CVE-2026-45934 : Detail

CVE-2026-45934

5.5
/
Medium
0.02%V4
Local
2026-05-27
14h17 +00:00
2026-06-24
17h11 +00:00
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CVE Descriptions

In the Linux kernel, the following vulnerability has been resolved: btrfs: fix EEXIST abort due to non-consecutive gaps in chunk allocation I have been observing a number of systems aborting at insert_dev_extents() in btrfs_create_pending_block_groups(). The following is a sample stack trace of such an abort coming from forced chunk allocation (typically behind CONFIG_BTRFS_EXPERIMENTAL) but this can theoretically happen to any DUP chunk allocation. [81.801] ------------[ cut here ]------------ [81.801] BTRFS: Transaction aborted (error -17) [81.801] WARNING: fs/btrfs/block-group.c:2876 at btrfs_create_pending_block_groups+0x721/0x770 [btrfs], CPU#1: bash/319 [81.802] Modules linked in: virtio_net btrfs xor zstd_compress raid6_pq null_blk [81.803] CPU: 1 UID: 0 PID: 319 Comm: bash Kdump: loaded Not tainted 6.19.0-rc6+ #319 NONE [81.803] Hardware name: QEMU Standard PC (i440FX + PIIX, 1996), BIOS Arch Linux 1.17.0-2-2 04/01/2014 [81.804] RIP: 0010:btrfs_create_pending_block_groups+0x723/0x770 [btrfs] [81.806] RSP: 0018:ffffa36241a6bce8 EFLAGS: 00010282 [81.806] RAX: 000000000000000d RBX: ffff8e699921e400 RCX: 0000000000000000 [81.807] RDX: 0000000002040001 RSI: 00000000ffffffef RDI: ffffffffc0608bf0 [81.807] RBP: 00000000ffffffef R08: ffff8e69830f6000 R09: 0000000000000007 [81.808] R10: ffff8e699921e5e8 R11: 0000000000000000 R12: ffff8e6999228000 [81.808] R13: ffff8e6984d82000 R14: ffff8e69966a69c0 R15: ffff8e69aa47b000 [81.809] FS: 00007fec6bdd9740(0000) GS:ffff8e6b1b379000(0000) knlGS:0000000000000000 [81.809] CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 [81.810] CR2: 00005604833670f0 CR3: 0000000116679000 CR4: 00000000000006f0 [81.810] Call Trace: [81.810] [81.810] __btrfs_end_transaction+0x3e/0x2b0 [btrfs] [81.811] btrfs_force_chunk_alloc_store+0xcd/0x140 [btrfs] [81.811] kernfs_fop_write_iter+0x15f/0x240 [81.812] vfs_write+0x264/0x500 [81.812] ksys_write+0x6c/0xe0 [81.812] do_syscall_64+0x66/0x770 [81.812] entry_SYSCALL_64_after_hwframe+0x76/0x7e [81.813] RIP: 0033:0x7fec6be66197 [81.814] RSP: 002b:00007fffb159dd30 EFLAGS: 00000202 ORIG_RAX: 0000000000000001 [81.815] RAX: ffffffffffffffda RBX: 00007fec6bdd9740 RCX: 00007fec6be66197 [81.815] RDX: 0000000000000002 RSI: 0000560483374f80 RDI: 0000000000000001 [81.816] RBP: 0000560483374f80 R08: 0000000000000000 R09: 0000000000000000 [81.816] R10: 0000000000000000 R11: 0000000000000202 R12: 0000000000000002 [81.817] R13: 00007fec6bfb85c0 R14: 00007fec6bfb5ee0 R15: 00005604833729c0 [81.817] [81.817] irq event stamp: 20039 [81.818] hardirqs last enabled at (20047): [] __up_console_sem+0x52/0x60 [81.818] hardirqs last disabled at (20056): [] __up_console_sem+0x37/0x60 [81.819] softirqs last enabled at (19470): [] __irq_exit_rcu+0x96/0xc0 [81.819] softirqs last disabled at (19463): [] __irq_exit_rcu+0x96/0xc0 [81.820] ---[ end trace 0000000000000000 ]--- [81.820] BTRFS: error (device dm-7 state A) in btrfs_create_pending_block_groups:2876: errno=-17 Object already exists Inspecting these aborts with drgn, I observed a pattern of overlapping chunk_maps. Note how stripe 1 of the first chunk overlaps in physical address with stripe 0 of the second chunk. Physical Start Physical End Length Logical Type Stripe ---------------------------------------------------------------------------------------------------- 0x0000000102500000 0x0000000142500000 1.0G 0x0000000641d00000 META|DUP 0/2 0x0000000142500000 0x0000000182500000 1.0G 0x0000000641d00000 META|DUP 1/2 0x0000000142500000 0x0000000182500000 1.0G 0x0000000601d00000 META|DUP 0/2 0x0000000182500000 0x00000001c2500000 1.0G 0x0000000601d00000 META|DUP 1/2 Now how could this possibly happen? All chunk allocation is ---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) 4.1.1 To (excluding) 6.18.14

Linux>>Linux_kernel >> Version From (including) 6.19 To (excluding) 6.19.4

Linux>>Linux_kernel >> Version 4.1

Linux>>Linux_kernel >> Version 4.1

Linux>>Linux_kernel >> Version 4.1

Linux>>Linux_kernel >> Version 4.1

Linux>>Linux_kernel >> Version 4.1

Linux>>Linux_kernel >> Version 4.1

Linux>>Linux_kernel >> Version 4.1

Linux>>Linux_kernel >> Version 4.1

References