The Magnet job: Magnet Forensics mobile solutions
With the prominence of mobile devices and the range of data they continually collect, it’s inevitable that when a crime is committed, mobile data will be a critical source of evidence.
Content Industry: Federal Agencies
Rethinking digital forensics in incident response
The term DFIR has become really popular over the last several years and is used as an all-encompassing term for digital forensics and incident response.
Rotten to the core: investigating iOS stalkerware
Too many victims are dismissed and too many rotten apples are not properly investigated. Don’t be a bad seed. Listen in as Chris Atha explains how to investigate and detect iOS stalkerware.
Six pillars of digital forensics
When it comes to a crime, there are six vital pillars of digital information that should be collected. In this presentation, we will cover real life cases where each of these items was critical to solving this case. These “pillars” will be covered in order of importance, and we will discuss why each item is relevant to the overall case.
Magnet Witness: Evolución de la adquisición de video y del análisis
Dado que más del 80 % de los casos penales dependen de las pruebas de video, desde la vigilancia por DVR hasta las cámaras corporales y las fuentes en la nube, es esencial contar con una solución eficaz y fiable para adquirir y revisar el video.
Magnet Witness: evolving video acquisition and analysis
With over 80% of criminal cases depending on video evidence—from DVR surveillance to body cams and cloud sources—having an efficient, dependable solution to acquire and review video is essential.
Mobile Unpacked S3:E2 // Äpfel, zwiebeln und oger: der umgang mit geschichteten iOS-datenstrukturen
Im Dreamworks-Film “Shrek” sagte die Titelfigur: “Oger sind wie Zwiebeln. Sie haben Schichten.” Nun, Apple unterscheidet sich nicht so sehr von dem grünen Helden, denn ihr liebenswertes Monster, iOS, weist ebenfalls eigene Schichten von Datenstrukturen im gesamten Dateisystem auf. Diese Folge von Mobile Unpacked wird sich damit befassen, wie man diese Strukturen identifiziert und wie man die verschiedenen Schichten Stück für Stück freilegt, um die wichtigen Artefakt-Daten zu finden, die in unterschiedlichen Dateitypen wie SEGB, Plist-Dateien und SQLite-Datenbanken verborgen sind.
Mobile Unpacked S3:E2 // apples, onions, and ogres: dealing with layered iOS data structures
In the Dreamworks film Shrek, the titular character said that “Ogres are like onions. They have layers.” Well, Apple isn’t so different from the green hero in that their lovable monster, iOS also features its own layers of data structures all over the file system. This episode of Mobile Unpacked will cover identifying these structures and how to peel back the different layers to find the key artifact data hidden across different file types such as SEGB, Plist files, and SQLite Databases.
New methods for AI media classification
Several AI solutions for media classification detect content such as CSAM or generic objects, many of which may not align with the specific needs of law enforcement investigations.
Obtención de datos latentes mediante el uso de Magnet Axiom
n Guatemala, como en otros países existe la problemática del robo de datos de tarjetas de crédito o débito, mediante la alteración de cajeros automáticos