Solana has emerged as a major blockchain platform providing high throughput and low fees. Like other blockchains, Solana can be attacked via so-called ''Sandwiching'' attacks, where an attacker observes a pending transaction, quickly buys the target cryptocurrency, lets the transaction go through, and then immediately sells it for a profit, skimming that profit from the user who submitted the transaction. While such attacks have been observed by users, they remain underexplored in academic literature due to technical difficulties studying Solana at scale.

Bluetooth-based item trackers have sparked apprehension over their potential misuse in harmful stalking and privacy violations. In response, manufacturers have implemented safety alerts to notify victims of extended tracking by unknown item trackers. In this study, we specifically investigate the anti-stalking mechanism of Apple's AirTag. We identify and analyze potential triggers of safety alerts that have not been examined in previous research, such as the local time, the victim's device model, AirTag's battery life, and the distance between the AirTag and the victim's device. Furthermore, we demonstrate a novel possibility of developing a stealthy cloned AirTag capable of tracking victims directly on the Find My app while circumventing safety alerts on the victim’s device. Our experiments demonstrate that, despite regular updates to the public key and MAC address, our cloned AirTag can provide real-time location updates even with a four months old key, thereby highlighting the challenges in designing a robust anti-stalking framework. Furthermore, we propose practical solutions to mitigate stalking risks from cloned AirTags and enhance the existing anti-stalking safeguards for AirTags. These suggestions seek to provide a foundation for similar Bluetooth-based item trackers to improve their anti-stalking protections while ensuring optimal tracking efficiency. We conducted rigorous experiments to validate our findings, ensuring their accuracy and reliability. Our evaluation highlights that safety alerts take over 8 hours to appear during the day and are more prompt during the night, particularly after 11 pm.

Online services such as Facebook and Google serve as a popular way by which users today are exposed to products, services, viewpoints, and opportunities. These services implement advertising platforms that enable precise targeting of platform users, and they optimize the delivery of ads to the subset of the targeted users predicted to be most receptive. Unfortunately, recent work has shown that such delivery can---often without the advertisers' knowledge---show ads to biased sets of users based only on the content of the ad. Such concerns are particularly acute for ads that contain pictures of people (e.g., job ads showing workers), as advertisers often select images to carefully convey their goals and values (e.g., to promote diversity in hiring). However, it remains unknown how ad delivery algorithms react to---and make delivery decisions based on---demographic features of people represented in such ad images. Here, we examine how one major advertising platform (Facebook) delivers ads that include pictures of people of varying ages, genders, and races. We develop techniques to isolate the effect of these demographic variables, using a combination of both stock photos and realistic synthetically-generated images of people. We find dramatic skews in who ultimately sees ads solely based on the demographics of the person in the ad. Ads are often delivered disproportionately to users similar to those pictured: images of Black people are shown more to Black users, and the age of the person pictured correlates positively with the age of the users to whom it is shown. But, this is not universal, and more complex effects emerge: older women see more images of children, while images of younger women are shown disproportionately to men aged 55 and older. These findings bring up novel technical, legal, and policy questions and underscore the need to better understand how platforms deliver ads today.