CVE-2022-49221 : Detail

CVE-2022-49221

5.5
/
Medium
Memory Corruption
0.05%V3
Local
2025-02-26
01h55 +00:00
2025-02-26
01h55 +00:00
CVE.org
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CVE Descriptions

drm/msm/dp: populate connector of struct dp_panel

In the Linux kernel, the following vulnerability has been resolved: drm/msm/dp: populate connector of struct dp_panel DP CTS test case 4.2.2.6 has valid edid with bad checksum on purpose and expect DP source return correct checksum. During drm edid read, correct edid checksum is calculated and stored at connector::real_edid_checksum. The problem is struct dp_panel::connector never be assigned, instead the connector is stored in struct msm_dp::connector. When we run compliance testing test case 4.2.2.6 dp_panel_handle_sink_request() won't have a valid edid set in struct dp_panel::edid so we'll try to use the connectors real_edid_checksum and hit a NULL pointer dereference error because the connector pointer is never assigned. Changes in V2: -- populate panel connector at msm_dp_modeset_init() instead of at dp_panel_read_sink_caps() Changes in V3: -- remove unhelpful kernel crash trace commit text -- remove renaming dp_display parameter to dp Changes in V4: -- add more details to commit text Changes in v10: -- group into one series Changes in v11: -- drop drm/msm/dp: dp_link_parse_sink_count() return immediately if aux read Signee-off-by: Kuogee Hsieh

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.

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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) 5.10.67 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