CVE-2025-68358 : Detail

CVE-2025-68358

5.5
/
Medium
0.01%V4
Local
2025-12-24
10h32 +00:00
2026-02-19
15h39 +00:00
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CVE Descriptions

btrfs: fix racy bitfield write in btrfs_clear_space_info_full()

In the Linux kernel, the following vulnerability has been resolved: btrfs: fix racy bitfield write in btrfs_clear_space_info_full() From the memory-barriers.txt document regarding memory barrier ordering guarantees: (*) These guarantees do not apply to bitfields, because compilers often generate code to modify these using non-atomic read-modify-write sequences. Do not attempt to use bitfields to synchronize parallel algorithms. (*) Even in cases where bitfields are protected by locks, all fields in a given bitfield must be protected by one lock. If two fields in a given bitfield are protected by different locks, the compiler's non-atomic read-modify-write sequences can cause an update to one field to corrupt the value of an adjacent field. btrfs_space_info has a bitfield sharing an underlying word consisting of the fields full, chunk_alloc, and flush: struct btrfs_space_info { struct btrfs_fs_info * fs_info; /* 0 8 */ struct btrfs_space_info * parent; /* 8 8 */ ... int clamp; /* 172 4 */ unsigned int full:1; /* 176: 0 4 */ unsigned int chunk_alloc:1; /* 176: 1 4 */ unsigned int flush:1; /* 176: 2 4 */ ... Therefore, to be safe from parallel read-modify-writes losing a write to one of the bitfield members protected by a lock, all writes to all the bitfields must use the lock. They almost universally do, except for btrfs_clear_space_info_full() which iterates over the space_infos and writes out found->full = 0 without a lock. Imagine that we have one thread completing a transaction in which we finished deleting a block_group and are thus calling btrfs_clear_space_info_full() while simultaneously the data reclaim ticket infrastructure is running do_async_reclaim_data_space(): T1 T2 btrfs_commit_transaction btrfs_clear_space_info_full data_sinfo->full = 0 READ: full:0, chunk_alloc:0, flush:1 do_async_reclaim_data_space(data_sinfo) spin_lock(&space_info->lock); if(list_empty(tickets)) space_info->flush = 0; READ: full: 0, chunk_alloc:0, flush:1 MOD/WRITE: full: 0, chunk_alloc:0, flush:0 spin_unlock(&space_info->lock); return; MOD/WRITE: full:0, chunk_alloc:0, flush:1 and now data_sinfo->flush is 1 but the reclaim worker has exited. This breaks the invariant that flush is 0 iff there is no work queued or running. Once this invariant is violated, future allocations that go into __reserve_bytes() will add tickets to space_info->tickets but will see space_info->flush is set to 1 and not queue the work. After this, they will block forever on the resulting ticket, as it is now impossible to kick the worker again. I also confirmed by looking at the assembly of the affected kernel that it is doing RMW operations. For example, to set the flush (3rd) bit to 0, the assembly is: andb $0xfb,0x60(%rbx) and similarly for setting the full (1st) bit to 0: andb $0xfe,-0x20(%rax) So I think this is really a bug on practical systems. I have observed a number of systems in this exact state, but am currently unable to reproduce it. Rather than leaving this footgun lying around for the future, take advantage of the fact that there is room in the struct anyway, and that it is already quite large and simply change the three bitfield members to bools. This avoids writes to space_info->full having any effect on ---truncated---

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE Other No informations.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 5.5 MEDIUM CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Base: Exploitabilty Metrics

The Exploitability metrics reflect the characteristics of the thing that is vulnerable, which we refer to formally as the vulnerable component.

Attack Vector

This metric reflects the context by which vulnerability exploitation is possible.

Local

The vulnerable component is not bound to the network stack and the attacker’s path is via read/write/execute capabilities.

Attack Complexity

This metric describes the conditions beyond the attacker’s control that must exist in order to exploit the vulnerability.

Low

Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success when attacking the vulnerable component.

Privileges Required

This metric describes the level of privileges an attacker must possess before successfully exploiting the vulnerability.

Low

The attacker requires privileges that provide basic user capabilities that could normally affect only settings and files owned by a user. Alternatively, an attacker with Low privileges has the ability to access only non-sensitive resources.

User Interaction

This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable component.

None

The vulnerable system can be exploited without interaction from any user.

Base: Scope Metrics

The Scope metric captures whether a vulnerability in one vulnerable component impacts resources in components beyond its security scope.

Scope

Formally, a security authority is a mechanism (e.g., an application, an operating system, firmware, a sandbox environment) that defines and enforces access control in terms of how certain subjects/actors (e.g., human users, processes) can access certain restricted objects/resources (e.g., files, CPU, memory) in a controlled manner. All the subjects and objects under the jurisdiction of a single security authority are considered to be under one security scope. If a vulnerability in a vulnerable component can affect a component which is in a different security scope than the vulnerable component, a Scope change occurs. Intuitively, whenever the impact of a vulnerability breaches a security/trust boundary and impacts components outside the security scope in which vulnerable component resides, a Scope change occurs.

Unchanged

An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.

Base: Impact Metrics

The Impact metrics capture the effects of a successfully exploited vulnerability on the component that suffers the worst outcome that is most directly and predictably associated with the attack. Analysts should constrain impacts to a reasonable, final outcome which they are confident an attacker is able to achieve.

Confidentiality Impact

This metric measures the impact to the confidentiality of the information resources managed by a software component due to a successfully exploited vulnerability.

None

There is no loss of confidentiality within the impacted component.

Integrity Impact

This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information.

None

There is no loss of integrity within the impacted component.

Availability Impact

This metric measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability.

High

There is a total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).

Temporal Metrics

The Temporal metrics measure the current state of exploit techniques or code availability, the existence of any patches or workarounds, or the confidence in the description of a vulnerability.

Environmental Metrics

These metrics enable the analyst to customize the CVSS score depending on the importance of the affected IT asset to a user’s organization, measured in terms of Confidentiality, Integrity, and Availability.

nvd@nist.gov

EPSS

EPSS is a scoring model that predicts the likelihood of a vulnerability being exploited.

EPSS Score

The EPSS model produces a probability score between 0 and 1 (0 and 100%). The higher the score, the greater the probability that a vulnerability will be exploited.

EPSS Percentile

The percentile is used to rank CVE according to their EPSS score. For example, a CVE in the 95th percentile according to its EPSS score is more likely to be exploited than 95% of other CVE. Thus, the percentile is used to compare the EPSS score of a CVE with that of other CVE.

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 4.8 To (excluding) 5.15.201

Linux>>Linux_kernel >> Version From (including) 5.16 To (excluding) 6.1.164

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.124

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.12.68

Linux>>Linux_kernel >> Version From (including) 6.13 To (excluding) 6.17.13

Linux>>Linux_kernel >> Version From (including) 6.18 To (excluding) 6.18.2

References