CVE-2024-45818
Dec. 31, 2024, 7:15 p.m.
6.5
Medium
Description
The hypervisor contains code to accelerate VGA memory accesses for HVM
guests, when the (virtual) VGA is in "standard" mode. Locking involved
there has an unusual discipline, leaving a lock acquired past the
return from the function that acquired it. This behavior results in a
problem when emulating an instruction with two memory accesses, both of
which touch VGA memory (plus some further constraints which aren't
relevant here). When emulating the 2nd access, the lock that is already
being held would be attempted to be re-acquired, resulting in a
deadlock.
This deadlock was already found when the code was first introduced, but
was analysed incorrectly and the fix was incomplete. Analysis in light
of the new finding cannot find a way to make the existing locking
discipline work.
In staging, this logic has all been removed because it was discovered
to be accidentally disabled since Xen 4.7. Therefore, we are fixing the
locking problem by backporting the removal of most of the feature. Note
that even with the feature disabled, the lock would still be acquired
for any accesses to the VGA MMIO region.
Product(s) Impacted
| Product | Versions |
|---|---|
| Xen Hypervisor |
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-667
Improper Locking
The product does not properly acquire or release a lock on a resource, leading to unexpected resource state changes and behaviors.
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: LOCAL
- Attack Complexity: LOW
- Privileges Required: LOW
- Scope: CHANGED
- Confidentiality Impact: HIGH
- Integrity Impact: NONE
- Availability Impact: NONE
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N
Timeline
Published: Dec. 19, 2024, 12:15 p.m.
Last Modified: Dec. 31, 2024, 7:15 p.m.
Last Modified: Dec. 31, 2024, 7:15 p.m.
Status : Awaiting Analysis
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
security@xen.org
*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.