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.

This paper reports on the first Internet-wide active measurement study to enumerate networks not filtering incoming packets based on their source address. Our method identifies closed and open DNS resolvers handling requests from the outside of the network with the source address in the prefix of the tested network. The study gives the most complete picture of the inbound Source Address Validation deployment at network providers: 32,673 IPv4 ASes and 197,641 IPv4 BGP prefixes are vulnerable to spoofing of inbound traffic.

Internet measurement tools are used to make inferences about network policies and practices across the Internet, such as censorship, traffic manipulation, bandwidth, and security measures. Some tools must be run from vantage points within individual networks, so are dependent on volunteer recruitment. A small pool of volunteers limits the impact of these tools. Crowdsourcing marketplaces can potentially recruit workers to run tools from networks not covered by the volunteer pool. We design an infrastructure to collect and synchronize measurements from five crowdsourcing platforms, and use that infrastructure to collect data on network source address validation policies for CAIDA's Spoofer project. In six weeks we increased the coverage of Spoofer measurements by recruiting 1519 workers from within 91 countries and 784 unique ASes for 2,000 Euro; 342 of these ASes were not previously covered, and represent a 15% increase in ASes over the prior 12 months. We describe lessons learned in recruiting and renumerating workers; in particular, strategies to address worker behavior when workers are screened because of overlap in the volunteer pool.

Despite source IP address spoofing being a known vulnerability for at least 25 years, and despite many efforts to shed light on the problem, spoofing remains a popular attack method for redirection, amplification, and anonymity. To defeat these attacks requires operators to ensure their networks filter packets with spoofed source IP addresses, known as source address validation (SAV), best deployed at the edge of the network where traffic originates. In this paper, we present a new method using routing loops appearing in traceroute data to infer inadequate SAV at the transit provider edge, where a provider does not filter traffic that should not have come from the customer. Our method does not require a vantage point within the customer network. We present and validate an algorithm that identifies at Internet scale which loops imply a lack of ingress filtering by providers. We found 703 provider ASes that do not implement ingress filtering on at least one of their links for 1,780 customer ASes. Most of these observations are unique compared to the existing methods of the Spoofer and Open Resolver projects. By increasing the visibility of the networks that allow spoofing, we aim to strengthen the incentives for the adoption of SAV.