CVE Vulnerabilities

CVE-2020-26230

Exposure of Sensitive Information to an Unauthorized Actor

Published: Nov 13, 2020 | Modified: Feb 04, 2021
CVSS 3.x
5.3
MEDIUM
Source:
NVD
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:N/A:N
CVSS 2.x
2.6 LOW
AV:N/AC:H/Au:N/C:P/I:N/A:N
RedHat/V2
RedHat/V3
Ubuntu

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.

Weakness

The product exposes sensitive information to an actor that is not explicitly authorized to have access to that information.

Affected Software

Name Vendor Start Version End Version
Radar-covid-backend-dp3t-server Radarcovid * 1.1.2 (excluding)
Radarcovid Radarcovid * 1.0.7 (excluding)
Radarcovid Radarcovid * 1.0.8 (excluding)
Radarcovid Radarcovid * 1.1.0 (excluding)

Extended Description

There are many different kinds of mistakes that introduce information exposures. The severity of the error can range widely, depending on the context in which the product operates, the type of sensitive information that is revealed, and the benefits it may provide to an attacker. Some kinds of sensitive information include:

Information might be sensitive to different parties, each of which may have their own expectations for whether the information should be protected. These parties include:

Information exposures can occur in different ways:

It is common practice to describe any loss of confidentiality as an “information exposure,” but this can lead to overuse of CWE-200 in CWE mapping. From the CWE perspective, loss of confidentiality is a technical impact that can arise from dozens of different weaknesses, such as insecure file permissions or out-of-bounds read. CWE-200 and its lower-level descendants are intended to cover the mistakes that occur in behaviors that explicitly manage, store, transfer, or cleanse sensitive information.

Potential Mitigations

  • Compartmentalize the system to have “safe” areas where trust boundaries can be unambiguously drawn. Do not allow sensitive data to go outside of the trust boundary and always be careful when interfacing with a compartment outside of the safe area.
  • Ensure that appropriate compartmentalization is built into the system design, and the compartmentalization allows for and reinforces privilege separation functionality. Architects and designers should rely on the principle of least privilege to decide the appropriate time to use privileges and the time to drop privileges.

References