Stellar: Network Attack Mitigation Using Advanced Blackholing
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Stellar: Network Attack Mitigation using Advanced Blackholing Christoph Dietzel Matthias Wichtlhuber TU Berlin/DE-CIX DE-CIX [email protected] [email protected] Georgios Smaragdakis Anja Feldmann TU Berlin Max Planck Institute for Informatics [email protected] [email protected] ABSTRACT is generated and steered towards a target service to make it un- Network attacks, including Distributed Denial-of-Service (DDoS), available. Once the network links to the target are congested due continuously increase in terms of bandwidth along with damage to the DDoS attack, legitimate traffic that traverses the same links (recent attacks exceed 1:7 Tbps) and have a devastating impact on is also affected. the targeted companies/governments. Over the years, mitigation DDoS threats are continuously increasing in terms of volume, fre- techniques, ranging from blackholing to policy-based filtering at quency, and complexity. While the largest observed and publicly re- routers, and on to traffic scrubbing, have been added to the network ported attacks were between 50 to 200 Gbps before 2015 [59, 60, 70], operator’s toolbox. Even though these mitigation techniques pro- current peaks are an order of magnitude higher and exceeded 1 vide some protection, they either yield severe collateral damage, e.g., Tbps [9, 48] in 2016, and 1:7 Tbps [57] in early 2018. We also ob- dropping legitimate traffic (blackholing), are cost-intensive, ordo serve a massive rise in the number of DDoS attacks. Jonker et not scale well for Tbps level attacks (ACL filtering, traffic scrubbing), al. [41] report that a third of all active /24 networks were targeted or require cooperation and sharing of resources (Flowspec). by DDoS attacks between 2016 and 2017. Similar observations are In this paper, we propose Advanced Blackholing and its system reported by the security industry [3, 19]. A particularly prominent realization Stellar. Advanced blackholing builds upon the scalability DDoS attack type is amplification attacks [64, 65]. They take advan- of blackholing while limiting collateral damage by increasing its tage of protocol design flaws, whereby a relatively small request granularity. Moreover, Stellar reduces the required level of coopera- triggers a significantly larger response. With a spoofed source IP tion to enhance mitigation effectiveness. We show that fine-grained address [49] the response traffic is amplified and reflected tothe blackholing can be realized, e.g., at a major IXP, by combining target. Vulnerable protocols include classical protocols such as NTP, available hardware filters with novel signaling mechanisms. We DNS, and/or SNMP [20, 64], as well as relatively new protocols, e.g., evaluate the scalability and performance of Stellar at a large IXP DNSSEC [74] and memcached [5, 57]. Amplification factors of up that interconnects more than 800 networks, exchanges more than to 50; 000× have been witnessed in the wild [73]. To exemplify, a 6 Tbps traffic, and witnesses many network attacks every day. Our request of 15 bytes can trigger a 750 Kbytes response. results show that network attacks, e.g., DDoS amplification attacks, can be successfully mitigated while the networks and services under attack continue to operate untroubled. 1.1 DDoS Mitigation: State of the Art This alarming increase in DDoS attacks and their sophistication CCS CONCEPTS and severity, e.g., see [56, 77], demands scalable yet cost-effective • Networks → Denial-of-service attacks; Network components; countermeasures. However, at this point, we are left with various Network measurement; Network services; mitigation techniques and tools that can partially counteract the impact of the attacks. These include: (i) Traffic Scrubbing Services KEYWORDS (TSS), (ii) Router Access Control List Filters (ACL), (iii) Remotely BGP; IXP; Blackholing; DDoS Mitigation. Triggered Black Hole (RTBH), and (iv) BGP Flowspec. Traffic Scrubbing Services (TSS): offer all-round carefree ser- 1 INTRODUCTION vices to their subscribers. They redirect the traffic of a service to specialized hardware either via DNS redirection or BGP delega- The revolution of the digital age fueled by the Internet has attracted tion [43]. There they classify traffic as unwanted or benign and the good but the evil alike. While the threats executed over the In- send the benign “scrubbed” traffic to its original destination or move ternet are multifaceted from a criminalistics perspective, e.g., fraud, the destination to their network [4, 30, 43, 75]. The convenience and data and identity theft, espionage, or cyber terrorism, the dominant fine-grained filtering of TSS comes at significant recurring costs network threat is Denial-of-Service (DoS) attacks [2]. The goal of and requires in-time subscription and setup. Moreover, it currently DoS attacks is to force a service or system to become unavailable has inherent limitations, e.g., per packet or per flow processing for by consuming crucial resources. These resources can be computing deep packet inspection, which can reduce effectiveness [75] and power at the servers or exploitation of application-layer vulnerabil- does not cope with Tbps-level attacks [48]. Moreover, it may reroute ities, i.e., semantic attacks, or network bandwidth, i.e., volumetric traffic and, thus, impose performance penalties, and is vulnerable attacks. To conduct such volumetric attacks, adversaries often use to evasion tactics [42]. Distributed DoS (DDoS). Traffic from numerous distributed sources 1 CoNEXT ’18, December 4–7, 2018, Heraklion, Greece C. Dietzel et al. ACL Filters: are often used by Internet Service Providers (ISPs) TSS ACL RTBH Flowspec Advanced and Internet Exchange Points (IXPs) to overcome specific network filters Blackholing problems. They deploy policy-based filters that drop unwanted traf- Granularity 3 3 7 3 3 fic at their AS border routers. The implementations and capabilities Signaling complexity 7 7 7 7 3 Cooperation •• 7 7 3 depend on the vendor-specific hardware, e.g., ACL rules or QoS Resource sharing 3 3 3 7 3 classifiers. Such filters can work well if the hardware is homoge- Telemetry 3 7 7 • 3 neous, the network engineers have sufficient expertise, and the Scalability 7 • 3 3 3 Resources 7 7 3 7 3 network management system supports the automated deployment Performance 7 3 3 3 3 of filters. However, such systems typically do not scale well and, Reaction time 7 7 3 3 3 given that the filtering location is beyond the ingress points ofthe Costs 7 • 3 3 3 network, the bandwidth to a neighbor AS can still be exhausted. Table 1: Advanced Blackholing vs. DDoS mitigation solu- Remotely Triggered Black Hole (RTBH): also referred to as tions. 3: advantage, 7: disadvantage, •: neutral. BGP Blackholing, is an operational DDoS mitigation technique [16]. ASes under attack can signal upstream ISPs [24, 40] or IXPs [22, 50] to drop traffic to specific IP prefixes. Using BGP to trigger blackhol- regarding the state and volume of the attack, i.e., if it is still on- ing is simple to realize and lowers the entry barrier for ASes, but going or is over. Flowspec standardization [52] only recommends limits the level of granularity of the blackhole (to IP prefixes) and telemetry but ultimately it is a vendor-specific implementation. For the acceptance of neighboring ASes. Despite substantial growth a summary of the pros and cons see Table 1. of blackholing usage (it quadrupled between 2015 and 2017 [33]) that is evidence of its effectiveness to drop large volumes of attack 1.2 Advanced Blackholing in a Nutshell traffic [26], unfortunately, it is coarse-grained. BGP blackholing also In this paper, we propose another approach for attack mitigation, drops legitimate traffic to the prefix under attack and thereby causes called Advanced Blackholing (Advanced BH). Advanced Blackhol- collateral damage. Essentially, this makes the IP prefix partially un- ing does not require trust, cooperation, and sharing of resources reachable. For RTBH to be effective, cooperation between network among networks. It builds upon the excellent scalability of RTBH operators to act upon receiving a blackhole signal (typically, a BGP (to aggressively drop volumetric attack traffic) while incorporating community) is required, see Section 2. Namely, it requires that BGP the good properties of ACLs, Flowspec, and TSS (fine-granular fil- messages for prefixes more specific than /24 in IPv4 are propagated, tering) in a lightweight fashion. Thus, Advanced Blackholing offers thus, networks operators have to set up exceptions for blackholing a new service in between RTBH and TSS and, as we will show, it to accept BGP messages such prefixes, e.g., /32 in IPv4. can be deployed at scale, e.g., at IXPs. BGP Flowspec: the BGP flow specification feature, also referred IXPs offer an ideal deployment location for DDoS traffic mitiga- to as Flowspec, allows the deployment and propagation of more tion as many ISPs use them to exchange traffic, e.g., more than 800 fine-grained filters (compared to RTBH) across AS domain bor- networks and more than 6 Tbps at DE-CIX in Frankfurt or AMS-IX ders, e.g., to mitigate DDoS attacks [18]. Flow specifications can in Amsterdam. Notice that by enabling such a service in one of match a particular flow with a source, destination, layer-4 (L4) these large IXPs, hundreds of member networks (as well as their parameters, packet characteristics such as length and fragment, customers and peer networks) will immediately benefit without and allow to specify a drop rate limit.