CVE-2024-26976 : Détail

CVE-2024-26976

7
/
Haute
0.05%V4
Local
2024-05-01
05h20 +00:00
2025-02-05
21h08 +00:00
CVE.org
NVD
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Descriptions du CVE

KVM: Always flush async #PF workqueue when vCPU is being destroyed

In the Linux kernel, the following vulnerability has been resolved: KVM: Always flush async #PF workqueue when vCPU is being destroyed Always flush the per-vCPU async #PF workqueue when a vCPU is clearing its completion queue, e.g. when a VM and all its vCPUs is being destroyed. KVM must ensure that none of its workqueue callbacks is running when the last reference to the KVM _module_ is put. Gifting a reference to the associated VM prevents the workqueue callback from dereferencing freed vCPU/VM memory, but does not prevent the KVM module from being unloaded before the callback completes. Drop the misguided VM refcount gifting, as calling kvm_put_kvm() from async_pf_execute() if kvm_put_kvm() flushes the async #PF workqueue will result in deadlock. async_pf_execute() can't return until kvm_put_kvm() finishes, and kvm_put_kvm() can't return until async_pf_execute() finishes: WARNING: CPU: 8 PID: 251 at virt/kvm/kvm_main.c:1435 kvm_put_kvm+0x2d/0x320 [kvm] Modules linked in: vhost_net vhost vhost_iotlb tap kvm_intel kvm irqbypass CPU: 8 PID: 251 Comm: kworker/8:1 Tainted: G W 6.6.0-rc1-e7af8d17224a-x86/gmem-vm #119 Hardware name: QEMU Standard PC (Q35 + ICH9, 2009), BIOS 0.0.0 02/06/2015 Workqueue: events async_pf_execute [kvm] RIP: 0010:kvm_put_kvm+0x2d/0x320 [kvm] Call Trace: async_pf_execute+0x198/0x260 [kvm] process_one_work+0x145/0x2d0 worker_thread+0x27e/0x3a0 kthread+0xba/0xe0 ret_from_fork+0x2d/0x50 ret_from_fork_asm+0x11/0x20 ---[ end trace 0000000000000000 ]--- INFO: task kworker/8:1:251 blocked for more than 120 seconds. Tainted: G W 6.6.0-rc1-e7af8d17224a-x86/gmem-vm #119 "echo 0 > /proc/sys/kernel/hung_task_timeout_secs" disables this message. task:kworker/8:1 state:D stack:0 pid:251 ppid:2 flags:0x00004000 Workqueue: events async_pf_execute [kvm] Call Trace: __schedule+0x33f/0xa40 schedule+0x53/0xc0 schedule_timeout+0x12a/0x140 __wait_for_common+0x8d/0x1d0 __flush_work.isra.0+0x19f/0x2c0 kvm_clear_async_pf_completion_queue+0x129/0x190 [kvm] kvm_arch_destroy_vm+0x78/0x1b0 [kvm] kvm_put_kvm+0x1c1/0x320 [kvm] async_pf_execute+0x198/0x260 [kvm] process_one_work+0x145/0x2d0 worker_thread+0x27e/0x3a0 kthread+0xba/0xe0 ret_from_fork+0x2d/0x50 ret_from_fork_asm+0x11/0x20 If kvm_clear_async_pf_completion_queue() actually flushes the workqueue, then there's no need to gift async_pf_execute() a reference because all invocations of async_pf_execute() will be forced to complete before the vCPU and its VM are destroyed/freed. And that in turn fixes the module unloading bug as __fput() won't do module_put() on the last vCPU reference until the vCPU has been freed, e.g. if closing the vCPU file also puts the last reference to the KVM module. Note that kvm_check_async_pf_completion() may also take the work item off the completion queue and so also needs to flush the work queue, as the work will not be seen by kvm_clear_async_pf_completion_queue(). Waiting on the workqueue could theoretically delay a vCPU due to waiting for the work to complete, but that's a very, very small chance, and likely a very small delay. kvm_arch_async_page_present_queued() unconditionally makes a new request, i.e. will effectively delay entering the guest, so the remaining work is really just: trace_kvm_async_pf_completed(addr, cr2_or_gpa); __kvm_vcpu_wake_up(vcpu); mmput(mm); and mmput() can't drop the last reference to the page tables if the vCPU is still alive, i.e. the vCPU won't get stuck tearing down page tables. Add a helper to do the flushing, specifically to deal with "wakeup all" work items, as they aren't actually work items, i.e. are never placed in a workqueue. Trying to flush a bogus workqueue entry rightly makes __flush_work() complain (kudos to whoever added that sanity check). Note, commit 5f6de5cbebee ("KVM: Prevent module exit until al ---truncated---

Informations du CVE

Faiblesses connexes

CWE-ID Nom de la faiblesse Source
CWE-400 Uncontrolled Resource Consumption
The product does not properly control the allocation and maintenance of a limited resource.

Métriques

Métriques Score Gravité CVSS Vecteur Source
V3.1 7 HIGH CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/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.

High

There is a total loss of confidentiality, resulting in all resources within the impacted component being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server.

Integrity Impact

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

High

There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the impacted component. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to 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 est un modèle de notation qui prédit la probabilité qu'une vulnérabilité soit exploitée.

Score EPSS

Le modèle EPSS produit un score de probabilité compris entre 0 et 1 (0 et 100 %). Plus la note est élevée, plus la probabilité qu'une vulnérabilité soit exploitée est grande.

Percentile EPSS

Le percentile est utilisé pour classer les CVE en fonction de leur score EPSS. Par exemple, une CVE dans le 95e percentile selon son score EPSS est plus susceptible d'être exploitée que 95 % des autres CVE. Ainsi, le percentile sert à comparer le score EPSS d'une CVE par rapport à d'autres CVE.
EPSS First.org

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 2.6.38 To (excluding) 4.19.312

Linux>>Linux_kernel >> Version From (including) 4.20 To (excluding) 5.4.274

Linux>>Linux_kernel >> Version From (including) 5.5 To (excluding) 5.10.215

Linux>>Linux_kernel >> Version From (including) 5.11 To (excluding) 5.15.154

Linux>>Linux_kernel >> Version From (including) 5.16 To (excluding) 6.1.84

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.24

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.7.12

Linux>>Linux_kernel >> Version From (including) 6.8 To (excluding) 6.8.3

Configuraton 0

Debian>>Debian_linux >> Version 10.0

Références