Orchestration or Automation: Authentication Flaw Detection in Android Apps

Passwords are pervasively used to authenticate users' identities in mobile apps. To secure passwords against attacks, protection is applied to the password authentication protocol (PAP). The implementation of the protection scheme becomes an important factor in protecting PAP against attacks. We focus on two basic protection in Android, i.e., SSL/TLS-based PAP and timestamp-based PAP. Previously, we proposed an automated tool, GLACIATE, to detect authentication flaws. We were curious whether orchestration (i.e., involving manual-effort) works better than automation. To answer this question, we propose an orchestrated approach, AUTH-EYE in this paper and compare its effectiveness GLACIATE. We study requirements for correct implementation of PAP and then apply GLACIATE to identify protection enhancements automatically. Through dependency analysis, GLACIATE matches the implementations against the abstracted flaws to recognise defective apps. To evaluate AUTH-EYE, we collected 1,200 Android apps from Google Play. We compared AUTH-EYE with the automation tool, GLACIATE, and two other orchestration tools, MalloDroid and SMV-Hunter. The results demonstrated that orchestration tools detect flaws more precisely although F1 of GLACIATE is higher than AUTH-EYE. Further analysis of the results reveals that highly popular apps and e-commerce apps are not more secure than other apps.