2012 · 110 citations · 11 references
ComputingComputer ScienceCybersecurityApplication SecurityComputer SecurityWeb SecurityAdversary TechniquesBrowser SecurityUser Behavior AnalysisWeb Application SecurityWeb Application VulnerabilitiesWeb AuthenticationBrowser Enforcement MechanismsClickjackingContextIntegrityRedirection-based Clickjacking DefenseUi Authentication Challenges
Clickjacking attacks are an emerging threat on the web. The study designs new clickjacking attack variants to show existing defenses are insufficient and proposes the InContext defense that enforces context integrity of sensitive UI elements. The authors design attack variants using existing techniques, analyze the root cause of clickjacking, propose the InContext defense that enforces context integrity, and evaluate its effectiveness with 2064 MTurk participants. The attacks can severely damage users by compromising webcams, email, and anonymity, achieving success rates of 43% to 98%, while the InContext defense proves highly effective against such attacks.
Clickjacking attacks are an emerging threat on the web. In this paper, we design new clickjacking attack variants using existing techniques and demonstrate that existing clickjacking defenses are insufficient. Our attacks show that clickjacking can cause severe damages, including compromising a user's private webcam, email or other private data, and web surfing anonymity. We observe the root cause of clickjacking is that an attacker application presents a sensitive UI element of a target application out of context to a user (such as hiding the sensitive UI by making it transparent), and hence the user is tricked to act out of context. To address this root cause, we propose a new defense, InContext, in which web sites (or applications) mark UI elements that are sensitive, and browsers (or OSes) enforce context integrity of user actions on these sensitive UI elements, ensuring that a user sees everything she should see before her action and that the timing of the action corresponds to her intent. We have conducted user studies on Amazon Mechanical Turk with 2064 participants to evaluate the effectiveness of our attacks and our defense. We show that our attacks have success rates ranging from 43% to 98%, and our InContext defense can be very effective against the clickjacking attacks in which the use of clickjacking is more effective than social engineering.
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