools capable oflow-level binary inspectionto accurately analyze these files.
Hex Workshopis a professional hex editor designed for detailed examination, interpretation, and manipulation of binary data. It allows investigators to view registry hive files at the hexadecimal level, search for specific byte patterns, validate offsets, and correlate raw binary structures with known registry data formats. This capability is essential when registry files are corrupted, partially deleted, or need manual verification beyond automated tools.
The other options are unsuitable: Camtasia is a screen recording tool, Rufus is used for creating bootable USB drives, and Dundas BI is a business intelligence and data visualization platform. None provide binary-level forensic analysis functionality. Therefore, consistent with CHFI v11 registry and binary forensic analysis practices,Hex Workshopis the most appropriate tool for examining registry files in this scenario.

Under the CHFI v11 objectives related to theeDiscovery process, investigators must understand and correctly apply variouseDiscovery collection methodologiesbased on where data resides and how it is accessed. In this scenario, the investigator is collecting evidence frominternal servers and shared drivesthat are part of the organization's on-premises infrastructure. These repositories typically store centralized data such as user files, audit logs, access records, and application artifacts.
This approach directly aligns withnetwork collection, an eDiscovery methodology in which data is acquired remotely over the organizational network fromfile servers, database servers, shared storage, and internal repositories. Network collection is commonly used in enterprise investigations because it allows investigators to gather large volumes of data efficiently without physically seizing individual endpoint devices.
Cloud-based collection (Option B) applies only when data is hosted on third-party cloud platforms such as AWS, Azure, or Google Cloud. Email collection (Option C) is limited to mail servers and messaging systems, while mobile device collection (Option D) focuses on smartphones and tablets. None of these accurately describe the centralized, internal infrastructure outlined in the scenario.
The CHFI v11 Exam Blueprint emphasizeseDiscovery collection methodologiesas part of forensic readiness and investigation workflows, highlighting network collection as the appropriate technique for acquiring evidence from organizational servers and shared drives while maintaining integrity and chain of custody