312-49v11 Exam Dumps - Computer Hacking Forensic Investigator (CHFIv11)

As defined in theCHFI v11 Procedures and Methodologydomain,directed collectionis an eDiscovery methodology in which investigators deliberately limit evidence collection tospecific data sets, file types, directories, custodians, or system areasthat are known or highly likely to contain relevant information. This approach is commonly used to reduce data volume, minimize business disruption, and lower legal and operational costs while maintaining forensic relevance.

In the given scenario, the investigator intentionally restricts the scope of ESI by targetingspecific directories and file types, rather than collecting full disk images or all user data. CHFI v11 explicitly describes this asdirected (or targeted) collection, which is aligned with theElectronic Discovery Reference Model (EDRM)best practices. Directed collection helps investigators remain compliant with legal proportionality requirements and reduces exposure to irrelevant or private third-party data.

The other options do not match the scenario.Custodian self-collectionintroduces risk and is generally discouraged due to evidence integrity concerns.Incremental collectionfocuses on changes since a prior collection, not selective scope reduction.Remote acquisitionrefers to the method of access, not the collection strategy itself.

CHFI v11 emphasizes directed collection as a preferred methodology when investigators already understandwhere relevant evidence residesand need to collect it efficiently and defensibly. Therefore, the correct and CHFI v11–verified answer isdirected collection of definite data sets and system areas, makingOption Dcorrect.

According to the CHFI v11 objectives underDigital Forensics ReviewandAnti-Forensics Techniques, attackers frequently usefile extension manipulationas an anti-forensic technique to conceal malicious executables by renaming them with harmless-looking extensions such as .txt, .jpg, or .pdf. This tactic relies on the assumption that investigators or users will trust the file extension rather than verifying the file’s true structure.

Autopsy, which is built onThe Sleuth Kit (TSK), provides a dedicated capability todetect file extension mismatchesby analyzing file headers (magic numbers) and comparing them against the file’s extension. If a file’s internal signature does not match its extension, Autopsy flags it as suspicious, allowing investigators to identify hidden executables and recover their true file types. CHFI v11 explicitly highlights“Detecting File Extension Mismatch using Autopsy”as a key forensic technique for defeating anti-forensics.

OSForensics is primarily used for detecting data hiding techniques such as alternate data streams and overwritten metadata, whileTimestompis itself an anti-forensic tool used to manipulate timestamps.StegoHuntfocuses on steganography detection rather than file type validation.

The CHFI Exam Blueprint v4 emphasizes the importance offile type analysis and extension mismatch detectionwhen investigating disguised malware, makingAutopsythe most appropriate and exam-aligned tool in this scenario

According to CHFI v11 objectives underComputer Forensics FundamentalsandDigital Forensics using Python, investigators are encouraged to automate forensic analysis tasks to improve efficiency, accuracy, and repeatability. The Sleuth Kit (TSK) is a widely used open-source forensic toolkit for analyzing disk images, file systems, and recovering deleted files. To extend these capabilities using Python, CHFI v11 highlights the use of Python bindings specifically designed for forensic purposes.

PyTSK (also known as pytsk3) is the official Python binding for The Sleuth Kit. It allows forensic investigators to programmatically access disk images, partitions, file systems, directories, and file metadata directly from Python scripts. This enables automation of tasks such as file enumeration, timeline creation, deleted file recovery, and artifact extraction—core activities in disk and file system forensics.

The other options are not suitable in this context. NumPy is designed for numerical computation, PyTorch is used for machine learning, and PySpark is intended for big data processing. None of these tools integrate with Sleuth Kit or provide native disk forensic analysis capabilities. Therefore, PyTSK is the correct and CHFI-aligned choice for Python-based Sleuth Kit forensic automation.

According to theCHFI v11 Malware Forensics and Malware Analysis objectives, dynamic malware analysis must be performed in acontrolled, isolated, and well-monitored environmentto both observe malicious behavior and prevent unintended spread to production systems. A key requirement of such an environment is the ability tomonitor and record all system-level changesmade by the malware during execution.

Host Integrity Monitoring (HIM)plays a critical role in dynamic malware analysis by tracking modifications tofiles, registry keys, services, processes, startup locations, system calls, and configuration settings. CHFI v11 emphasizes system behavior analysis as a core component of malware forensics, including monitoring registry artifacts, file system changes, persistence mechanisms, and process activity. HIM enables investigators to safely analyze malware impact while maintaining forensic visibility and containment.

The other options are not aligned with CHFI v11 best practices.Disabling antivirus softwareweakens security controls but does not ensure containment or safety.Running malware on physical machinesincreases the risk of permanent damage and network propagation, which contradicts CHFI guidelines favoring sandboxed or virtualized environments.Using outdated operating systemsdoes not contribute to safety and may introduce irrelevant vulnerabilities.

CHFI v11 strongly advocatescontrolled malware analysis labswith monitoring mechanisms that capture behavioral indicators without exposing production assets. Therefore, implementinghost integrity monitoringis a key design aspect that supports bothsafe containment and effective behavioral analysis, makingOption Athe correct and CHFI-verified answer.

