CVE-2022-49282 : Detail

CVE-2022-49282

5.5
/
Medium
Memory Corruption
0.05%V4
Local
2025-02-26
01h56 +00:00
2025-02-26
01h56 +00:00
CVE.org
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CVE Descriptions

f2fs: quota: fix loop condition at f2fs_quota_sync()

In the Linux kernel, the following vulnerability has been resolved: f2fs: quota: fix loop condition at f2fs_quota_sync() cnt should be passed to sb_has_quota_active() instead of type to check active quota properly. Moreover, when the type is -1, the compiler with enough inline knowledge can discard sb_has_quota_active() check altogether, causing a NULL pointer dereference at the following inode_lock(dqopt->files[cnt]): [ 2.796010] Unable to handle kernel NULL pointer dereference at virtual address 00000000000000a0 [ 2.796024] Mem abort info: [ 2.796025] ESR = 0x96000005 [ 2.796028] EC = 0x25: DABT (current EL), IL = 32 bits [ 2.796029] SET = 0, FnV = 0 [ 2.796031] EA = 0, S1PTW = 0 [ 2.796032] Data abort info: [ 2.796034] ISV = 0, ISS = 0x00000005 [ 2.796035] CM = 0, WnR = 0 [ 2.796046] user pgtable: 4k pages, 39-bit VAs, pgdp=00000003370d1000 [ 2.796048] [00000000000000a0] pgd=0000000000000000, pud=0000000000000000 [ 2.796051] Internal error: Oops: 96000005 [#1] PREEMPT SMP [ 2.796056] CPU: 7 PID: 640 Comm: f2fs_ckpt-259:7 Tainted: G S 5.4.179-arter97-r8-64666-g2f16e087f9d8 #1 [ 2.796057] Hardware name: Qualcomm Technologies, Inc. Lahaina MTP lemonadep (DT) [ 2.796059] pstate: 80c00005 (Nzcv daif +PAN +UAO) [ 2.796065] pc : down_write+0x28/0x70 [ 2.796070] lr : f2fs_quota_sync+0x100/0x294 [ 2.796071] sp : ffffffa3f48ffc30 [ 2.796073] x29: ffffffa3f48ffc30 x28: 0000000000000000 [ 2.796075] x27: ffffffa3f6d718b8 x26: ffffffa415fe9d80 [ 2.796077] x25: ffffffa3f7290048 x24: 0000000000000001 [ 2.796078] x23: 0000000000000000 x22: ffffffa3f7290000 [ 2.796080] x21: ffffffa3f72904a0 x20: ffffffa3f7290110 [ 2.796081] x19: ffffffa3f77a9800 x18: ffffffc020aae038 [ 2.796083] x17: ffffffa40e38e040 x16: ffffffa40e38e6d0 [ 2.796085] x15: ffffffa40e38e6cc x14: ffffffa40e38e6d0 [ 2.796086] x13: 00000000000004f6 x12: 00162c44ff493000 [ 2.796088] x11: 0000000000000400 x10: ffffffa40e38c948 [ 2.796090] x9 : 0000000000000000 x8 : 00000000000000a0 [ 2.796091] x7 : 0000000000000000 x6 : 0000d1060f00002a [ 2.796093] x5 : ffffffa3f48ff718 x4 : 000000000000000d [ 2.796094] x3 : 00000000060c0000 x2 : 0000000000000001 [ 2.796096] x1 : 0000000000000000 x0 : 00000000000000a0 [ 2.796098] Call trace: [ 2.796100] down_write+0x28/0x70 [ 2.796102] f2fs_quota_sync+0x100/0x294 [ 2.796104] block_operations+0x120/0x204 [ 2.796106] f2fs_write_checkpoint+0x11c/0x520 [ 2.796107] __checkpoint_and_complete_reqs+0x7c/0xd34 [ 2.796109] issue_checkpoint_thread+0x6c/0xb8 [ 2.796112] kthread+0x138/0x414 [ 2.796114] ret_from_fork+0x10/0x18 [ 2.796117] Code: aa0803e0 aa1f03e1 52800022 aa0103e9 (c8e97d02) [ 2.796120] ---[ end trace 96e942e8eb6a0b53 ]--- [ 2.800116] Kernel panic - not syncing: Fatal exception [ 2.800120] SMP: stopping secondary CPUs

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.

 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) 5.4.148 To (excluding) 5.4.189

Linux>>Linux_kernel >> Version From (including) 5.10.67 To (excluding) 5.10.110

Linux>>Linux_kernel >> Version From (including) 5.13.19 To (excluding) 5.14

Linux>>Linux_kernel >> Version From (including) 5.14.6 To (excluding) 5.15.33

Linux>>Linux_kernel >> Version From (including) 5.16 To (excluding) 5.16.19

Linux>>Linux_kernel >> Version From (including) 5.17 To (excluding) 5.17.2

References