In the past years, there has been increasing awareness by the public and policy makers on the potential harm that social network manipulation can produce. Yet, most researchers have looked at the front end of the problem: developing algorithms to flag fake accounts on social networks and suspend them.
Find Security Bugs can often uncover interesting findings that may lead to the discovery of critical vulnerabilities. Back in May, we published on this blog two vulnerabilities in components of Spring, a Java web framework, using this tool. However, the process of using Find Security Bugs can be a little bit tedious to unseasoned Java users. Also, the process of analyzing compiled code and triaging the findings needed improvements. Here is the solution that was built to find vulnerabilities at scale.
This post will detail the password filter implant project we developed recently. Our password filter is used to exfiltrate Active Directory credentials through DNS. This text will discuss the technicalities of the project as well as my personal experience developing it. It is available under an open source license on GitHub.
In the past year, we developed a data-driven method for identifying, quantifying, and comparing ransom payments in the Bitcoin ecosystem from 35 ransomware families. The study was conducted in partnership with Bernhard Haslhofer from the Austrian Institute of Technology (AIT) and Benoît Dupont from the Université de Montréal (UdeM).
On Tuesday, we released the details of RCE vulnerability affecting Spring Data (CVE-2018-1273). We are now repeating the same exercise for a similar RCE vulnerability in Spring Security OAuth2 (CVE-2018-1260). We are going to present the attack vector, its discovery method and the conditions required for exploitation.