1000 days of UDP amplification DDoS attacks

Distributed Denial of Service (DDoS) attacks employing reflected UDP amplification are regularly used to disrupt networks and systems. The amplification allows one rented server to generate significant volumes of data, while the reflection hides the identity of the attacker. Consequently this is an attractive, low risk, strategy for criminals bent on vandalism and extortion. To measure the uptake of this strategy we analyse the results of running a network of honeypot UDP reflectors (median size 65 nodes) from July 2014 onwards. We explore the life cycle of attacks that use our reflectors, from the scanning phase used to detect our honeypot machines, through to their use in attacks. We see a median of 1450 malicious scanners per day across all UDP protocols, and have recorded details of 5.18 million subsequent attacks involving in excess of 3.31 trillion packets. Using a capture-recapture statistical technique, we estimate that our reflectors can see between 85.1% and 96.6% of UDP reflection attacks over our measurement period.We are extremely grateful to the organisations and individuals who have hosted Hopscotch nodes, and in particular the ShadowServer Foundation and Digital Ocean Inc. Daniel R. Thomas is supported by a grant from ThreatSTOP Inc. Richard Clayton is supported by the Department of Homeland Security (DHS) Science and Technology Directorate, Cyber Security Division (DHSS\&T/CSD) Broad Agency Announcement 11.02, the Government of Australia and SPAWAR Systems Center Pacific [contract number N66001-13-C-0131]; and the EPSRC [grant number EP/M020320/1]. Alastair R. Beresford is partly supported by the EPSRC [grant number EP/M020320/1]. The opinions, findings, and conclusions or recommendations expressed are those of the authors and do not necessarily reflect those of any of the funders

DDoS Never Dies? An IXP Perspective on DDoS Amplification Attacks

DDoS attacks remain a major security threat to the continuous operation of Internet edge infrastructures, web services, and cloud platforms. While a large body of research focuses on DDoS detection and protection, to date we ultimately failed to eradicate DDoS altogether. Yet, the landscape of DDoS attack mechanisms is even evolving, demanding an updated perspective on DDoS attacks in the wild. In this paper, we identify up to 2608 DDoS amplification attacks at a single day by analyzing multiple Tbps of traffic flows at a major IXP with a rich ecosystem of different networks. We observe the prevalence of well-known amplification attack protocols (e.g., NTP, CLDAP), which should no longer exist given the established mitigation strategies. Nevertheless, they pose the largest fraction on DDoS amplification attacks within our observation and we witness the emergence of DDoS attacks using recently discovered amplification protocols (e.g., OpenVPN, ARMS, Ubiquity Discovery Protocol). By analyzing the impact of DDoS on core Internet infrastructure, we show that DDoS can overload backbone-capacity and that filtering approaches in prior work omit 97% of the attack traffic.Comment: To appear at PAM 202

DDoS Hide & Seek:On the effectiveness of a booter services takedown

Booter services continue to provide popular DDoS-as-a-service platforms and enable anyone irrespective of their technical ability, to execute DDoS attacks with devastating impact. Since booters are a serious threat to Internet operations and can cause significant financial and reputational damage, they also draw the attention of law enforcement agencies and related counter activities. In this paper, we investigate booter-based DDoS attacks in the wild and the impact of an FBI takedown targeting 15 booter websites in December 2018 from the perspective of a major IXP and two ISPs. We study and compare attack properties of multiple booter services by launching Gbps-level attacks against our own infrastructure. To understand spatial and temporal trends of the DDoS traffic originating from booters we scrutinize 5 months, worth of inter-domain traffic. We observe that the takedown only leads to a temporary reduction in attack traffic. Additionally, one booter was found to quickly continue operation by using a new domain for its website

