CVE-2023-53777

Dec. 9, 2025, 6:37 p.m.

None
No Score

Description

In the Linux kernel, the following vulnerability has been resolved: erofs: kill hooked chains to avoid loops on deduplicated compressed images After heavily stressing EROFS with several images which include a hand-crafted image of repeated patterns for more than 46 days, I found two chains could be linked with each other almost simultaneously and form a loop so that the entire loop won't be submitted. As a consequence, the corresponding file pages will remain locked forever. It can be _only_ observed on data-deduplicated compressed images. For example, consider two chains with five pclusters in total: Chain 1: 2->3->4->5 -- The tail pcluster is 5; Chain 2: 5->1->2 -- The tail pcluster is 2. Chain 2 could link to Chain 1 with pcluster 5; and Chain 1 could link to Chain 2 at the same time with pcluster 2. Since hooked chains are all linked locklessly now, I have no idea how to simply avoid the race. Instead, let's avoid hooked chains completely until I could work out a proper way to fix this and end users finally tell us that it's needed to add it back. Actually, this optimization can be found with multi-threaded workloads (especially even more often on deduplicated compressed images), yet I'm not sure about the overall system impacts of not having this compared with implementation complexity.

Product(s) Impacted

Vendor Product Versions
Linux
  • Kernel
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a linux kernel / / / / / / / /

Timeline

Published: Dec. 9, 2025, 1:16 a.m.
Last Modified: Dec. 9, 2025, 6:37 p.m.

Status : Awaiting Analysis

CVE has been recently published to the CVE List and has been received by the NVD.

More info

Source

416baaa9-dc9f-4396-8d5f-8c081fb06d67

*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.