Michele Spagnuolo (Google), David Dworken (Google), Artur Janc (Google), Santiago Díaz (Google), Lukas Weichselbaum (Google)

The area of security measurability is gaining increased attention, with a wide range of organizations calling for the development of scalable approaches for assessing the security of software systems and infrastructure. In this paper, we present our experience developing Security Signals, a comprehensive system providing security measurability for web services, deployed in a complex application ecosystem of thousands of web services handling traffic from billions of users. The system collects security-relevant information from production HTTP traffic at the reverse proxy layer, utilizing novel concepts such as synthetic signals augmented with additional risk information to provide a holistic view of the security posture of individual services and the broader application ecosystem. This approach to measurability has enabled large-scale security improvements to our services, including prioritized rollouts of security enhancements and the implementation of automated regression monitoring. Furthermore, it has proven valuable for security research and prioritization of defensive work. Security Signals addresses shortcomings of prior web measurability proposals by tracking a comprehensive set of security properties relevant to web applications, and by extracting insights from collected data for use by both security experts and non-experts. We believe the lessons learned from the implementation and use of Security Signals offer valuable insights for practitioners responsible for web service security, potentially inspiring new approaches to web security measurability.

View More Papers

The Skeleton Keys: A Large Scale Analysis of Credential...

Yizhe Shi (Fudan University), Zhemin Yang (Fudan University), Kangwei Zhong (Fudan University), Guangliang Yang (Fudan University), Yifan Yang (Fudan University), Xiaohan Zhang (Fudan University), Min Yang (Fudan University)

Read More

MineShark: Cryptomining Traffic Detection at Scale

Shaoke Xi (Zhejiang University), Tianyi Fu (Zhejiang University), Kai Bu (Zhejiang University), Chunling Yang (Zhejiang University), Zhihua Chang (Zhejiang University), Wenzhi Chen (Zhejiang University), Zhou Ma (Zhejiang University), Chongjie Chen (HANG ZHOU CITY BRAIN CO., LTD), Yongsheng Shen (HANG ZHOU CITY BRAIN CO., LTD), Kui Ren (Zhejiang University)

Read More

SCAMMAGNIFIER: Piercing the Veil of Fraudulent Shopping Website Campaigns

Marzieh Bitaab (Arizona State University), Alireza Karimi (Arizona State University), Zhuoer Lyu (Arizona State University), Adam Oest (Amazon), Dhruv Kuchhal (Amazon), Muhammad Saad (X Corp.), Gail-Joon Ahn (Arizona State University), Ruoyu Wang (Arizona State University), Tiffany Bao (Arizona State University), Yan Shoshitaishvili (Arizona State University), Adam Doupé (Arizona State University)

Read More