Exploits, Tools & Data Recovery · The Forensic Tool Landscape · Lesson 3 of 5

Testing the Tools

See how NIST tests forensic tools and why examiners must check results.

Proving a tool works

You saw in Mobile Forensics that tool validation means checking that a tool really does what it claims. Here's how that works at a national level, and why it never really finishes.

NIST's Computer Forensics Tool Testing (CFTT) program begins by writing a specification: a plain list of what tools in a category should do. For phones, that means things like copying every supported contact, call record and text message correctly. Testers then load test phones with known content, run the tool and compare what comes out with what went in. The Department of Homeland Security's Science and Technology Directorate partners with NIST to publish the results as public test reports. Categories go beyond phones to disk imaging, write blockers, deleted file recovery, SQLite and cloud data extraction.

Every report names an exact tool and version. NIST's mobile page lists 2025 reports for, among others, Cellebrite Inseyets.UFED and Physical Analyzer, Magnet Axiom and Graykey, MSAB XRY, Oxygen Forensic Detective and Belkasoft X. A report isn't a pass or fail certificate. It describes what worked and lists anomalies, the cases where the tool's output didn't match the known content.

An early report shows why the details matter. A 2009 test of Cellebrite UFED 1.1.0.5 found it handled supported data correctly in all but five test cases. Among the exceptions, unread text messages were changed to read, some outgoing messages stored on the phone weren't reported, and dropped connections during extraction weren't clearly shown to the examiner. A changed read status could matter a great deal if a case turns on whether someone saw a message.

Versions matter just as much. A test of version 10.3 says nothing certain about version 10.4, because updates add parsers and can add bugs. So labs also validate tools themselves, often with their own test phones, whenever they adopt a new tool or a major update.

When tools disagree

Two tools can read the same data and give different answers. Each decodes with its own parsers, and a parser written for last year's version of an app can miss a new field, misread a timestamp or count one record twice.

A well-known example comes from a computer rather than a phone, but the lesson carries over. During Casey Anthony's 2011 murder trial in Florida, prosecutors said a family computer had visited a web page about chloroform 84 times, a figure from a tool called CacheBack. After testifying, the tool's developer, John Bradley, learned that an earlier police report using a different tool, NetAnalysis, had shown one visit. He reworked part of his software and also found one visit. NBC News reported that both tools had failed to fully decode the browser history file, and that Bradley alerted prosecutors, who didn't correct the record. (Anthony was acquitted. The point here is the evidence, not the verdict.)

The lesson is that the tool said so is not a finding. Examiners are responsible for every result in their reports, so good practice includes:

• Verifying key results by hand, for example by opening the underlying database record a tool decoded.
• Cross-checking important findings with a second tool and explaining any difference.
• Knowing the tool's limits, including anomalies listed in test reports.
• Recording details of the software. You saw in Mobile Forensics that reports list each tool with its version number. That lets someone else repeat the work. It also matters later: if a parser bug is discovered, labs can find which past cases relied on the affected release.

Courts care about this. In many countries the other side can challenge how a result was produced, and an examiner who can explain how a finding was checked is far more convincing than one who points at a screen.