Vulnerabilities > CVE-2020-26230 - Information Exposure vulnerability in Radarcovid Radar-Covid-Backend-Dp3T-Server and Radarcovid

047910
CVSS 2.6 - LOW
Attack vector
NETWORK
Attack complexity
HIGH
Privileges required
NONE
Confidentiality impact
PARTIAL
Integrity impact
NONE
Availability impact
NONE
network
high complexity
radarcovid
CWE-200
NVD
Published: 2020-11-13
Updated: 2021-02-04

Summary

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.

Vulnerable Configurations

Part Description Count
Application
Radarcovid
5

Common Weakness Enumeration (CWE)

Common Attack Pattern Enumeration and Classification (CAPEC)

  • Subverting Environment Variable Values
    The attacker directly or indirectly modifies environment variables used by or controlling the target software. The attacker's goal is to cause the target software to deviate from its expected operation in a manner that benefits the attacker.
  • Footprinting
    An attacker engages in probing and exploration activity to identify constituents and properties of the target. Footprinting is a general term to describe a variety of information gathering techniques, often used by attackers in preparation for some attack. It consists of using tools to learn as much as possible about the composition, configuration, and security mechanisms of the targeted application, system or network. Information that might be collected during a footprinting effort could include open ports, applications and their versions, network topology, and similar information. While footprinting is not intended to be damaging (although certain activities, such as network scans, can sometimes cause disruptions to vulnerable applications inadvertently) it may often pave the way for more damaging attacks.
  • Exploiting Trust in Client (aka Make the Client Invisible)
    An attack of this type exploits a programs' vulnerabilities in client/server communication channel authentication and data integrity. It leverages the implicit trust a server places in the client, or more importantly, that which the server believes is the client. An attacker executes this type of attack by placing themselves in the communication channel between client and server such that communication directly to the server is possible where the server believes it is communicating only with a valid client. There are numerous variations of this type of attack.
  • Browser Fingerprinting
    An attacker carefully crafts small snippets of Java Script to efficiently detect the type of browser the potential victim is using. Many web-based attacks need prior knowledge of the web browser including the version of browser to ensure successful exploitation of a vulnerability. Having this knowledge allows an attacker to target the victim with attacks that specifically exploit known or zero day weaknesses in the type and version of the browser used by the victim. Automating this process via Java Script as a part of the same delivery system used to exploit the browser is considered more efficient as the attacker can supply a browser fingerprinting method and integrate it with exploit code, all contained in Java Script and in response to the same web page request by the browser.
  • Session Credential Falsification through Prediction
    This attack targets predictable session ID in order to gain privileges. The attacker can predict the session ID used during a transaction to perform spoofing and session hijacking.

References