CVE-2024-36972 : Detail

CVE-2024-36972

7.5
/
High
Memory Corruption
0.05%V3
Network
2024-06-10
14h57 +00:00
2024-12-19
09h03 +00:00
CVE.org
NVD
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CVE Descriptions

af_unix: Update unix_sk(sk)->oob_skb under sk_receive_queue lock.

In the Linux kernel, the following vulnerability has been resolved: af_unix: Update unix_sk(sk)->oob_skb under sk_receive_queue lock. Billy Jheng Bing-Jhong reported a race between __unix_gc() and queue_oob(). __unix_gc() tries to garbage-collect close()d inflight sockets, and then if the socket has MSG_OOB in unix_sk(sk)->oob_skb, GC will drop the reference and set NULL to it locklessly. However, the peer socket still can send MSG_OOB message and queue_oob() can update unix_sk(sk)->oob_skb concurrently, leading NULL pointer dereference. [0] To fix the issue, let's update unix_sk(sk)->oob_skb under the sk_receive_queue's lock and take it everywhere we touch oob_skb. Note that we defer kfree_skb() in manage_oob() to silence lockdep false-positive (See [1]). [0]: BUG: kernel NULL pointer dereference, address: 0000000000000008 PF: supervisor write access in kernel mode PF: error_code(0x0002) - not-present page PGD 8000000009f5e067 P4D 8000000009f5e067 PUD 9f5d067 PMD 0 Oops: 0002 [#1] PREEMPT SMP PTI CPU: 3 PID: 50 Comm: kworker/3:1 Not tainted 6.9.0-rc5-00191-gd091e579b864 #110 Hardware name: QEMU Standard PC (i440FX + PIIX, 1996), BIOS rel-1.16.0-0-gd239552ce722-prebuilt.qemu.org 04/01/2014 Workqueue: events delayed_fput RIP: 0010:skb_dequeue (./include/linux/skbuff.h:2386 ./include/linux/skbuff.h:2402 net/core/skbuff.c:3847) Code: 39 e3 74 3e 8b 43 10 48 89 ef 83 e8 01 89 43 10 49 8b 44 24 08 49 c7 44 24 08 00 00 00 00 49 8b 14 24 49 c7 04 24 00 00 00 00 <48> 89 42 08 48 89 10 e8 e7 c5 42 00 4c 89 e0 5b 5d 41 5c c3 cc cc RSP: 0018:ffffc900001bfd48 EFLAGS: 00000002 RAX: 0000000000000000 RBX: ffff8880088f5ae8 RCX: 00000000361289f9 RDX: 0000000000000000 RSI: 0000000000000206 RDI: ffff8880088f5b00 RBP: ffff8880088f5b00 R08: 0000000000080000 R09: 0000000000000001 R10: 0000000000000003 R11: 0000000000000001 R12: ffff8880056b6a00 R13: ffff8880088f5280 R14: 0000000000000001 R15: ffff8880088f5a80 FS: 0000000000000000(0000) GS:ffff88807dd80000(0000) knlGS:0000000000000000 CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 CR2: 0000000000000008 CR3: 0000000006314000 CR4: 00000000007506f0 PKRU: 55555554 Call Trace: unix_release_sock (net/unix/af_unix.c:654) unix_release (net/unix/af_unix.c:1050) __sock_release (net/socket.c:660) sock_close (net/socket.c:1423) __fput (fs/file_table.c:423) delayed_fput (fs/file_table.c:444 (discriminator 3)) process_one_work (kernel/workqueue.c:3259) worker_thread (kernel/workqueue.c:3329 kernel/workqueue.c:3416) kthread (kernel/kthread.c:388) ret_from_fork (arch/x86/kernel/process.c:153) ret_from_fork_asm (arch/x86/entry/entry_64.S:257) Modules linked in: CR2: 0000000000000008

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-476 NULL Pointer Dereference
The product dereferences a pointer that it expects to be valid but is NULL.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 7.5 HIGH CVSS:3.1/AV:N/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.

Network

The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).

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 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) 5.15.149 To (excluding) 5.15.161

Linux>>Linux_kernel >> Version From (including) 6.1.78 To (excluding) 6.1.93

Linux>>Linux_kernel >> Version From (including) 6.6.17 To (excluding) 6.6.33

Linux>>Linux_kernel >> Version From (including) 6.7.5 To (excluding) 6.9.4

References