CVE-2024-56559 : Detail

CVE-2024-56559

5.5
/
Medium
0.01%V4
Local
2024-12-27
14h23 +00:00
2025-05-04
09h58 +00:00
Notifications for a CVE
Stay informed of any changes for a specific CVE.
Notifications manage

CVE Descriptions

mm/vmalloc: combine all TLB flush operations of KASAN shadow virtual address into one operation

In the Linux kernel, the following vulnerability has been resolved: mm/vmalloc: combine all TLB flush operations of KASAN shadow virtual address into one operation When compiling kernel source 'make -j $(nproc)' with the up-and-running KASAN-enabled kernel on a 256-core machine, the following soft lockup is shown: watchdog: BUG: soft lockup - CPU#28 stuck for 22s! [kworker/28:1:1760] CPU: 28 PID: 1760 Comm: kworker/28:1 Kdump: loaded Not tainted 6.10.0-rc5 #95 Workqueue: events drain_vmap_area_work RIP: 0010:smp_call_function_many_cond+0x1d8/0xbb0 Code: 38 c8 7c 08 84 c9 0f 85 49 08 00 00 8b 45 08 a8 01 74 2e 48 89 f1 49 89 f7 48 c1 e9 03 41 83 e7 07 4c 01 e9 41 83 c7 03 f3 90 <0f> b6 01 41 38 c7 7c 08 84 c0 0f 85 d4 06 00 00 8b 45 08 a8 01 75 RSP: 0018:ffffc9000cb3fb60 EFLAGS: 00000202 RAX: 0000000000000011 RBX: ffff8883bc4469c0 RCX: ffffed10776e9949 RDX: 0000000000000002 RSI: ffff8883bb74ca48 RDI: ffffffff8434dc50 RBP: ffff8883bb74ca40 R08: ffff888103585dc0 R09: ffff8884533a1800 R10: 0000000000000004 R11: ffffffffffffffff R12: ffffed1077888d39 R13: dffffc0000000000 R14: ffffed1077888d38 R15: 0000000000000003 FS: 0000000000000000(0000) GS:ffff8883bc400000(0000) knlGS:0000000000000000 CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 CR2: 00005577b5c8d158 CR3: 0000000004850000 CR4: 0000000000350ef0 Call Trace: ? watchdog_timer_fn+0x2cd/0x390 ? __pfx_watchdog_timer_fn+0x10/0x10 ? __hrtimer_run_queues+0x300/0x6d0 ? sched_clock_cpu+0x69/0x4e0 ? __pfx___hrtimer_run_queues+0x10/0x10 ? srso_return_thunk+0x5/0x5f ? ktime_get_update_offsets_now+0x7f/0x2a0 ? srso_return_thunk+0x5/0x5f ? srso_return_thunk+0x5/0x5f ? hrtimer_interrupt+0x2ca/0x760 ? __sysvec_apic_timer_interrupt+0x8c/0x2b0 ? sysvec_apic_timer_interrupt+0x6a/0x90 ? asm_sysvec_apic_timer_interrupt+0x16/0x20 ? smp_call_function_many_cond+0x1d8/0xbb0 ? __pfx_do_kernel_range_flush+0x10/0x10 on_each_cpu_cond_mask+0x20/0x40 flush_tlb_kernel_range+0x19b/0x250 ? srso_return_thunk+0x5/0x5f ? kasan_release_vmalloc+0xa7/0xc0 purge_vmap_node+0x357/0x820 ? __pfx_purge_vmap_node+0x10/0x10 __purge_vmap_area_lazy+0x5b8/0xa10 drain_vmap_area_work+0x21/0x30 process_one_work+0x661/0x10b0 worker_thread+0x844/0x10e0 ? srso_return_thunk+0x5/0x5f ? __kthread_parkme+0x82/0x140 ? __pfx_worker_thread+0x10/0x10 kthread+0x2a5/0x370 ? __pfx_kthread+0x10/0x10 ret_from_fork+0x30/0x70 ? __pfx_kthread+0x10/0x10 ret_from_fork_asm+0x1a/0x30 Debugging Analysis: 1. The following ftrace log shows that the lockup CPU spends too much time iterating vmap_nodes and flushing TLB when purging vm_area structures. (Some info is trimmed). kworker: funcgraph_entry: | drain_vmap_area_work() { kworker: funcgraph_entry: | mutex_lock() { kworker: funcgraph_entry: 1.092 us | __cond_resched(); kworker: funcgraph_exit: 3.306 us | } ... ... kworker: funcgraph_entry: | flush_tlb_kernel_range() { ... ... kworker: funcgraph_exit: # 7533.649 us | } ... ... kworker: funcgraph_entry: 2.344 us | mutex_unlock(); kworker: funcgraph_exit: $ 23871554 us | } The drain_vmap_area_work() spends over 23 seconds. There are 2805 flush_tlb_kernel_range() calls in the ftrace log. * One is called in __purge_vmap_area_lazy(). * Others are called by purge_vmap_node->kasan_release_vmalloc. purge_vmap_node() iteratively releases kasan vmalloc allocations and flushes TLB for each vmap_area. - [Rough calculation] Each flush_tlb_kernel_range() runs about 7.5ms. -- 2804 * 7.5ms = 21.03 seconds. -- That's why a soft lock is triggered. 2. Extending the soft lockup time can work around the issue (For example, # echo ---truncated---

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-667 Improper Locking
The product does not properly acquire or release a lock on a resource, leading to unexpected resource state changes and behaviors.

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) 6.9 To (excluding) 6.12.4

References