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

According to the CHFI v11 objectives underMalware ForensicsandStatic Malware Analysis, the correct initial step when analyzing a suspicious document—such as a potentially malicious PDF—is to performstatic analysis before any execution. Running the toolPDFiDusing the command python pdfid.py infected.pdf is a standard and CHFI-aligned first action. PDFiD is designed to quickly scan a PDF file and identify suspicious elements such as /JavaScript, /OpenAction, /Launch, /EmbeddedFile, and /AA, which are commonly abused by attackers to deliver malware through PDF documents.

This approach is non-intrusive and ensures the investigator does not accidentally trigger malicious code, thereby preserving evidence integrity and maintaining forensic soundness. Opening the file in a virtual machine (Option B) constitutesdynamic analysis, which should only be performed after initial static indicators suggest malicious intent and after proper containment controls are in place. Metadata extraction (Option C) is useful but limited, as metadata alone does not reliably expose embedded exploit code. Manual hex inspection (Option D) is advanced and time-consuming and is not recommended as the first step.

The CHFI v11 Exam Blueprint emphasizes astructured malware analysis workflow, starting with static analysis tools like PDFiD for suspicious documents, making Option A the most appropriate and exam-accurate answer

Under theCHFI v11 Mobile and IoT Forensicsdomain, investigators are required to extract and analyzeapplication-level artifactsfrom mobile devices to reconstruct user activity. Web browsers such asGoogle Chromestore valuable forensic data on Android devices, includingbrowsing history, cookies, cached files, saved form data, session tokens, and timestamps, which can be critical in cybercrime investigations.

Magnet AXIOMis a comprehensive digital forensics platform explicitly supported and referenced in CHFI v11 formobile device forensic analysis. It is capable of performinglogical and file system extractionsfrom Android devices and includes built-in parsers forChrome artifacts. Magnet AXIOM can automatically locate Chrome databases (such as History, Cookies, and cache directories), decode SQLite databases, and present the extracted data in a forensically structured and timeline-based view. This makes it highly effective for correlating browser activity with other evidence.

The other tools listed are not suitable for this task.LOICis a network stress-testing/DoS tool,Orbot Proxyis used to route traffic through the Tor network, andDroidSheepis a network sniffing tool for session hijacking. None of these tools are designed for forensic extraction or analysis of browser artifacts from Android devices.

Therefore, in alignment withCHFI v11 Mobile and IoT Forensics objectives, the correct and most suitable tool for extracting Chrome artifacts from an Android device isMagnet AXIOM, makingOption Dthe correct answer.

According to theCHFI v11 Regulations, Policies, and Ethicsdomain,privacy issues most commonly arise during the forensic analysis phaseof a cybercrime investigation. While search warrants legally authorize investigators to collect and examine specific digital evidence, they are typicallyscope-limitedto the suspect, systems, data types, and timeframes defined in the warrant.

Duringforensic analysis, investigators may inadvertently encounterpersonal or sensitive information belonging to third parties, such as usernames, email addresses, chat records, credentials, or identifiers of other users connected to the system. CHFI v11 explicitly highlights this phase as legally and ethically sensitive because analysts must ensure thatnon-relevant data and third-party information are handled carefullyto avoid violations of privacy laws and data protection regulations.

Implementing network security measures is a preventive activity, not an investigative one. Obtaining search warrants is a legal safeguard designed to protect privacy, not create privacy concerns. Preserving anonymity is a mitigation action, not the step that introduces the risk.

CHFI v11 stresses the importance ofminimization, access control, proper documentation, and legal oversightduring forensic analysis to prevent misuse or overexposure of unrelated personal data. Failure to manage privacy during this phase can result in legal challenges, evidence exclusion, or regulatory violations.

Therefore, the step that raisesprivacy-related concernsin this scenario isconducting forensic analysis, makingOption Bthe correct and CHFI v11–verified answer.

This question aligns with CHFI v11 objectives underNetwork and Web Attacks, specificallycommand injection techniques and shell command chaining behavior. In command injection scenarios, attackers (or penetration testers) often chain multiple commands to extend the impact of an injection flaw. Understanding how command separators and logical operators behave in operating systems such as Linux and Windows is critical for both exploitation and forensic analysis.

The logical AND operator&&ensures that the second command is executedonly if the first command completes successfully(i.e., returns an exit status of zero). This behavior is particularly useful in controlled exploitation, where an attacker wants to ensure prerequisite conditions are met before executing follow-up commands. CHFI v11 highlights this operator as a common technique used in command injection attacks to maintain execution flow control.

In contrast, the logical OR operator || executes the second command only if the first fails, the pipe operator | passes the output of one command as input to another regardless of success, and separators such as ; or $() execute commands unconditionally. Therefore, to guarantee conditional execution based on success,&&is the correct and CHFI-aligned choice.

This question aligns with CHFI v11 objectives underCloud Forensics, particularly focusing on evidence acquisition and analysis in cloud environments such as Google Cloud Platform (GCP). Unlike traditional on-premises systems, cloud infrastructures rely heavily onlogs and metadataas primary sources of forensic evidence because investigators often do not have direct access to physical hardware.

CHFI v11 emphasizes that cloud service logs—such as audit logs, access logs, activity logs, and resource metadata—are crucial for reconstructing events in a cloud-based incident. In GCP, these logs record detailed information aboutuser actions, API calls, authentication attempts, resource creation or deletion, privilege changes, and interactions with cloud services. This enables investigators to trace malicious activity, identify compromised accounts, establish timelines, and attribute actions to specific users or service accounts.

While logs may incidentally include IP addresses or device-related hints, their primary forensic value lies in trackingwhat actions were performed, when they occurred, and by whom. Encryption mechanisms are predefined by the cloud provider and are not inferred from logs during investigations. Therefore, consistent with CHFI v11 cloud forensics methodology, logs and metadata are essential for tracking user actions and interactions within the GCP environment, making option D the correct answer.