DC Forensic -
Fact-Based Analysis in Sensitive Situations

• Hash value (SHA-256): A digital checksum that ensures that a file has not been altered after it was backed up.
• Write blocker: Hardware that physically prevents a data carrier from being written to while it is being read.
• Forensic image: A bit-for-bit 1:1 copy of a medium, including deleted data areas.
• Slack space: Hidden storage areas at the end of files where traces of deleted data can often be found.
• Data carving: Search for file signatures in "empty" storage space for recovery without file system information.

• Anti-forensics: Techniques used by perpetrators (shredders, encryption) that we neutralize using specialized tools.
• Timeline analysis: Chronological review of all user activities (when was what copied/deleted?).
• Registry forensics: Reading the Windows registry to document installed hardware, programs, and user history.
• Mobile App Artifacts: In-depth analysis of messaging app databases (WhatsApp/Signal) to reconstruct deleted chats.
• IP Attribution: Mapping digital traces to specific network nodes and physical locations.

• Email Header Analysis: We examine an email’s metadata (headers) to verify the actual sender path, the mail servers involved, and the time of transmission. This allows us to detect spoofing (falsified sender addresses).
• Document Metadata (EXIF/XMP): Every PDF or Word document contains hidden information: Who created it? How long was it worked on? Was the creation date altered afterward? We make this “hidden data” visible.
• OCR Forensics (Text Recognition): Making scanned documents or image files searchable to find specific keywords or sensitive information even within thousands of unsorted image files.

• Heuristic analysis: Search for behavior patterns instead of fixed file signatures. This helps us identify new or unknown manipulation methods.
• Encryption analysis (decryption): We examine the type of encryption used for containers or drives. In many cases, we can use forensic tools and computing power (brute force or dictionary attacks) to access encrypted evidence.
• Cross-drive analysis: Comparing data across multiple devices. We check whether a file was moved from laptop A to USB stick B and ultimately ended up on a private PC.
• Browser forensics: Analysis of histories, cache memories, cookies, and session data. We reconstruct web searches, logins, and even form entries that the user made in the browser.

• Wearable forensics: Analysis of smartwatches or fitness trackers. These devices often store more accurate location and health data (e.g., stress pulse during an incident) than the smartphone itself.
• Geofencing analysis: Verification of whether a device was located in a defined geographical area at a specific time, based on GPS logs and Wi-Fi triangulation.
• Cloud backup extraction: Often, the physical device is destroyed or inaccessible. We extract evidence directly from cloud backups (iCloud, Google Dashboard) to restore the digital state.

Yes. Using audio forensics, we analyze the background frequencies (known as "room noise"). An edit almost always causes a minimal irregularity in the frequency response, which we can prove graphically.

Perpetrators often try to tamper with the system clock to falsify alibis. We compare the local system time with the timestamps of file system events and external server logs (e.g., routers or cloud) to restore the true chronology.

In most cases, yes. Standard formatting only deletes the table of contents, not the data itself. As long as the sectors have not been overwritten multiple times with new data, reconstruction is possible.

Here we examine psychological manipulation. We reconstruct the chain of communication (phishing emails, phone calls) to understand how an employee was tricked into bypassing security measures.