] __kmalloc_cache_noprof+0x2f9/0x3f0 [] task_numa_work+0x725/0xa00 [] task_work_run+0x58/0x90 [] syscall_exit_to_user_mode+0x1c8/0x1e0 [] do_syscall_64+0x85/0x150 [] entry_SYSCALL_64_after_hwframe+0x76/0x7e ... This issue can be consistently reproduced on three different servers: * a 448-core server * a 256-core server * a 192-core server [Root Cause] Since multiple threads are created by the hackbench program (along with the command argument 'thread'), a shared vma might be accessed by two or more cores simultaneously. When two or more cores observe that vma->numab_state is NULL at the same time, vma->numab_state will be overwritten. Although current code ensures that only one thread scans the VMAs in a single 'numa_scan_period', there might be a chance for another thread to enter in the next 'numa_scan_period' while we have not gotten till numab_state allocation [1]. Note that the command `/opt/ltp/testcases/bin/hackbench 50 process 1000` cannot the reproduce the issue. It is verified with 200+ test runs. [Solution] Use the cmpxchg atomic operation to ensure that only one thread executes the vma->numab_state assignment. [1] https://lore.kernel.org/lkml/[email protected]/">

CVE-2024-56613 : Detail

CVE-2024-56613

5.5
/
Medium
0.04%V3
Local
2024-12-27
14h51 +00:00
2025-01-20
06h24 +00:00
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CVE Descriptions

sched/numa: fix memory leak due to the overwritten vma->numab_state

In the Linux kernel, the following vulnerability has been resolved: sched/numa: fix memory leak due to the overwritten vma->numab_state [Problem Description] When running the hackbench program of LTP, the following memory leak is reported by kmemleak. # /opt/ltp/testcases/bin/hackbench 20 thread 1000 Running with 20*40 (== 800) tasks. # dmesg | grep kmemleak ... kmemleak: 480 new suspected memory leaks (see /sys/kernel/debug/kmemleak) kmemleak: 665 new suspected memory leaks (see /sys/kernel/debug/kmemleak) # cat /sys/kernel/debug/kmemleak unreferenced object 0xffff888cd8ca2c40 (size 64): comm "hackbench", pid 17142, jiffies 4299780315 hex dump (first 32 bytes): ac 74 49 00 01 00 00 00 4c 84 49 00 01 00 00 00 .tI.....L.I..... 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................ backtrace (crc bff18fd4): [] __kmalloc_cache_noprof+0x2f9/0x3f0 [] task_numa_work+0x725/0xa00 [] task_work_run+0x58/0x90 [] syscall_exit_to_user_mode+0x1c8/0x1e0 [] do_syscall_64+0x85/0x150 [] entry_SYSCALL_64_after_hwframe+0x76/0x7e ... This issue can be consistently reproduced on three different servers: * a 448-core server * a 256-core server * a 192-core server [Root Cause] Since multiple threads are created by the hackbench program (along with the command argument 'thread'), a shared vma might be accessed by two or more cores simultaneously. When two or more cores observe that vma->numab_state is NULL at the same time, vma->numab_state will be overwritten. Although current code ensures that only one thread scans the VMAs in a single 'numa_scan_period', there might be a chance for another thread to enter in the next 'numa_scan_period' while we have not gotten till numab_state allocation [1]. Note that the command `/opt/ltp/testcases/bin/hackbench 50 process 1000` cannot the reproduce the issue. It is verified with 200+ test runs. [Solution] Use the cmpxchg atomic operation to ensure that only one thread executes the vma->numab_state assignment. [1] https://lore.kernel.org/lkml/[email protected]/

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-401 Missing Release of Memory after Effective Lifetime
The product does not sufficiently track and release allocated memory after it has been used, which slowly consumes remaining memory.

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.

[email protected]

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) 6.4 To (excluding) 6.6.66

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.12.5

Linux>>Linux_kernel >> Version 6.13

References