William Findlay (Carleton University) and AbdelRahman Abdou (Carleton University)

While security researchers are adept at discovering vulnerabilities and measuring their impact, disclosing vulnerabilities to affected stakeholders has traditionally been difficult. Beyond public notices such as CVEs, there have traditionally been few appropriate channels through which to directly communicate the nature and scope of a vulnerability to those directly impacted by it. Security.txt is a relatively new proposed standard that hopes to change this by defining a canonical file format and URI through which organizations can provide contact information for vulnerability disclosure. However, despite its favourable characteristics, limited studies have systematically analyzed how effective Security.txt might be for a widespread vulnerability notification campaign. In this paper, we present a large-scale study of Security.txt’s adoption over the top 1M popular domains according to the Tranco list. We measure specific features of Security.txt files such as contact information, preferred language, and RFC version compliance. We then analyze these results to better understand how suitable the current Security.txt standard is for facilitating a large-scale vulnerability notification campaign, and make recommendations for improving future version of the standard.

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DeFiIntel: A Dataset Bridging On-Chain and Off-Chain Data for...

Iori Suzuki (Graduate School of Environment and Information Sciences, Yokohama National University), Yin Minn Pa Pa (Institute of Advanced Sciences, Yokohama National University), Nguyen Thi Van Anh (Institute of Advanced Sciences, Yokohama National University), Katsunari Yoshioka (Graduate School of Environment and Information Sciences, Yokohama National University)

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Bridging the Privacy Gap: Enhanced User Consent Mechanisms on...

Carl Magnus Bruhner (Linkoping University), David Hasselquist (Linkoping University, Sectra Communications), Niklas Carlsson (Linkoping University)

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Progressive Scrutiny: Incremental Detection of UBI bugs in the...

Yizhuo Zhai (University of California, Riverside), Yu Hao (University of California, Riverside), Zheng Zhang (University of California, Riverside), Weiteng Chen (University of California, Riverside), Guoren Li (University of California, Riverside), Zhiyun Qian (University of California, Riverside), Chengyu Song (University of California, Riverside), Manu Sridharan (University of California, Riverside), Srikanth V. Krishnamurthy (University of California, Riverside),…

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FitM: Binary-Only Coverage-GuidedFuzzing for Stateful Network Protocols

Dominik Maier, Otto Bittner, Marc Munier, Julian Beier (TU Berlin)

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