CVE-2024-40962 : Detail

CVE-2024-40962

5.5
/
Medium
Memory Corruption
0.04%V4
Local
2024-07-12
12h32 +00:00
2024-12-19
09h09 +00:00
CVE.org
NVD
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CVE Descriptions

btrfs: zoned: allocate dummy checksums for zoned NODATASUM writes

In the Linux kernel, the following vulnerability has been resolved: btrfs: zoned: allocate dummy checksums for zoned NODATASUM writes Shin'ichiro reported that when he's running fstests' test-case btrfs/167 on emulated zoned devices, he's seeing the following NULL pointer dereference in 'btrfs_zone_finish_endio()': Oops: general protection fault, probably for non-canonical address 0xdffffc0000000011: 0000 [#1] PREEMPT SMP KASAN NOPTI KASAN: null-ptr-deref in range [0x0000000000000088-0x000000000000008f] CPU: 4 PID: 2332440 Comm: kworker/u80:15 Tainted: G W 6.10.0-rc2-kts+ #4 Hardware name: Supermicro Super Server/X11SPi-TF, BIOS 3.3 02/21/2020 Workqueue: btrfs-endio-write btrfs_work_helper [btrfs] RIP: 0010:btrfs_zone_finish_endio.part.0+0x34/0x160 [btrfs] RSP: 0018:ffff88867f107a90 EFLAGS: 00010206 RAX: dffffc0000000000 RBX: 0000000000000000 RCX: ffffffff893e5534 RDX: 0000000000000011 RSI: 0000000000000004 RDI: 0000000000000088 RBP: 0000000000000002 R08: 0000000000000001 R09: ffffed1081696028 R10: ffff88840b4b0143 R11: ffff88834dfff600 R12: ffff88840b4b0000 R13: 0000000000020000 R14: 0000000000000000 R15: ffff888530ad5210 FS: 0000000000000000(0000) GS:ffff888e3f800000(0000) knlGS:0000000000000000 CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 CR2: 00007f87223fff38 CR3: 00000007a7c6a002 CR4: 00000000007706f0 DR0: 0000000000000000 DR1: 0000000000000000 DR2: 0000000000000000 DR3: 0000000000000000 DR6: 00000000fffe0ff0 DR7: 0000000000000400 PKRU: 55555554 Call Trace: ? __die_body.cold+0x19/0x27 ? die_addr+0x46/0x70 ? exc_general_protection+0x14f/0x250 ? asm_exc_general_protection+0x26/0x30 ? do_raw_read_unlock+0x44/0x70 ? btrfs_zone_finish_endio.part.0+0x34/0x160 [btrfs] btrfs_finish_one_ordered+0x5d9/0x19a0 [btrfs] ? __pfx_lock_release+0x10/0x10 ? do_raw_write_lock+0x90/0x260 ? __pfx_do_raw_write_lock+0x10/0x10 ? __pfx_btrfs_finish_one_ordered+0x10/0x10 [btrfs] ? _raw_write_unlock+0x23/0x40 ? btrfs_finish_ordered_zoned+0x5a9/0x850 [btrfs] ? lock_acquire+0x435/0x500 btrfs_work_helper+0x1b1/0xa70 [btrfs] ? __schedule+0x10a8/0x60b0 ? __pfx___might_resched+0x10/0x10 process_one_work+0x862/0x1410 ? __pfx_lock_acquire+0x10/0x10 ? __pfx_process_one_work+0x10/0x10 ? assign_work+0x16c/0x240 worker_thread+0x5e6/0x1010 ? __pfx_worker_thread+0x10/0x10 kthread+0x2c3/0x3a0 ? trace_irq_enable.constprop.0+0xce/0x110 ? __pfx_kthread+0x10/0x10 ret_from_fork+0x31/0x70 ? __pfx_kthread+0x10/0x10 ret_from_fork_asm+0x1a/0x30 Enabling CONFIG_BTRFS_ASSERT revealed the following assertion to trigger: assertion failed: !list_empty(&ordered->list), in fs/btrfs/zoned.c:1815 This indicates, that we're missing the checksums list on the ordered_extent. As btrfs/167 is doing a NOCOW write this is to be expected. Further analysis with drgn confirmed the assumption: >>> inode = prog.crashed_thread().stack_trace()[11]['ordered'].inode >>> btrfs_inode = drgn.container_of(inode, "struct btrfs_inode", \ "vfs_inode") >>> print(btrfs_inode.flags) (u32)1 As zoned emulation mode simulates conventional zones on regular devices, we cannot use zone-append for writing. But we're only attaching dummy checksums if we're doing a zone-append write. So for NOCOW zoned data writes on conventional zones, also attach a dummy checksum.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-476 NULL Pointer Dereference
The product dereferences a pointer that it expects to be valid but is NULL.

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.
EPSS First.org

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 6.5 To (excluding) 6.6.36

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.9.7

Linux>>Linux_kernel >> Version 6.10

Linux>>Linux_kernel >> Version 6.10

Linux>>Linux_kernel >> Version 6.10

Linux>>Linux_kernel >> Version 6.10

References

The information presented on CVE Find originates from several carefully selected reference sources. CVE data is provided by MITRE Corporation and the National Vulnerability Database (NVD). The Known Exploited Vulnerabilities (KEV) catalog is sourced from the Cybersecurity and Infrastructure Security Agency (CISA), while EPSS scores come from FIRST.org. Additionally, data regarding software weaknesses (CWE) and common attack patterns (CAPEC) is maintained by MITRE Corporation, and information on hardware and software configurations (CPE) is provided by the NVD.