The layered architecture of the TCP/IP protocol stack enables protocol layers to be implemented independently and flexibly. However, this layered design introduces potential security risks when shared resources are not properly managed between different layers. This paper investigates a neglected cross-layer shared resource risk, termed SocketFilled, which exploits the insecure usage of the UDP send buffer at the transport layer by the link layer, resulting in the interruption of response packets from the upper application layer. To explore the root causes of cross-layer DoS vulnerabilities resulting from the implementation of the TCP/IP protocol stack, we systematically analyzed the protocol standards of address resolution and reviewed the implementation in mainstream open-source operating systems. Moreover, we conducted a comprehensive experimental evaluation of mainstream operating systems (e.g., Linux and FreeBSD) and UDP services (e.g., DNS and QUIC). The experimental results show that the latest version of Linux and UDP service software (e.g., BIND9, PowerDNS, and Nginx) are affected, causing significant packet loss and even complete service interruption. Then, we estimated the impact range of SocketFilled in the wild and demonstrated that 17.3% of open resolvers,54.3% of authoritative servers of the Tranco Top 100K domains, and 3.8% of these well-known domains' HTTP/3 servers are potentially affected, including Bing, Amazon, and Shopee, after excluding the influence of cloud servers. We have conducted responsible disclosure by reporting the vulnerability to the Linux community. Our research highlights the effectiveness of cross-layer mechanisms in DoS attacks and calls for heightened attention to the layered complexity of protocol stack implementations within the security community.

Peer-assisted delivery network (PDN) can significantly reduce the bandwidth cost incurred by traditional CDN services. However, it is unclear whether they have been deployed extensively and their security implications have never been investigated thoroughly. In this paper, we report the first effort to address this issue through an automatic pipeline to discover real-world PDN services and their customers, and a PDN analysis framework to test the potential security and privacy risks of these services. Our results have revealed the extensive adoption of PDN across the Internet, especially by Chinese video platforms. Most importantly, our analysis on these PDN services has brought to light a series of novel security vulnerabilities, i.e., free riding of PDN services, video segment pollution, and unreported privacy risks, i.e., resource squatting and extensive leakage of video viewers' IPs. We have responsibly disclosed these security risks to relevant PDN providers which in turn have well acknowledged our findings.

Authoritative nameservers are delegated to provide the final resource record. Since the security and robustness of DNS are critical to the general operation of the Internet, domain name owners are required to deploy multiple candidate nameservers for traffic load balancing. Once the load balancing mechanism is compromised, an adversary can manipulate a large number of legitimate DNS requests to a specified candidate nameserver. As a result, it may not only bypass the defense mechanisms used to filter malicious traffic that can overload the victim nameserver, but also lowers the bar for DNS traffic hijacking and cache poisoning attacks.

Leveraging DNS for covert communications is appealing since most networks allow DNS traffic, especially the ones directed toward renowned DNS hosting services. Unfortunately, most DNS hosting services overlook domain ownership verification, enabling miscreants to host undelegated DNS records of a domain they do not own. Consequently, miscreants can conduct covert communication through such undelegated records for whitelisted domains on reputable hosting providers. In this paper, we shed light on the emerging threat posed by undelegated records and demonstrate their exploitation in the wild. To the best of our knowledge, this security risk has not been studied before.

In recent years, the security implication of stale NS records, which point to a nameserver that no longer resolves the domain, has been unveiled. Prior research studied the stale DNS records that point to expired domains. The popularity of DNS hosting services brings in a new category of stale NS records, which reside in the domain's zone (instead of the TLD zone) for an active domain. To the best of our knowledge, the security risk of this kind of stale NS record has never been studied before. In our research, we show that this new type of stale NS record can be practically exploited, causing a stealthier hijack of domains associated with the DNS hosting service. We also performed a large-scale analysis on over 1M high-profile domains, 17 DNS hosting providers and 12 popular public resolver operators to confirm the prevalence of this security risk. Our research further discovers 628 hijackable domains (e.g., 6 government entities and 2 payment services), 14 affected DNS hosting providers (e.g., Amazon Route 53), and 10 vulnerable public resolver operators (e.g., CloudFlare). Furthermore, we conducted an in-depth measurement analysis on them, thus providing a better understanding of this new security risk. Also, we explore the mitigation techniques that can be adopted by different affected parties.

Promotional infection is an attack in which the adversary exploits a website's weakness to inject illicit advertising content. Detection of such an infection is challenging due to its similarity to legitimate advertising activities. An interesting observation we make in our research is that such an attack almost always incurs a great semantic gap between the infected domain (e.g., a university site) and the content it promotes (e.g., selling cheap viagra). Exploiting this gap, we developed a semantic-based technique, called Semantic Inconsistency Search (SEISE), for efficient and accurate detection of the promotional injections on sponsored top-level domains (sTLD) with explicit semantic meanings. Our approach utilizes Natural Language Processing (NLP) to identify the bad terms (those related to illicit activities like fake drug selling, etc.) most irrelevant to an sTLD's semantics. These terms, which we call irrelevant bad terms (IBTs), are used to query search engines under the sTLD for suspicious domains. Through a semantic analysis on the results page returned by the search engines, SEISE is able to detect those truly infected sites and automatically collect new IBTs from the titles/URLs/snippets of their search result items for finding new infections. Running on 403 sTLDs with an initial 30 seed IBTs, SEISE analyzed 100K fully qualified domain names (FQDN), and along the way automatically gathered nearly 600 IBTs. In the end, our approach detected 11K infected FQDN with a false detection rate of 1.5% and over 90% coverage. Our study shows that by effective detection of infected sTLDs, the bar to promotion infections can be substantially raised, since other non-sTLD vulnerable domains typically have much lower Alexa ranks and are therefore much less attractive for underground advertising. Our findings further bring to light the stunning impacts of such promotional attacks, which compromise FQDNs under 3% of .edu, .gov domains and over one thousand gov.cn domains, including those of leading universities such as stanford.edu, mit.edu, princeton.edu, havard.edu and government institutes such as nsf.gov and nih.gov. We further demonstrate the potential to extend our current technique to protect generic domains such as .com and .org.

Compromised websites that redirect web traffic to malicious hosts play a critical role in organized web crimes, serving as doorways to all kinds of malicious web activities (e.g., drive-by downloads, phishing etc.). They are also among the most elusive components of a malicious web infrastructure and extremely difficult to hunt down, due to the simplicity of redirect operations, which also happen on legitimate sites, and extensive use of cloaking techniques. Making the detection even more challenging is the recent trend of injecting redirect scripts into JavaScript (JS) files, as those files are not indexed by search engines and their infections are therefore more difficult to catch. In our research, we look at the problem from a unique angle: the adversary's strategy and constraints for deploying redirect scripts quickly and stealthily. Specifically, we found that such scripts are often blindly injected into both JS and HTML files for a rapid deployment, changes to the infected JS files are often made minimum to evade detection and also many JS files are actually JS libraries (JS-libs) whose uninfected versions are publicly available. Based upon those observations, we developed JsRED, a new technique for the automatic detection of unknown redirect-script injections. Our approach analyzes the difference between a suspicious JS-lib file and its clean counterpart to identify malicious redirect scripts and further searches for similar scripts in other JS and HTML files. This simple, lightweight approach is found to work effectively against redirect injection campaigns: our evaluation shows that JsRED captured most of compromised websites with almost no false positives, significantly outperforming a commercial detection service in terms of finding unknown JS infections. Based upon the compromised websites reported by JsRED, we further conducted a measurement study that reveals interesting features of redirect payloads and a new Peer-to-Peer network the adversary constructed to evade detection.