According to theCHFI v11 Computer Forensics Fundamentals and Investigation Process, one of the most critical steps in forming a specialized cybercrime investigation team isclearly assigning roles and responsibilities to team members. This step ensures that every aspect of the investigation is handled efficiently, lawfully, and without overlap or conflict.

CHFI v11 emphasizes that cybercrime investigations are multidisciplinary by nature and requirerole-based coordination. Typical roles include first responders, incident responders, forensic examiners, evidence handlers, photographers, documentation specialists, and legal advisors. Clearly defining these roles at the outset ensuresproper evidence handling, adherence to legal procedures, and effective incident response. It also supports maintaining thechain of custody, minimizing contamination of evidence, and ensuring accountability throughout the investigation lifecycle.

Whilelegal adviceandexternal supportare important, they are supplementary functions that support the investigation after the core team structure is established.Conducting digital forensics analysisis an operational activity that occurs later in the forensic process, not during team formation.

CHFI v11 explicitly highlightsbuilding the investigation teamandassigning responsibilitiesas foundational steps before evidence collection and analysis begin. Without clearly defined roles, investigations risk procedural errors, legal challenges, and inefficiencies.

Therefore, the most crucial step in forming a specialized cybercrime investigation team—fully aligned with CHFI v11 objectives—isassigning roles to team members, makingOption Dthe correct answer.

According to the CHFI v11 objectives underMalware ForensicsandStatic and Dynamic Malware Analysis, Microsoft Office documents are one of the most common delivery mechanisms for malware, especially throughmalicious macros, embedded scripts, and exploit-laden objects. Attackers frequently weaponize Word, Excel, and PowerPoint files to execute malicious code when a user opens the document or enables macros.

Theprimary forensic purposeof analyzing suspicious Microsoft Office documents is toidentify embedded malware or malicious codeand understand how it executes. Investigators examine macro code (VBA), embedded objects, OLE streams, and document metadata to detect indicators such as obfuscated scripts, PowerShell execution commands, shellcode loaders, or downloader functionality. CHFI v11 emphasizes that this analysis helps determine theinfection chain, execution triggers, and potential impact on the compromised system.

Options A, B, and D are not valid forensic goals in this context. Identifying the document author (Option A) may be supplementary but does not address the core threat. Formatting optimization (Option B) and performance improvement (Option D) are unrelated to forensic or security investigations.

The CHFI Exam Blueprint v4 explicitly includesanalyzing suspicious Word, Excel, and PDF documentsas part of malware investigations, highlighting the need to detect hidden malicious logic and prevent further compromise. Therefore, identifying embedded malware or malicious code is the correct and exam-aligned objective

According to theCHFI v11 Computer Forensics Fundamentalsmodule, one of thecore responsibilities of a forensic investigatoris to ensure theproper handling, preservation, and integrity of digital evidence. This responsibility is foundational to the entire forensic process and directly impacts theadmissibility of evidence in court.

In the given scenario, the investigator creates aforensic imageof the suspect’s hard drive rather than working directly on the original media. CHFI v11 explicitly states that investigators must always perform analysis on abit-by-bit forensic copywhile preserving the original evidence in a secure, controlled environment. This practice prevents accidental modification, contamination, or destruction of original data and ensures compliance with thebest evidence ruleandchain of custody requirements.

The act of securely storing the original drive and working only on the forensic image demonstrates strict adherence to evidence preservation principles. While recovering deleted files is an investigative goal, the scenario emphasizesmaintaining integrity and preventing alteration, which aligns directly with evidence handling and preservation—not reporting, stakeholder engagement, or device reconstruction.

CHFI v11 consistently reinforces that failure to preserve evidence properly can lead tolegal challenges, evidence exclusion, or case dismissal, regardless of the quality of the technical analysis performed.

Therefore, the responsibility being fulfilled in this scenario—fully aligned with CHFI v11—isensuring appropriate handling and preservation of evidence, makingOption Athe correct answer.

According to theCHFI v11 Computer Forensics FundamentalsandEvidence Handling and Sanitizationguidelines,media sanitizationis a critical process used to ensure that deleted or sensitive data cannot be recovered using forensic techniques. Different international standards define specific overwrite patterns and the number of passes required to securely sanitize storage media.

The procedure described—six overwrite passes alternating between 0x00 and 0xFF, followed by a final overwrite with 0xAA—exactly matches theVSITR (Verschlusssache IT Richtlinien)standard. VSITR is a German government–approved data sanitization method that mandates7 overwrite passes:

Passes 1–6: Alternating 0x00 and 0xFF

Pass 7: Final overwrite with the pattern 0xAA

CHFI v11 explicitly references VSITR as ahigh-assurance sanitization standard, suitable for environments handling classified or highly sensitive information. This method is more rigorous than commonly used standards such asDoD 5220.22-M, which typically uses 3 passes (or a legacy 7-pass variant with different patterns).NAVSO P-5239-26 (MFM)uses different overwrite schemes, andGOST P50739-95generally involves fewer passes.

From a forensic and legal standpoint, following a recognized sanitization standard like VSITR demonstratesdue diligence, compliance, and defensibility, especially when preventing data leakage after incidents.

Therefore, based on the overwrite pattern and number of passes described, the media sanitization standard followed by Sarah isVSITR, makingOption Cthe correct and CHFI v11–verified answer.