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Yevheniya Nosyk

Publications and source records attributed to Yevheniya Nosyk.

8 recordsLinked to original sources

INFERMAL: Inferential analysis of maliciously registered domains

Cybercriminals have long depended on domain names for phishing, spam, malware distribution, and botnet operation. To facilitate the malicious activities, they continually register new domain names for exploitation. Previous work revealed an abnormally high concentration of malicious registrations in a handful of domain name registrars and top-level domains (TLDs). Anecdotal evidence suggests that low registration prices attract cybercriminals, implying that higher costs may potentially discourage them. However, no existing study has systematically analyzed the factors driving abuse, leaving a critical gap in understanding how different variables influence malicious registrations. In this report, we carefully distill the inclinations and aversions of malicious actors during the registration of new phishing domain names. We compile a comprehensive list of 73 features encompassing three main latent factors: registration attributes, proactive verification, and reactive security practices. Through a GLM regression analysis, we find that each dollar reduction in registration fees corresponds to a 49% increase in malicious domains. The availability of free services, such as web hosting, drives an 88% surge in phishing activities. Conversely, stringent restrictions cut down abuse by 63%, while registrars providing API access for domain registration or account creation experience a staggering 401% rise in malicious domains. This exploration may assist intermediaries involved in domain registration to develop tailored anti-abuse practices, yet aligning them with their economic incentives.

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Day in the Life of RIPE Atlas: Operational Insights and Applications in Network Measurements

Network measurement platforms are increasingly popular among researchers and operators alike due to their distributed nature, simplifying measuring the remote parts of the Internet. RIPE Atlas boasts over 12.9K vantage points in 178 countries worldwide and serves as a vital tool for analyzing anycast deployment, network latency, and topology, to name a few. Despite generating over a terabyte of measurement results per day, there is limited understanding of the underlying processes. This paper delves into one day in the life of RIPE Atlas, encompassing 50.9K unique measurements and over 1.3 billion results. While most daily measurements are user-defined, it is built-ins and anchor meshes that account for 89% of produced results. We extensively examine how different probes and measurements contribute to the daily operations of RIPE Atlas and consider any bias they may introduce. Furthermore, we demonstrate how existing measurements can be leveraged to investigate censorship, traceroute symmetry, and the usage of reserved address blocks, among others. Finally, we curate a set of recommendations for researchers using the RIPE Atlas platform to foster transparency, reproducibility, and ethics.

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Guardians of DNS Integrity: A Remote Method for Identifying DNSSEC Validators Across the Internet

DNS Security Extensions (DNSSEC) provide the most effective way to fight DNS cache poisoning attacks. Yet, very few DNS resolvers perform DNSSEC validation. Identifying such systems is non-trivial and the existing methods are not suitable for Internet-scale measurements. In this paper, we propose a novel remote technique for identifying DNSSEC-validating resolvers. The proposed method consists of two steps. In the first step, we identify open resolvers by scanning 3.1 billion end hosts and request every non-forwarder to resolve one correct and seven deliberately misconfigured domains. We then build a classifier that discriminates validators from non-validators based on query patterns and DNS response codes. We find that while most open resolvers are DNSSEC-enabled, less than 18% in IPv4 (38% in IPv6) validate received responses. In the second step, we remotely identify closed non-forwarders in networks that do not have inbound Source Address Validation (SAV) in place. Using the classifier built in step one, we identify 37.4% IPv4 (42.9% IPv6) closed DNSSEC validators and cross-validate the results using RIPE Atlas probes. Finally, we show that the discovered (non)-validators actively send requests to DNS root servers, suggesting that we deal with operational recursive resolvers rather than misconfigured machines.

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Don't Get Hijacked: Prevalence, Mitigation, and Impact of Non-Secure DNS Dynamic Updates

DNS dynamic updates represent an inherently vulnerable mechanism deliberately granting the potential for any host to dynamically modify DNS zone files. Consequently, this feature exposes domains to various security risks such as domain hijacking, compromise of domain control validation, and man-in-the-middle attacks. Originally devised without the implementation of authentication mechanisms, non-secure DNS updates were widely adopted in DNS software, subsequently leaving domains susceptible to a novel form of attack termed zone poisoning. In order to gauge the extent of this issue, our analysis encompassed over 353 million domain names, revealing the presence of 381,965 domains that openly accepted unsolicited DNS updates. We then undertook a comprehensive three-phase campaign involving the notification of Computer Security Incident Response Teams (CSIRTs). Following extensive discussions spanning six months, we observed substantial remediation, with nearly 54\% of nameservers and 98% of vulnerable domains addressing the issue. This outcome serves as evidence that engaging with CSIRTs can prove to be an effective approach for reporting security vulnerabilities. Moreover, our notifications had a lasting impact, as evidenced by the sustained low prevalence of vulnerable domains.

