When informed, GrubHub revised its code and had Crashlytics delete all the associated data that contained passwords.
Part 2: mSpy
The group extracts data from app communications, and tries to determine what parts of it are PII. This is both harder and easier than it might sound. But the team also applies machine learning, allowing it to identify PII more broadly, even when it appears without using any standard structure format, or shows up in surprising places. The ReCon project publishes some data derived from a few hundred early users, listing apps, the kind of data they passed, a severity score, whether a developer was notified, and when misbehavior was fixed if indeed it was.
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For instance, a user can block all examples of a given kind of PII, or block all location data sent from a given app. However, because some apps fail without location coordinates, the team is looking into coarsening GPS information instead of blocking it entirely.
Of course, examining a flow of data from users itself raises massive privacy red flags, which is part of the evolution of ReCon. At the moment, the tool measures and reports what apps are doing, though it could offer blocking controls in the future. Fortunately, the two projects have both a friendly competition and plans for collaboration.
The efforts will likely remain separate, but incorporate aspects or associate data to get a bigger picture about app behavior. And the ReCon team would like to develop software for a network appliance, a Raspberry Pi that would act as a sniffer or proxy or firmware for a network router, to let someone see the interactions across all network devices—especially Internet of Things equipment, which have all sorts of privacy and security issues of their own. Both ReCon and Lumen are working on obtaining more funding to improve the projects and make them viable for a large-scale consumer rollout.
As informative as RecCon and Lumen are, what apps are doing with our data remains an impenetrable subject.
Many privacy experts and researchers point to the use of dense legal documents to define disclosure without those being linked to verifiable discrete elements that software or humans could check. Gray also points out unintended consequences, where the app maker and a third-party ad tech network could both act within reasonable terms, but an unrelated party could violate privacy.
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She cites a situation in May in which a company claimed to be able to use advertising targeting to find women in the vicinity of Planned Parenthood clinics and serve them ads about anti-abortion religious counseling services. That action is possibly legal, but certainly not desirable by the users, ad networks, or publishers involved. The same conflicts that have driven the ad-blocking wars make it unlikely that the business models behind mobile apps will provide more transparency, making the research behind ReCon and Lumen all the more important.
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