Based on the interconnection of currently about 45.000 Autonomous Systems (ASs) the Internet and its routing system in particular is highly fragile. To exchange inter-AS routing information, the Border Gateway Protocol (BGP) is used since the very beginning, and will be used for the next years, even with IPv6. BGP has many weaknesses by design, of which the implicit trust of ASs to each other AS is the most threatening one. Although this has been topic on network security research for more than a decade, the problem still persists with no solution in sight. This paper contributes a solution to stay up to date concerning inter-AS routing anomalies based on a broad evidence collected from different publicly available sources. Such an overview is necessary to question and to rely on the Internet as a basis in general and must be a part of every cyber defense strategy. Existing methods of detecting inter-AS routing anomalies result in large sets of real time routing anomalies, based on the evaluation of routing announcements collected from different viewpoints. To decide, whether a detected anomaly is harmful or not, each of them has to be classified and correlated to others. We combine various detection methods and improve them with additional publicly available information. The improved outcome of the implemented routing anomaly detection system is used as input for our classification algorithms
Use-after-free is a type of vulnerability commonly present in software written in memory-unsafe languages like C or C++, where a program frees a memory buffer too early. By placing counterfeit structures at the freed memory location, an attacker can leak information or gain execution control upon subsequent access.In this paper, we show that the concept of use-after-free can be generalized to any environment and situation where resources can be silently exchanged. As an instance of our generalization we demonstrate Use-After-FreeMail attacks. Use-After-FreeMail attacks gather email addresses from publicly available database leaks. The fully automated quantitative analysis brought to light that 33.5% of all free-mail addresses we tested are not valid anymore. In two user studies with 100 and 31 participants we found that 11-19% of users are affected by our attack. In qualitative case studies we investigated what information can be gained in Use-After-FreeMail attacks, e.g., payment information, and how far currently used accounts can be compromised (identity theft). Finally, drawing the connection between mitigations against traditional use-afterfree scenarios and the Use-After-FreeMail scenario, we provide a concise list of recommendations to free-mail providers and users as a protection against use-after-free attacks.
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