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Websites delivered iOS malware to thousands of visitors in the biggest iPhone hack ever. There’s no telling who was infected—or who was behind it.
L'actualité du Logiciel Libre et de Linux, sur un site francophone contributif géré par une équipe bénévole par et pour des libristes enthousiastes
Context
The idea that FaceApp is somehow exceptionally dangerous threatens to obscure the real point: All apps deserve this level of scrutiny.
Malicious apps from a campaign called "Agent Smith" have been downloaded to 25 million Android devices, according to new research by cyber-security firm Check Point.
New study reveals scary, sneaky tactics
Security researchers say they have uncovered a massive espionage campaign involving the theft of call records from hacked cell network providers to conduct targeted surveillance on individuals of interest. The hackers have systematically broken in to more than 10 cell networks around the world to d…
It used a Shazam-like technology to identify soccer games
GrapheneOS is a security and privacy focused mobile OS with Android app compatibility.
Most phones that ship with Google’s Android operating system also come with a bunch of Google apps and services installed. But Android is open source software, so independent developers have been finding ways to de-Google Android for years. One of the more recent options comes from developer Gaël Duval and the /e/ Foundation. The /e/ …
Key points:
Seeing your favorite band live will probably cost you more in data than in dollars.
The privacy crisis Apple and Google need to fix—now
The tech giant records people’s locations worldwide. Now, investigators are using it to find suspects and witnesses near crimes, running the risk of snaring the innocent.
Malware that stole contacts, audio, location and more was under development for years.
Experts with whom we consulted confirmed New York Times reports on the Saudi capability to “collect vast amounts of previously inaccessible data from smartphones in the air without leaving a trace—including phone calls, texts, emails”—and confirmed that hacking was a key part of the Saudis’ “extensive surveillance efforts that ultimately led to the killing of [Washington Post] journalist Jamal Khashoggi.”
Objectives To investigate whether and how user data are shared by top rated medicines related mobile applications (apps) and to characterise privacy risks to app users, both clinicians and consumers.
Design Traffic, content, and network analysis.
Setting Top rated medicines related apps for the Android mobile platform available in the Medical store category of Google Play in the United Kingdom, United States, Canada, and Australia.
Participants 24 of 821 apps identified by an app store crawling program. Included apps pertained to medicines information, dispensing, administration, prescribing, or use, and were interactive.
Interventions Laboratory based traffic analysis of each app downloaded onto a smartphone, simulating real world use with four dummy scripts. The app’s baseline traffic related to 28 different types of user data was observed. To identify privacy leaks, one source of user data was modified and deviations in the resulting traffic observed.
Main outcome measures Identities and characterisation of entities directly receiving user data from sampled apps. Secondary content analysis of company websites and privacy policies identified data recipients’ main activities; network analysis characterised their data sharing relations.
Results 19/24 (79%) of sampled apps shared user data. 55 unique entities, owned by 46 parent companies, received or processed app user data, including developers and parent companies (first parties) and service providers (third parties). 18 (33%) provided infrastructure related services such as cloud services. 37 (67%) provided services related to the collection and analysis of user data, including analytics or advertising, suggesting heightened privacy risks. Network analysis revealed that first and third parties received a median of 3 (interquartile range 1-6, range 1-24) unique transmissions of user data. Third parties advertised the ability to share user data with 216 “fourth parties”; within this network (n=237), entities had access to a median of 3 (interquartile range 1-11, range 1-140) unique transmissions of user data. Several companies occupied central positions within the network with the ability to aggregate and re-identify user data.
Conclusions Sharing of user data is routine, yet far from transparent. Clinicians should be conscious of privacy risks in their own use of apps and, when recommending apps, explain the potential for loss of privacy as part of informed consent. Privacy regulation should emphasise the accountabilities of those who control and process user data. Developers should disclose all data sharing practices and allow users to choose precisely what data are shared and with whom.