Security readout for executives and security teams
Plain-English summary
Radar COVID could reveal that a user tested positive because only positive users uploaded diagnosis keys to the backend. A network operator or other on-path observer could spot that traffic pattern, and possibly link it to a real person using subscriber or other identifying data.
Executive priority
Treat as high priority if operating or assessing Radar COVID. The issue concerns sensitive health-status confidentiality, not system takeover, and the documented fix is version-based plus dummy traffic behavior.
Technical view
This is a CWE-200 traffic-analysis privacy flaw in Radar COVID. Affected iOS, Android, and backend versions exposed COVID-positive status through TEK-upload connections made only by positives. Mitigation added dummy backend traffic from all users to obscure upload status.
Likely exposure
Exposure is limited to Radar COVID deployments using iOS versions before 1.0.8, Android versions before 1.0.7, or backend before 1.1.2-RELEASE. The risk is highest where network providers, VPNs, enterprise networks, public Wi-Fi operators, or similar on-path parties can observe traffic metadata.
Exploitation context
The source bundle does not show CISA KEV listing or active exploitation. Exploitation requires on-path traffic visibility; de-anonymization additionally requires correlating Radar COVID traffic with subscriber records or other identifying flows.
Researcher notes
This is a metadata leakage issue, not a cryptographic break of TEKs. Practical privacy impact depends on observer position and access to re-identification data. The provided sources identify fixes but do not provide evidence of active exploitation.
Mitigation direction
- Upgrade iOS apps to version 1.0.8 or later; prefer 1.1.0 where applicable.
- Upgrade Android apps to version 1.0.7 or later; prefer 1.1.0 where applicable.
- Upgrade backend to 1.1.2-RELEASE or later.
- Verify dummy traffic is generated for all users regardless of diagnosis status.
- Check the GitHub Security Advisory for any deployment-specific guidance.
Validation and detection
- Inventory mobile app and backend versions against the affected ranges.
- Confirm production clients no longer upload only when users are COVID-positive.
- Review backend telemetry for dummy traffic from non-positive users.
- Assess whether network logs retain metadata that could identify historical positive uploads.
- Document any residual privacy risk from retained traffic or subscriber correlation data.
Public sources used
Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.
Conservative CVE-to-ATT&CK context
These mappings and lookup hints may be relevant to the vulnerability behavior, CWE, affected product, or exposure path. Glexia-inferred context is not an official MITRE, ATT&CK, CWE, or CVE Program mapping.
ATT&CK lookup starting points
Use these exact CWE pages and searches to review the Glexia ATT&CK library from this CVE's weakness and description context.
CWE-200: Information exposure and cloud metadata lookup
Information exposure and SSRF weaknesses can make discovery, cloud metadata, and credential material review relevant. Open the exact CWE lookup page first, then review the ATT&CK searches from that MITRE weakness context. This is a Glexia lookup hint, not an official ATT&CK mapping.
Open ATT&CK lookupCVE-2020-26230 mapping review
Open the CVE-to-ATT&CK bridge for reviewed, inferred, or future official mappings tied to this CVE.
Open ATT&CK lookup- Severity
- High
- CVSS
- 7.4 (3.1)
- Known Exploited
- No
- Published
Vector: CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
CNA and ADP enrichment extracted from CVE v5
These fields come from the CVE record and ADP containers, not from Glexia's Take. They preserve time-varying source decisions such as CISA SSVC, KEV status, CVSS metrics, and provider references.
CVSS vector scores
1 official scoreWe collect every scored CVSS vector available in the official CNA and ADP containers. When more than one version is present, the table keeps the source vectors side by side instead of collapsing them into the highest score.
CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N2.84Primary CVE scoreVulnerability scoring details
Base CVSS 3.1 score
7.4HighVector: CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Source materials
- CVE List V5 sourceCVE List V5
- https://github.com/RadarCOVID/radar-covid-backend-dp3t-server/security/advisories/GHSA-w7jx-37x3-w2jxCVE reference · x_refsource_CONFIRM
- https://github.com/RadarCOVID/radar-covid-android/commit/09d00e5ede801ca400d45c7feda5a99c34e4176cCVE reference · x_refsource_MISC
- https://github.com/RadarCOVID/radar-covid-android/commit/53252773ffa81e116deabcbbea3bac96872b9888CVE reference · x_refsource_MISC
- https://github.com/RadarCOVID/radar-covid-android/commit/7fdc7debeb8a37faa77b53d9f9a1b4bbcff445ceCVE reference · x_refsource_MISC
- https://github.com/RadarCOVID/radar-covid-android/commit/8e5d14ec60e0c1847a4733556cf34d232c27102cCVE reference · x_refsource_MISC
- https://github.com/RadarCOVID/radar-covid-android/commit/91dcfff6252055637bc9ee0c46b8f003d64a16b9CVE reference · x_refsource_MISC
- https://github.com/RadarCOVID/radar-covid-android/commit/9627f4d69705bca68e550eefd3df1b9abe90b215CVE reference · x_refsource_MISC
- https://github.com/RadarCOVID/radar-covid-android/commit/ea0c4cc837f72f58e2b5df1ecf0899743ec3cdf8CVE reference · x_refsource_MISC
- https://github.com/RadarCOVID/radar-covid-backend-dp3t-server/commit/6d30c92cc8fcbde3ded7e9518853ef278080344dCVE reference · x_refsource_MISC
- https://github.com/RadarCOVID/radar-covid-backend-dp3t-server/commit/c37f81636250892670750e3989139fd76d4beffeCVE reference · x_refsource_MISC
- https://github.com/RadarCOVID/radar-covid-ios/commit/2d1505d4858642995ea09f02f23c953acaa65195CVE reference · x_refsource_MISC
- https://github.com/DP-3T/documents/blob/master/DP3T%20-%20Best%20Practices%20for%20Operation%20Security%20in%20Proximity%20Tracing.pdfCVE reference · x_refsource_MISC
Products and packages named in the record
CWE details
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Exposure of Sensitive Information to an Unauthorized Actor
Exposure of Sensitive Information to an Unauthorized Actor represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.
