CVE-2020-26230Deanonymization of COVID-19 positive users of Radar COVID

Official description

Radar COVID is the official COVID-19 exposure notification app for Spain. In affected versions of Radar COVID, identification and de-anonymization of COVID-19 positive users that upload Radar COVID TEKs to the Radar COVID server is possible. This vulnerability enables the identification and de-anonymization of COVID-19 positive users when using Radar COVID. The vulnerability is caused by the fact that Radar COVID connections to the server (uploading of TEKs to the backend) are only made by COVID-19 positives. Therefore, any on-path observer with the ability to monitor traffic between the app and the server can identify which users had a positive test. Such an adversary can be the mobile network operator (MNO) if the connection is done through a mobile network, the Internet Service Provider (ISP) if the connection is done through the Internet (e.g., a home network), a VPN provider used by the user, the local network operator in the case of enterprise networks, or any eavesdropper with access to the same network (WiFi or Ethernet) as the user as could be the case of public WiFi hotspots deployed at shopping centers, airports, hotels, and coffee shops. The attacker may also de-anonymize the user. For this additional stage to succeed, the adversary needs to correlate Radar COVID traffic to other identifiable information from the victim. This could be achieved by associating the connection to a contract with the name of the victim or by associating Radar COVID traffic to other user-generated flows containing identifiers in the clear (e.g., HTTP cookies or other mobile flows sending unique identifiers like the IMEI or the AAID without encryption). The former can be executed, for instance, by the Internet Service Provider or the MNO. The latter can be executed by any on-path adversary, such as the network provider or even the cloud provider that hosts more than one service accessed by the victim. The farther the adversary is either from the victim (the client) or the end-point (the server), the less likely it may be that the adversary has access to re-identification information. The vulnerability has been mitigated with the injection of dummy traffic from the application to the backend. Dummy traffic is generated by all users independently of whether they are COVID-19 positive or not. The issue was fixed in iOS in version 1.0.8 (uniform distribution), 1.1.0 (exponential distribution), Android in version 1.0.7 (uniform distribution), 1.1.0 (exponential distribution), Backend in version 1.1.2-RELEASE. For more information see the referenced GitHub Security Advisory.

Affected products (as reported)

References

• https://github.com/RadarCOVID/radar-covid-backend-dp3t-server/security/advisories/GHSA-w7jx-37x3-w2jx x_refsource_CONFIRM
• https://github.com/RadarCOVID/radar-covid-android/commit/09d00e5ede801ca400d45c7feda5a99c34e4176c x_refsource_MISC
• https://github.com/RadarCOVID/radar-covid-android/commit/53252773ffa81e116deabcbbea3bac96872b9888 x_refsource_MISC
• https://github.com/RadarCOVID/radar-covid-android/commit/7fdc7debeb8a37faa77b53d9f9a1b4bbcff445ce x_refsource_MISC
• https://github.com/RadarCOVID/radar-covid-android/commit/8e5d14ec60e0c1847a4733556cf34d232c27102c x_refsource_MISC
• https://github.com/RadarCOVID/radar-covid-android/commit/91dcfff6252055637bc9ee0c46b8f003d64a16b9 x_refsource_MISC
• https://github.com/RadarCOVID/radar-covid-android/commit/9627f4d69705bca68e550eefd3df1b9abe90b215 x_refsource_MISC
• https://github.com/RadarCOVID/radar-covid-android/commit/ea0c4cc837f72f58e2b5df1ecf0899743ec3cdf8 x_refsource_MISC
• https://github.com/RadarCOVID/radar-covid-backend-dp3t-server/commit/6d30c92cc8fcbde3ded7e9518853ef278080344d x_refsource_MISC
• https://github.com/RadarCOVID/radar-covid-backend-dp3t-server/commit/c37f81636250892670750e3989139fd76d4beffe x_refsource_MISC
• https://github.com/RadarCOVID/radar-covid-ios/commit/2d1505d4858642995ea09f02f23c953acaa65195 x_refsource_MISC
• https://github.com/DP-3T/documents/blob/master/DP3T%20-%20Best%20Practices%20for%20Operation%20Security%20in%20Proximity%20Tracing.pdf x_refsource_MISC