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.
CVE-2020-26230
This high-severity CVE scores 7.4 under NVD CVSS v3. EPSS exploit probability: 1.6%, top 26% of all CVEs by exploit prediction. GitHub Security Advisory data not yet ingested — confidence will rise once GHSA publishes (typical lag: hours to days for open-source ecosystem CVEs; never for infrastructure-only CVEs).
- High severity, but no confirmed exploitation yet
No vendor fix yet — apply a workaround or compensating control (WAF / firewall / segmentation) and watch for a patch.
- CVSS v3
- 7.4
- EG Score
- 7.4(medium)
- EG Risk
- 38(Track)EG Risk 38/100SSVC: Track
EG Risk is EchelonGraph's 0–100 priority score: it fuses intrinsic severity with real-world exploitation and automatability so you can rank equal-severity CVEs and fix the most dangerous first. Higher = act sooner. Distinct from the 0–10 EG Score (severity).
How it’s computedSeverity74% × 45%Exploitation2% × 40%Automatability30% × 15%Action: Routine — remediate on your standard cadence. - EPSS
- 74.0%
- KEV
- Not listed
Published
November 13, 2020
Last Modified
November 21, 2024
References (24)
- security-advisories@githubhttps://github.com/DP-3T/documents/blob/master/DP3T%20-%20Best%20Practices%20for%20Operation%20Security%20in%20Proximity%20Tracing.pdf
- security-advisories@githubhttps://github.com/RadarCOVID/radar-covid-android/commit/09d00e5ede801ca400d45c7feda5a99c34e4176c
- security-advisories@githubhttps://github.com/RadarCOVID/radar-covid-android/commit/53252773ffa81e116deabcbbea3bac96872b9888
- security-advisories@githubhttps://github.com/RadarCOVID/radar-covid-android/commit/7fdc7debeb8a37faa77b53d9f9a1b4bbcff445ce
- security-advisories@githubhttps://github.com/RadarCOVID/radar-covid-android/commit/8e5d14ec60e0c1847a4733556cf34d232c27102c
- security-advisories@githubhttps://github.com/RadarCOVID/radar-covid-android/commit/91dcfff6252055637bc9ee0c46b8f003d64a16b9
- security-advisories@githubhttps://github.com/RadarCOVID/radar-covid-android/commit/9627f4d69705bca68e550eefd3df1b9abe90b215
- security-advisories@githubhttps://github.com/RadarCOVID/radar-covid-android/commit/ea0c4cc837f72f58e2b5df1ecf0899743ec3cdf8
- security-advisories@githubhttps://github.com/RadarCOVID/radar-covid-backend-dp3t-server/commit/6d30c92cc8fcbde3ded7e9518853ef278080344d
- security-advisories@githubhttps://github.com/RadarCOVID/radar-covid-backend-dp3t-server/commit/c37f81636250892670750e3989139fd76d4beffe
- security-advisories@githubhttps://github.com/RadarCOVID/radar-covid-backend-dp3t-server/security/advisories/GHSA-w7jx-37x3-w2jx
- security-advisories@githubhttps://github.com/RadarCOVID/radar-covid-ios/commit/2d1505d4858642995ea09f02f23c953acaa65195
- af854a3a-2127-422b-91ae-364da2661108https://github.com/DP-3T/documents/blob/master/DP3T%20-%20Best%20Practices%20for%20Operation%20Security%20in%20Proximity%20Tracing.pdf
- af854a3a-2127-422b-91ae-364da2661108https://github.com/RadarCOVID/radar-covid-android/commit/09d00e5ede801ca400d45c7feda5a99c34e4176c
- af854a3a-2127-422b-91ae-364da2661108https://github.com/RadarCOVID/radar-covid-android/commit/53252773ffa81e116deabcbbea3bac96872b9888
Weakness Classification(1)
MITRE Common Weakness Enumeration — the root-cause categories this CVE belongs to.
Data Freshness Timeline
(refreshed 14× in last 7d / 43× in last 30d)
Each row is a source pipeline that fetched or updated this CVE on that date, with what changed. For example, "NVD update" means NVD published or revised its analysis for this CVE; "MITRE cvelistV5" means we ingested or refreshed it from the CNA feed. Most recent first.
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Frequently asked(5)
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