Voyager is a software that implements what is called an invisible bit (aka, a tracking bit), that can be used to track certain activities. Voyager deploys the AWS network infrastructure, and its Data Base, the Relational Database Service (RDS). Voyager has been implemented at CI by a group of Computer Science students, as a Research & Development project for the HTTF. From AWS website:
Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups. It frees you to focus on your applications so you can give them the fast performance, high availability, security and compatibility they need.
For this project, we are also using the following tools: EC2, S3 and Route 53.
Anyone working in the field of Digital Forensics is aware that a substantial portion of time is dedicated to reverse engineering passwords. That is, in most cases a digital forensics investigator receives a password-protected handheld device, or a laptop with an encrypted hard disk, or a Microsoft Word document which has been password protected.
It is then the task of the investigator to try to retrieve the evidence, and that in turns requires reverse engineering the password; in some cases this can be achieved by recovering the hash of the password, which is stored somewhere (the locations are often known) on the device’s memory.
In order to obtain the password from the hash, we have to run a brute-force search algorithm that guesses passwords (the guesses can be more or less educated, depending on what is known about the case). Sometimes we get lucky. There are two programs that are used extensively for this purpose: John the Ripper and hashcat.
As we have been studying methods for recovering passwords from hashes, we have been using AWS EC2 instances in order to run experiments and help HTTF with their efforts. Together with senior capstone students as well as graduate students in Cybersecurity, we have been creating a set of guidelines and best practices to help in the recovery of passwords from hashes. AWS EC2 instances are ideal as they can be crafted to the needs and resources of a particular case. For example we are currently running a t2.2xlarge instance on a case where we have to recover the password of a Microsoft Word document; we have also used a p2.16xlarge with GPU-based parallel compute capabilities, but it costs $14/hour of usage, and so we deploy it in a very surgical manner.
On August 7, 2017, the CI Computer Science students presented a prototype of a digital forensic tool, which we named SEAKER (Storage Evaluator and Knowledge Extraction Reader), as part of their Masters COMP 524 Cybersecurity course. This project was a collaboration between the Ventura County District Attorney (VCDA) Digital Forensics Lab and CI Computer Science, under the umbrella of the SoCal High Technology Task Force (HTTF).
The students presented a live demo with devices supplied by the Ventura County DA. The SEAKER prototype was able to compile search results in less than a minute depending on the size of the device. According to VCDA officials at the presentation this is a remarkable increase in efficiency and will be a useful tool in the field: while imaging of a hd can take up to 4 hours, SEAKER performs a triage search in minutes.
Digital Forensics (DF) deals with the recovery and investigation of clues from digital devices (computers, handhelds, iPads, routers, modems, DVRs, etc.). The goal of this effort is to support or refute a hypothesis in court. DF is a complex and technical field: it can be used to attribute evidence to specific suspects, confirm alibis or statements, determine intent, identify sources, or authenticate documents.
A DF investigation commonly consists of 3 stages: acquisition or imaging of exhibits, analysis and reporting. The SEAKER tool helps with the acquisition of data from digital devices in a way that prevents tampering.
The SEAKER project was a fantastic learning experience for our students, as its design and prototyping combined many different skills: The C programming language, BASH shell scripting, the Linux Operating Systems and command line, the Raspberry Pi hardware, Gliffy diagrams, Dropbox Paper (which we used as a Wiki); Slack collaborative discussion / brainstorming tool, the GitHub software repository which was used as a collaborative tool in the design of the software that animated the Raspberry Pi, WordPress blogging, AWS S3 which served as a repository of the final product, Grep (regular expressions and pattern matching), working with different file systems, and of course strict performance (speed, read only). All of this had to be combined by a group of 18 students, with different backgrounds and skill sets to produce something that could be used by DF examiners.
One of the CI pillars is Community Engagement and Service Learning. This approach identifies needs in the community, and builds a curriculum around research and development to address those needs. The SEAKER project is a great example of such a symbiotic relation between CI and the community. Also, it is an example of the strength of a pedagogical approach that combines both theory and practice. Without theory a field becomes a collection of ad hoc procedures. But without practice theory becomes an abstract exercise in intellectual virtuosity. We plan to build on the approach that combines the Service Learning and Theory & Practice paradigms as we go forward with our Computer Science program in Security Systems Engineering and our Masters level offering in Cybersecurity.
“Storage Evaluator And Knowledge Extraction Reader”
On Monday August 7, at 6pm, in DEL NORTE 1530, the COMP 524 (Cybersecurity) students will present their final project, a technical solution for the SoCal High Technology Task Force in Ventura. This project implements a digital forensic tool with strict performance requirements.
We used GitHub as the software repository, Dropbox Paper for the documentation Wiki, and AWS S3 for distribution of the production version of the software.
You are cordially invited to attend; the presentation will take about two hours, and there will be snacks (Short link to this post: https://wp.me/p7D4ee-FJ).