Using honeypots to trace back amplification DDoS attacks

In today’s interconnected world, Denial-of-Service attacks can cause great harm by simply rendering a target system or service inaccessible. Amongst the most powerful and widespread DoS attacks are amplification attacks, in which thousands of vulnerable servers are tricked into reflecting and amplifying attack traffic. However, as these attacks inherently rely on IP spoofing, the true attack source is hidden. Consequently, going after the offenders behind these attacks has so far been deemed impractical. This thesis presents a line of work that enables practical attack traceback supported by honeypot reflectors. To this end, we investigate the tradeoffs between applicability, required a priori knowledge, and traceback granularity in three settings. First, we show how spoofed attack packets and non-spoofed scan packets can be linked using honeypot-induced fingerprints, which allows attributing attacks launched from the same infrastructures as scans. Second, we present a classifier-based approach to trace back attacks launched from booter services after collecting ground-truth data through self-attacks. Third, we propose to use BGP poisoning to locate the attacking network without prior knowledge and even when attack and scan infrastructures are disjoint. Finally, as all of our approaches rely on honeypot reflectors, we introduce an automated end-to-end pipeline to systematically find amplification vulnerabilities and synthesize corresponding honeypots.In der heutigen vernetzten Welt können Denial-of-Service-Angriffe große Schäden verursachen, einfach indem sie ihr Zielsystem unerreichbar machen. Zu den stärksten und verbreitetsten DoS-Angriffen zählen Amplification-Angriffe, bei denen tausende verwundbarer Server missbraucht werden, um Angriffsverkehr zu reflektieren und zu verstärken. Da solche Angriffe jedoch zwingend gefälschte IP-Absenderadressen nutzen, ist die wahre Angriffsquelle verdeckt. Damit gilt die Verfolgung der Täter bislang als unpraktikabel. Diese Dissertation präsentiert eine Reihe von Arbeiten, die praktikable Angriffsrückverfolgung durch den Einsatz von Honeypots ermöglicht. Dazu untersuchen wir das Spannungsfeld zwischen Anwendbarkeit, benötigtem Vorwissen, und Rückverfolgungsgranularität in drei Szenarien. Zuerst zeigen wir, wie gefälschte Angriffs- und ungefälschte Scan-Datenpakete miteinander verknüpft werden können. Dies ermöglicht uns die Rückverfolgung von Angriffen, die ebenfalls von Scan-Infrastrukturen aus durchgeführt wurden. Zweitens präsentieren wir einen Klassifikator-basierten Ansatz um Angriffe durch Booter-Services mittels vorher durch Selbstangriffe gesammelter Daten zurückzuverfolgen. Drittens zeigen wir auf, wie BGP Poisoning genutzt werden kann, um ohne weiteres Vorwissen das angreifende Netzwerk zu ermitteln. Schließlich präsentieren wir einen automatisierten Prozess, um systematisch Schwachstellen zu finden und entsprechende Honeypots zu synthetisieren

Utilizing the SHAP framework to bypass intrusion detection systems

The number of people connected to the internet is swiftly growing, and technology is increasingly integrated into our daily lives. With this increase, there is a surge of attacks towards the digital infrastructure. It is of great importance to understand how we can analyze and mitigate attacks to ensure the availability of the services we depend on. The purpose of this study is two-sided. The first is to evaluate different machine learning models in intrusion detection systems. We measured their performance on distributed denial of service(DDoS) attacks and explained them using SHAP values. Secondly, by using the SHAP values, we found the most important features and generated multiple variations of the same attacks to see how the different models reacted. Ultimately, we found that SHAP values have great potential as a base for generating more sophisticated attacks. In turn, the modified attacks were able to bypass intrusion detection systems.Masteroppgave i informatikkINF399MAMN-PROGMAMN-IN

Security Vulnerability Evaluation of Popular Personal Firewalls and Operating Systems

In this thesis, experimental evaluation of security vulnerabilities has been performed under DoS attacks for popular personal firewalls from McAfee, Norton and Kaspersky; and for operating systems namely Apple’s Leopard and SnowLeopard, and Microsoft’s Windows XP and Windows 7. Our experimental results show that the firewalls and operating systems behave differently under a given DoS attack. Some of the firewalls crashed under certain DoS attacks especially when they were configured to prevent and block packets belonging to such attacks. Operating systems evaluated in this thesis were also found to have different built-in security capabilities, and some of them even crashed under certain DoS attacks requiring forced reboot of the system. Comparative performance of firewalls and operating systems under DoS attacks has been presented

DDoS cyber-incident detection in smart grids

The smart grid (SG) offers potential benefits for utilities, electric generators, and customers alike. However, the prevalence of cyber-attacks targeting the SG emphasizes its dark side. In particular, distributed denial-of-service (DDoS) attacks can affect the communication of different devices, interrupting the SG’s operation. This could have profound implications for the power system, including area blackouts. The problem is that few operational technology tools provide reflective DDoS protection. Furthermore, such tools often fail to classify the types of attacks that have occurred. Defensive capabilities are necessary to identify the footprints of attacks in a timely manner, as they occur, and to make these systems sustainable for delivery of the services as expected. To meet this need for defensive capabilities, we developed a situational awareness tool to detect system compromise by monitoring the indicators of compromise (IOCs) of amplification DDoS attacks. We achieved this aim by finding IOCs and exploring attack footprints to understand the nature of such attacks and their cyber behavior. Finally, an evaluation of our approach against a real dataset of DDoS attack instances indicated that our tool can distinguish and detect different types of amplification DDoS attacks

The security of NTP's datagram protocol

For decades, the Network Time Protocol (NTP) has been used to synchronize computer clocks over untrusted network paths. This work takes a new look at the security of NTP’s datagram protocol. We argue that NTP’s datagram protocol in RFC5905 is both underspecified and flawed. The NTP specifications do not sufficiently respect (1) the conflicting security requirements of different NTP modes, and (2) the mechanism NTP uses to prevent off-path attacks. A further problem is that (3) NTP’s control-query interface reveals sensitive information that can be exploited in off-path attacks. We exploit these problems in several attacks that remote attackers can use to maliciously alter a target’s time. We use network scans to find millions of IPs that are vulnerable to our attacks. Finally, we move beyond identifying attacks by developing a cryptographic model and using it to prove the security of a new backwards-compatible client/server protocol for NTP.https://eprint.iacr.org/2016/1006.pdfhttps://eprint.iacr.org/2016/1006.pdfPublished versio