One of the major disturbances for network providers in recent years have been Distributed Reflective Denial-of-Service (DRDoS) attacks. In such an attack, the attacker spoofs the IP address of a victim and sent a flood of tiny packets to vulnerable services which then respond with much larger replies to the victim. Led by the idea that the attacker cannot fabricate the number of hops between the amplifier and the victim, Hop Count Filtering (HCF) mechanisms that analyze the Time to Live of incoming packets have been proposed as a solution. In this paper, we evaluate the feasibility of using Hop Count Filtering to mitigate DRDoS attacks. To that end, we detail how a server can use active probing to learn TTLs of alleged packet senders. Based on data sets of benign and spoofed NTP requests, we find that a TTL-based defense could block over 75% of spoofed traffic, while allowing 85% of benign traffic to pass. To achieve this performance, however, such an approach must allow for a tolerance of +/-2 hops. Motivated by this, we investigate the tacit assumption that an attacker cannot learn the correct TTL value. By using a combination of tracerouting and BGP data, we build statistical models which allow to estimate the TTL within that tolerance level. We observe that by wisely choosing the used amplifiers, the attacker is able to circumvent such TTL-based defenses. Finally, we argue that any (current or future) defensive system based on TTL values can be bypassed in a similar fashion, and find that future research must be steered towards more fundamental solutions to thwart any kind of IP spoofing attacks.
RAID 2016, 19th International Symposium on Research in Attacks, Intrusions and Defenses