CVE-2024-50082 : Detail

CVE-2024-50082

4.7
/
Medium
0.04%V3
Local
2024-10-29
00h50 +00:00
2024-12-19
09h32 +00:00
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CVE Descriptions

blk-rq-qos: fix crash on rq_qos_wait vs. rq_qos_wake_function race

In the Linux kernel, the following vulnerability has been resolved: blk-rq-qos: fix crash on rq_qos_wait vs. rq_qos_wake_function race We're seeing crashes from rq_qos_wake_function that look like this: BUG: unable to handle page fault for address: ffffafe180a40084 #PF: supervisor write access in kernel mode #PF: error_code(0x0002) - not-present page PGD 100000067 P4D 100000067 PUD 10027c067 PMD 10115d067 PTE 0 Oops: Oops: 0002 [#1] PREEMPT SMP PTI CPU: 17 UID: 0 PID: 0 Comm: swapper/17 Not tainted 6.12.0-rc3-00013-geca631b8fe80 #11 Hardware name: QEMU Standard PC (i440FX + PIIX, 1996), BIOS rel-1.16.0-0-gd239552ce722-prebuilt.qemu.org 04/01/2014 RIP: 0010:_raw_spin_lock_irqsave+0x1d/0x40 Code: 90 90 90 90 90 90 90 90 90 90 90 90 90 f3 0f 1e fa 0f 1f 44 00 00 41 54 9c 41 5c fa 65 ff 05 62 97 30 4c 31 c0 ba 01 00 00 00 0f b1 17 75 0a 4c 89 e0 41 5c c3 cc cc cc cc 89 c6 e8 2c 0b 00 RSP: 0018:ffffafe180580ca0 EFLAGS: 00010046 RAX: 0000000000000000 RBX: ffffafe180a3f7a8 RCX: 0000000000000011 RDX: 0000000000000001 RSI: 0000000000000003 RDI: ffffafe180a40084 RBP: 0000000000000000 R08: 00000000001e7240 R09: 0000000000000011 R10: 0000000000000028 R11: 0000000000000888 R12: 0000000000000002 R13: ffffafe180a40084 R14: 0000000000000000 R15: 0000000000000003 FS: 0000000000000000(0000) GS:ffff9aaf1f280000(0000) knlGS:0000000000000000 CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 CR2: ffffafe180a40084 CR3: 000000010e428002 CR4: 0000000000770ef0 DR0: 0000000000000000 DR1: 0000000000000000 DR2: 0000000000000000 DR3: 0000000000000000 DR6: 00000000fffe0ff0 DR7: 0000000000000400 PKRU: 55555554 Call Trace: try_to_wake_up+0x5a/0x6a0 rq_qos_wake_function+0x71/0x80 __wake_up_common+0x75/0xa0 __wake_up+0x36/0x60 scale_up.part.0+0x50/0x110 wb_timer_fn+0x227/0x450 ... So rq_qos_wake_function() calls wake_up_process(data->task), which calls try_to_wake_up(), which faults in raw_spin_lock_irqsave(&p->pi_lock). p comes from data->task, and data comes from the waitqueue entry, which is stored on the waiter's stack in rq_qos_wait(). Analyzing the core dump with drgn, I found that the waiter had already woken up and moved on to a completely unrelated code path, clobbering what was previously data->task. Meanwhile, the waker was passing the clobbered garbage in data->task to wake_up_process(), leading to the crash. What's happening is that in between rq_qos_wake_function() deleting the waitqueue entry and calling wake_up_process(), rq_qos_wait() is finding that it already got a token and returning. The race looks like this: rq_qos_wait() rq_qos_wake_function() ============================================================== prepare_to_wait_exclusive() data->got_token = true; list_del_init(&curr->entry); if (data.got_token) break; finish_wait(&rqw->wait, &data.wq); ^- returns immediately because list_empty_careful(&wq_entry->entry) is true ... return, go do something else ... wake_up_process(data->task) (NO LONGER VALID!)-^ Normally, finish_wait() is supposed to synchronize against the waker. But, as noted above, it is returning immediately because the waitqueue entry has already been removed from the waitqueue. The bug is that rq_qos_wake_function() is accessing the waitqueue entry AFTER deleting it. Note that autoremove_wake_function() wakes the waiter and THEN deletes the waitqueue entry, which is the proper order. Fix it by swapping the order. We also need to use list_del_init_careful() to match the list_empty_careful() in finish_wait().

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE Other No informations.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 4.7 MEDIUM CVSS:3.1/AV:L/AC:H/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.

High

successful attack depends on conditions beyond the attacker's control. That is, a successful attack cannot be accomplished at will, but requires the attacker to invest in some measurable amount of effort in preparation or execution against the vulnerable component before a successful attack can be expected.

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.

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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) 4.19 To (excluding) 5.10.228

Linux>>Linux_kernel >> Version From (including) 5.11 To (excluding) 5.15.169

Linux>>Linux_kernel >> Version From (including) 5.16 To (excluding) 6.1.114

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.58

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.11.5

Linux>>Linux_kernel >> Version 6.12

Linux>>Linux_kernel >> Version 6.12

Linux>>Linux_kernel >> Version 6.12

References