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The Closed Resolver Project: Measuring the Deployment of Source Address Validation of Inbound Traffic

Source Address Validation (SAV) is a standard aimed at discarding packets with spoofed source IP addresses. The absence of SAV for outgoing traffic has been known as a root cause of Distributed Denial-of-Service (DDoS) attacks and received widespread attention. While less obvious, the absence of inbound filtering enables an attacker to appear as an internal host of a network and may reveal valuable information about the network infrastructure. Inbound IP spoofing may amplify other attack vectors such as DNS cache poisoning or the recently discovered NXNSAttack. In this paper, we present the preliminary results of the Closed Resolver Project that aims at mitigating the problem of inbound IP spoofing. We perform the first Internet-wide active measurement study to enumerate networks that filter or do not filter incoming packets by their source address, for both the IPv4 and IPv6 address spaces. To achieve this, we identify closed and open DNS resolvers that accept spoofed requests coming from the outside of their network. The proposed method provides the most complete picture of inbound SAV deployment by network providers. Our measurements cover over 55 % IPv4 and 27 % IPv6 Autonomous Systems (AS) and reveal that the great majority of them are fully or partially vulnerable to inbound spoofing. By identifying dual-stacked DNS resolvers, we additionally show that inbound filtering is less often deployed for IPv6 than it is for IPv4. Overall, we discover 13.9 K IPv6 open resolvers that can be exploited for amplification DDoS attacks - 13 times more than previous work. Furthermore, we enumerate uncover 4.25 M IPv4 and 103 K IPv6 vulnerable closed resolvers that could only be detected thanks to our spoofing technique, and that pose a significant threat when combined with the NXNSAttack.

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Source Address Validation

Source address validation (SAV) is a standard formalized in RFC 2827 aimed at discarding packets with spoofed source IP addresses. The absence of SAV has been known as a root cause of reflection distributed denial-of-service (DDoS) attacks. Outbound SAV (oSAV): filtering applied at the network edge to traffic coming from inside the customer network to the outside. Inbound SAV (iSAV): filtering applied at the network edge to traffic coming from the outside to the customer network.

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Study on Domain Name System (DNS) Abuse: Technical Report

A safe and secure Domain Name System (DNS) is of paramount importance for the digital economy and society. Malicious activities on the DNS, generally referred to as "DNS abuse" are frequent and severe problems affecting online security and undermining users' trust in the Internet. The proposed definition of DNS abuse is as follows: Domain Name System (DNS) abuse is any activity that makes use of domain names or the DNS protocol to carry out harmful or illegal activity. DNS abuse exploits the domain name registration process, the domain name resolution process, or other services associated with the domain name (e.g., shared web hosting service). Notably, we distinguish between: maliciously registered domain names: domain name registered with the malicious intent to carry out harmful or illegal activity compromised domain names: domain name registered by bona fide third-party for legitimate purposes, compromised by malicious actors to carry out harmful and illegal activity. DNS abuse disrupts, damages, or otherwise adversely impacts the DNS and the Internet infrastructure, their users or other persons.

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Don't Forget to Lock the Front Door! Inferring the Deployment of Source Address Validation of Inbound Traffic

This paper concerns the problem of the absence of ingress filtering at the network edge, one of the main causes of important network security issues. Numerous network operators do not deploy the best current practice - Source Address Validation (SAV) that aims at mitigating these issues. We perform the first Internet-wide active measurement study to enumerate networks not filtering incoming packets by their source address. The measurement method consists of identifying closed and open DNS resolvers handling requests coming from the outside of the network with the source address from the range assigned inside the network under the test. The proposed method provides the most complete picture of the inbound SAV deployment state at network providers. We reveal that 32 673 Autonomous Systems (ASes) and 197 641 Border Gateway Protocol (BGP) prefixes are vulnerable to spoofing of inbound traffic. Finally, using the data from the Spoofer project and performing an open resolver scan, we compare the filtering policies in both directions.

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