OSINT-based Email Analyzer for Phishing Detection
Pavanello, Francesco (2023-02-14)
OSINT-based Email Analyzer for Phishing Detection
(14.02.2023)
Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.
avoin
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2023022027862
https://urn.fi/URN:NBN:fi-fe2023022027862
Tiivistelmä
It is more and more common to receive emails asking for credentials. They usually say that there is some kind of issue that must be solved by accessing the involved service using the link inside the message text. These emails are often malicious, thought to steal users' or employees' credentials and gain access to personal or corporate areas.
This scenario is commonly known as phishing, and nowadays it is the most common cause of corporate data breaches. The attacker tries to exploit human vulnerabilities like fear, concern or carelessness to obtain what would be difficult to achieve otherwise.
Even if it is easy from an expert point of view to recognize such attempts, it is not so simple to automatize their detection, due to the fact that there are various techniques to elude systematic checks. Nevertheless, Würth Phoenix wants to improve their cyber defense against any possible threat, and hence they assigned me the task of working on phishing emails detection.
This thesis presents a novel program that can analyze all emails delivered to a specifically set up email server without any filtering on incoming traffic, which is then called a "spam-trap-box." Additionally, it is configured with accounts registered for domains owned by failed companies that used to operate in the same industry of Würth Phoenix customers. This way it is more probable to analyze traffic similar to the one in a real case scenario.
The innovative part of the analysis implemented is the use of Open Source Intelligence (OSINT) to compare the most relevant parts of an email with evidence of other phishing attempts indexed on the web, which are generally known as Indicators of Compromise (IoCs).
After the inspection, if an email is categorized as malicious, new IoCs are created to feed the Würth Phoenix Security Operation Center (SOC), which is the service responsible for the protection against cyber threats offered to their customers. The new indicators include more information than the ones used during the analysis, and the findings are inherent to clients' businesses, thus the SOC has more details to use while analyzing their email traffic.
This scenario is commonly known as phishing, and nowadays it is the most common cause of corporate data breaches. The attacker tries to exploit human vulnerabilities like fear, concern or carelessness to obtain what would be difficult to achieve otherwise.
Even if it is easy from an expert point of view to recognize such attempts, it is not so simple to automatize their detection, due to the fact that there are various techniques to elude systematic checks. Nevertheless, Würth Phoenix wants to improve their cyber defense against any possible threat, and hence they assigned me the task of working on phishing emails detection.
This thesis presents a novel program that can analyze all emails delivered to a specifically set up email server without any filtering on incoming traffic, which is then called a "spam-trap-box." Additionally, it is configured with accounts registered for domains owned by failed companies that used to operate in the same industry of Würth Phoenix customers. This way it is more probable to analyze traffic similar to the one in a real case scenario.
The innovative part of the analysis implemented is the use of Open Source Intelligence (OSINT) to compare the most relevant parts of an email with evidence of other phishing attempts indexed on the web, which are generally known as Indicators of Compromise (IoCs).
After the inspection, if an email is categorized as malicious, new IoCs are created to feed the Würth Phoenix Security Operation Center (SOC), which is the service responsible for the protection against cyber threats offered to their customers. The new indicators include more information than the ones used during the analysis, and the findings are inherent to clients' businesses, thus the SOC has more details to use while analyzing their email traffic.