Bitcoin does have legitimate purposes however, it will always be associated with nefarious deeds. There are many reasons that an examiner might be required to examine Bitcoin forensic artifacts. Preston Miller, in Digital Forensics, 2016 Forensic relevance
If you’re an experienced coder but have never used Python before, it can be picked up very quickly. Python is “a hacker’s” language that supports a massive amount of libraries and a large contributor base. In this book we will be using Bash to collect forensic artifacts and then build scripts using Python to analyze them. If you’re comfortable as a developer you’re encouraged to use any language you will be most effective with.
#DIGITAL ARTIFACT MEANING CODE#
One of the great benefits of a scripting language is that the code does not need to be compiled and can be managed very easily. I myself recommend you pick from three different languages, all of which are considered scripting languages. If you’re working with a team, pick a language that everyone agrees on and can contribute with. Although this book will use bash scripting to collect artifacts, it’s important to pick a language you’re most comfortable with. OS X systems come preinstalled with a number of languages to pick from when developing scripts to collect artifacts. Jaron Bradley, in OS X Incident Response, 2016 Picking a language It is up to the forensic examiner to ask just as much as it is the responsibility of the case agent (or client) to inform the forensic examiner of important information. In most cases, knowing the details of an investigation will enable the forensic analyst to target specific data, in specific areas, that may resolve the case or lead to investigative leads that will satisfy case goals. Investigations, whether criminal or civil in nature, where the forensic examiner is purposely not made aware of intimate case details will only result in a massive amount of time spent needlessly hoping to find evidence that miraculously jumps out during an exam. Being made aware of the case details and needs of the investigator will prevent frustration for everyone involved in the case. Already, analyzing terabytes of data is akin to searching for a needle in a haystack of needles. The forensic examiner needs to know the objectives and goals of the investigation. If your job is solely digital forensics, where you have no interaction with victims or suspects, you need to have constant communication with the case agent. Knowing that every suspect is different from the next, that there are many ways to commit the same crime, and that the technology used is dependent upon the choices of the suspect, take a breath and think before going fishing in an ocean of electronic data.
Motives are different from each other suspect, as is each suspect’s technology skill level. Even within the same case, the storage media being analyzed will be different, requiring different skill sets and tools. Forensic artifacts in one case may not be exist in another. In the next section we will explore a concept that is not as well known as that of the IOC, yet still provides a tremendous amount of value to those seeking to understand more about their host and network environments while attempting to forecast and predict threat activity.īrett Shavers, in Placing the Suspect Behind the Keyboard, 2013 This case is different from that caseĮvery investigation is unique because people are unique. Not to mention the fact that, at least in the eyes of certain organizations and industry subject matter experts, IOCs are merely attributes of IOAs. This is important due to the fact that there remains some degree of debate as to what an IOC is (exactly) within the information security industry, how they are used, and to what degree. If we are to assume that our definition of IOCs is true and accurate and that IOCs apply to machine-oriented platforms such as firewalls, IDSs, IPSs, ETDR platforms, and advanced threat detection (ATD) products among other platforms, as well as to information security and cyber threat intelligence analysts respectively, then we must dismiss lists such as these in relation to IOCs and relegate them to behaviors associated with IOAs and TTP.
Suspicious registry or system file changes Large number of requests for the same file In their list they include observable behaviors such as: However, the list provided by Dark Reading is actually better aligned with the definition we saw above for IOAs or TTPs.
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