Johnathan Wilkes, John Anny (Palo Alto Networks)

By embracing automation, organizations can transcend manual limitations to reduce mean time to response and address exposures consistently across their cybersecurity infrastructure. In the dynamic realm of cybersecurity, swiftly addressing externally discovered exposures is paramount, as each represents a ticking time bomb. A paradigm shift towards automation to enhance speed, efficiency, and uniformity in the remediation process is needed to answer the question, "You found the exposure, now what?". Traditional manual approaches are not only time-consuming but also prone to human error, underscoring the need for a comprehensive, automated solution. Acknowledging the diversity of exposures and the array of security tools, we will propose how to remediate common external exposures, such as open ports and dangling domains. The transformative nature of this shift is crucial, particularly in the context of multiple cloud platforms with distinct data enrichment and remediation capabilities.

View More Papers

WIP: Towards Practical LiDAR Spoofing Attack against Vehicles Driving...

Ryo Suzuki (Keio University), Takami Sato (University of California, Irvine), Yuki Hayakawa, Kazuma Ikeda, Ozora Sako, Rokuto Nagata (Keio University), Qi Alfred Chen (University of California, Irvine), Kentaro Yoshioka (Keio University)

Read More

AAKA: An Anti-Tracking Cellular Authentication Scheme Leveraging Anonymous Credentials

Hexuan Yu (Virginia Polytechnic Institute and State University), Changlai Du (Virginia Polytechnic Institute and State University), Yang Xiao (University of Kentucky), Angelos Keromytis (Georgia Institute of Technology), Chonggang Wang (InterDigital), Robert Gazda (InterDigital), Y. Thomas Hou (Virginia Polytechnic Institute and State University), Wenjing Lou (Virginia Polytechnic Institute and State University)

Read More

Towards Precise Reporting of Cryptographic Misuses

Yikang Chen (The Chinese University of Hong Kong), Yibo Liu (Arizona State University), Ka Lok Wu (The Chinese University of Hong Kong), Duc V Le (Visa Research), Sze Yiu Chau (The Chinese University of Hong Kong)

Read More