CVE-2024-39371 : Detail

CVE-2024-39371

5.5
/
Medium
Memory Corruption
0.04%V3
Local
2024-06-25
14h22 +00:00
2024-12-19
09h06 +00:00
Notifications for a CVE
Stay informed of any changes for a specific CVE.
Notifications manage

CVE Descriptions

io_uring: check for non-NULL file pointer in io_file_can_poll()

In the Linux kernel, the following vulnerability has been resolved: io_uring: check for non-NULL file pointer in io_file_can_poll() In earlier kernels, it was possible to trigger a NULL pointer dereference off the forced async preparation path, if no file had been assigned. The trace leading to that looks as follows: BUG: kernel NULL pointer dereference, address: 00000000000000b0 PGD 0 P4D 0 Oops: 0000 [#1] PREEMPT SMP CPU: 67 PID: 1633 Comm: buf-ring-invali Not tainted 6.8.0-rc3+ #1 Hardware name: QEMU Standard PC (i440FX + PIIX, 1996), BIOS unknown 2/2/2022 RIP: 0010:io_buffer_select+0xc3/0x210 Code: 00 00 48 39 d1 0f 82 ae 00 00 00 48 81 4b 48 00 00 01 00 48 89 73 70 0f b7 50 0c 66 89 53 42 85 ed 0f 85 d2 00 00 00 48 8b 13 <48> 8b 92 b0 00 00 00 48 83 7a 40 00 0f 84 21 01 00 00 4c 8b 20 5b RSP: 0018:ffffb7bec38c7d88 EFLAGS: 00010246 RAX: ffff97af2be61000 RBX: ffff97af234f1700 RCX: 0000000000000040 RDX: 0000000000000000 RSI: ffff97aecfb04820 RDI: ffff97af234f1700 RBP: 0000000000000000 R08: 0000000000200030 R09: 0000000000000020 R10: ffffb7bec38c7dc8 R11: 000000000000c000 R12: ffffb7bec38c7db8 R13: ffff97aecfb05800 R14: ffff97aecfb05800 R15: ffff97af2be5e000 FS: 00007f852f74b740(0000) GS:ffff97b1eeec0000(0000) knlGS:0000000000000000 CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 CR2: 00000000000000b0 CR3: 000000016deab005 CR4: 0000000000370ef0 Call Trace: ? __die+0x1f/0x60 ? page_fault_oops+0x14d/0x420 ? do_user_addr_fault+0x61/0x6a0 ? exc_page_fault+0x6c/0x150 ? asm_exc_page_fault+0x22/0x30 ? io_buffer_select+0xc3/0x210 __io_import_iovec+0xb5/0x120 io_readv_prep_async+0x36/0x70 io_queue_sqe_fallback+0x20/0x260 io_submit_sqes+0x314/0x630 __do_sys_io_uring_enter+0x339/0xbc0 ? __do_sys_io_uring_register+0x11b/0xc50 ? vm_mmap_pgoff+0xce/0x160 do_syscall_64+0x5f/0x180 entry_SYSCALL_64_after_hwframe+0x46/0x4e RIP: 0033:0x55e0a110a67e Code: ba cc 00 00 00 45 31 c0 44 0f b6 92 d0 00 00 00 31 d2 41 b9 08 00 00 00 41 83 e2 01 41 c1 e2 04 41 09 c2 b8 aa 01 00 00 0f 05 90 89 30 eb a9 0f 1f 40 00 48 8b 42 20 8b 00 a8 06 75 af 85 f6 because the request is marked forced ASYNC and has a bad file fd, and hence takes the forced async prep path. Current kernels with the request async prep cleaned up can no longer hit this issue, but for ease of backporting, let's add this safety check in here too as it really doesn't hurt. For both cases, this will inevitably end with a CQE posted with -EBADF.

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 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) 5.19 To (excluding) 6.1.95

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.35

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.9.5

Linux>>Linux_kernel >> Version 6.10

Linux>>Linux_kernel >> Version 6.10

References