CHFI 312-49v11 Release Date

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 the CHFI v11 objectives underMobile and IoT Forensics, understanding theiOS architecture stackis essential for both application analysis and forensic investigations. The iOS architecture is divided into four primary layers: Cocoa Touch, Media Services, Core Services, and Core OS. Each layer provides specific frameworks and capabilities.

In this scenario, Alice is working withOpenGL ES,OpenAL, andAV Foundation, which are all core frameworks associated withgraphics rendering, audio processing, and multimedia handling. These technologies reside in theMedia Services Layer, making Option D the correct answer. The Media Services layer is responsible for supporting 2D/3D graphics, audio, video playback, and media capture—critical components for immersive gaming and multimedia applications.

The Cocoa Touch layer (Option A) focuses on user interface elements and application-level interactions. The Core Services layer (Option C) provides foundational services such as data persistence, networking, and location services. The Core OS layer (Option B) operates closest to the hardware, handling memory management, security, and low-level system operations. None of these layers directly provide the multimedia frameworks highlighted in the scenario.

CHFI v11 explicitly includesiOS architecture and boot processas part of mobile forensics, emphasizing the Media Services layer as the source of multimedia frameworks commonly examined during application and malware analysis on iOS devices

This question aligns with CHFI v11 objectives underOperating System ForensicsandLive Data Acquisition. When investigating a compromised Windows system, collecting volatile data such as running processes and active services is critical, as this information exists only in memory and can be lost if the system is shut down. CHFI v11 emphasizes the use ofnative, low-impact system utilitiesduring live forensic response to minimize changes to the system state.

Thetasklistcommand is a built-in Windows utility that displays a list of currently running processes along with associated process IDs (PIDs), memory usage, and service relationships. It is specifically designed for real-time process enumeration and is commonly used in forensic investigations to identify suspicious or malicious processes with minimal system interaction. Because tasklist is native to Windows, it does not introduce external binaries that could alter evidence integrity.

ExifTool is used for metadata analysis, Wireshark captures network traffic rather than process data, and Hexinator is a hex editor used for file-level analysis, not live process enumeration. Therefore, in accordance with CHFI v11 best practices for volatile evidence collection on Windows systems,tasklistis the correct and most forensically sound tool for this scenario.

According to theCHFI v11 Dark Web Forensicsobjectives, governments that enforce strict internet censorship oftenblock access to publicly listed Tor entry (guard) relaysby using IP blacklisting, deep packet inspection (DPI), and traffic fingerprinting. In such environments, connecting directly to the Tor network using standard relay information becomes ineffective.

To overcome this restriction, Tor providesbridge nodes (Tor bridges). Bridges areunlisted Tor entry relayswhose IP addresses arenot published in the public Tor directory, making them significantly harder for censors to detect and block. CHFI v11 explicitly identifiesTor bridgesas a key mechanism for bypassing government surveillance and censorship. Bridges may also usepluggable transports(such as obfs4, meek, or snowflake) that disguise Tor traffic to appear like normal HTTPS or other benign traffic, further evading detection.

The other options are incorrect.Public Tor relay nodesare typically the first targets of censorship and are already blocked.Direct communication with an exit nodeis not possible because Tor circuits must always begin with an entry point.Collaborating with government authoritiescontradicts the goal of bypassing surveillance and is not a technical solution discussed in CHFI v11.

CHFI v11 emphasizes that investigators and analysts must understand Tor infrastructure, including bridges, to properly investigate dark web activity and censorship circumvention techniques. Therefore, the correct and CHFI-aligned method is touse bridge nodes to access the Tor network, makingOption Athe correct answer.