CVE-2024-46797 : Detail

CVE-2024-46797

5.5
/
Medium
0.02%V4
Local
2024-09-18
07h12 +00:00
2024-12-19
09h23 +00:00
CVE.org
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CVE Descriptions

powerpc/qspinlock: Fix deadlock in MCS queue

In the Linux kernel, the following vulnerability has been resolved: powerpc/qspinlock: Fix deadlock in MCS queue If an interrupt occurs in queued_spin_lock_slowpath() after we increment qnodesp->count and before node->lock is initialized, another CPU might see stale lock values in get_tail_qnode(). If the stale lock value happens to match the lock on that CPU, then we write to the "next" pointer of the wrong qnode. This causes a deadlock as the former CPU, once it becomes the head of the MCS queue, will spin indefinitely until it's "next" pointer is set by its successor in the queue. Running stress-ng on a 16 core (16EC/16VP) shared LPAR, results in occasional lockups similar to the following: $ stress-ng --all 128 --vm-bytes 80% --aggressive \ --maximize --oomable --verify --syslog \ --metrics --times --timeout 5m watchdog: CPU 15 Hard LOCKUP ...... NIP [c0000000000b78f4] queued_spin_lock_slowpath+0x1184/0x1490 LR [c000000001037c5c] _raw_spin_lock+0x6c/0x90 Call Trace: 0xc000002cfffa3bf0 (unreliable) _raw_spin_lock+0x6c/0x90 raw_spin_rq_lock_nested.part.135+0x4c/0xd0 sched_ttwu_pending+0x60/0x1f0 __flush_smp_call_function_queue+0x1dc/0x670 smp_ipi_demux_relaxed+0xa4/0x100 xive_muxed_ipi_action+0x20/0x40 __handle_irq_event_percpu+0x80/0x240 handle_irq_event_percpu+0x2c/0x80 handle_percpu_irq+0x84/0xd0 generic_handle_irq+0x54/0x80 __do_irq+0xac/0x210 __do_IRQ+0x74/0xd0 0x0 do_IRQ+0x8c/0x170 hardware_interrupt_common_virt+0x29c/0x2a0 --- interrupt: 500 at queued_spin_lock_slowpath+0x4b8/0x1490 ...... NIP [c0000000000b6c28] queued_spin_lock_slowpath+0x4b8/0x1490 LR [c000000001037c5c] _raw_spin_lock+0x6c/0x90 --- interrupt: 500 0xc0000029c1a41d00 (unreliable) _raw_spin_lock+0x6c/0x90 futex_wake+0x100/0x260 do_futex+0x21c/0x2a0 sys_futex+0x98/0x270 system_call_exception+0x14c/0x2f0 system_call_vectored_common+0x15c/0x2ec The following code flow illustrates how the deadlock occurs. For the sake of brevity, assume that both locks (A and B) are contended and we call the queued_spin_lock_slowpath() function. CPU0 CPU1 ---- ---- spin_lock_irqsave(A) | spin_unlock_irqrestore(A) | spin_lock(B) | | | ▼ | id = qnodesp->count++; | (Note that nodes[0].lock == A) | | | ▼ | Interrupt | (happens before "nodes[0].lock = B") | | | ▼ | spin_lock_irqsave(A) | | | ▼ | id = qnodesp->count++ | nodes[1].lock = A | | | ▼ | Tail of MCS queue | | spin_lock_irqsave(A) ▼ | Head of MCS queue ▼ | CPU0 is previous tail ▼ | Spin indefinitely ▼ (until "nodes[1].next != NULL") prev = get_tail_qnode(A, CPU0) | ▼ prev == &qnodes[CPU0].nodes[0] (as qnodes ---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.
EPSS First.org

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.51

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.10.10

Linux>>Linux_kernel >> Version 6.11

Linux>>Linux_kernel >> Version 6.11

Linux>>Linux_kernel >> Version 6.11

Linux>>Linux_kernel >> Version 6.11

Linux>>Linux_kernel >> Version 6.11

Linux>>Linux_kernel >> Version 6.11

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.