Cyber Resilience

CVE-2023-44385

High

Published: 19 October 2023

Published
19 October 2023
Modified
21 November 2024
KEV Added
Patch
CVSS Score v3.1 8.6 CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H
EPSS Score 0.0135 80.5th percentile
Risk Priority 18 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2023-44385 is a high-severity CSRF (CWE-352) vulnerability in Home-Assistant Home Assistant Companion. Its CVSS base score is 8.6 (High).

Operationally, ranked in the top 19.5% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.

EU & UK References

Vulnerability details

The Home Assistant Companion for iOS and macOS app up to version 2023.4 are vulnerable to Client-Side Request Forgery. Attackers may send malicious links/QRs to victims that, when visited, will make the victim to call arbitrary services in their Home…

more

Assistant installation. Combined with this security advisory, may result in full compromise and remote code execution (RCE). Version 2023.7 addresses this issue and all users are advised to upgrade. There are no known workarounds for this vulnerability. This issue is also tracked as GitHub Security Lab (GHSL) Vulnerability Report: GHSL-2023-161.

CWE(s)

Related Threats

No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.

Affected Assets

home-assistant
home assistant companion
≤ 2023.7 · ≤ 2023.7

Mitigating Controls

Likely Mitigating Controls AI

Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.

addresses: CWE-352

Awareness training educates users on avoiding untrusted links and actions that can be exploited via CSRF.

addresses: CWE-352

Requiring user re-entry of credentials for sensitive actions prevents automated forgery of requests without active user participation.

addresses: CWE-352

Security testing regimens explicitly include checks for missing or ineffective anti-CSRF protections in web applications.

addresses: CWE-352

Detects anomalous request patterns consistent with cross-site request forgery.

References