CVE-2024-50002 : Detail

CVE-2024-50002

5.5
/
Medium
0.03%V4
Local
2024-10-21
18h02 +00:00
2024-12-19
09h31 +00:00
CVE.org
NVD
Notifications for a CVE
Stay informed of any changes for a specific CVE.
Notifications manage

CVE Descriptions

static_call: Handle module init failure correctly in static_call_del_module()

In the Linux kernel, the following vulnerability has been resolved: static_call: Handle module init failure correctly in static_call_del_module() Module insertion invokes static_call_add_module() to initialize the static calls in a module. static_call_add_module() invokes __static_call_init(), which allocates a struct static_call_mod to either encapsulate the built-in static call sites of the associated key into it so further modules can be added or to append the module to the module chain. If that allocation fails the function returns with an error code and the module core invokes static_call_del_module() to clean up eventually added static_call_mod entries. This works correctly, when all keys used by the module were converted over to a module chain before the failure. If not then static_call_del_module() causes a #GP as it blindly assumes that key::mods points to a valid struct static_call_mod. The problem is that key::mods is not a individual struct member of struct static_call_key, it's part of a union to save space: union { /* bit 0: 0 = mods, 1 = sites */ unsigned long type; struct static_call_mod *mods; struct static_call_site *sites; }; key::sites is a pointer to the list of built-in usage sites of the static call. The type of the pointer is differentiated by bit 0. A mods pointer has the bit clear, the sites pointer has the bit set. As static_call_del_module() blidly assumes that the pointer is a valid static_call_mod type, it fails to check for this failure case and dereferences the pointer to the list of built-in call sites, which is obviously bogus. Cure it by checking whether the key has a sites or a mods pointer. If it's a sites pointer then the key is not to be touched. As the sites are walked in the same order as in __static_call_init() the site walk can be terminated because all subsequent sites have not been touched by the init code due to the error exit. If it was converted before the allocation fail, then the inner loop which searches for a module match will find nothing. A fail in the second allocation in __static_call_init() is harmless and does not require special treatment. The first allocation succeeded and converted the key to a module chain. That first entry has mod::mod == NULL and mod::next == NULL, so the inner loop of static_call_del_module() will neither find a module match nor a module chain. The next site in the walk was either already converted, but can't match the module, or it will exit the outer loop because it has a static_call_site pointer and not a static_call_mod pointer.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-755 Improper Handling of Exceptional Conditions
The product does not handle or incorrectly handles an exceptional condition.

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) 5.10 To (excluding) 5.15.168

Linux>>Linux_kernel >> Version From (including) 5.16 To (excluding) 6.1.113

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.55

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.10.14

Linux>>Linux_kernel >> Version From (including) 6.11 To (excluding) 6.11.3

References

The information presented on CVE Find originates from several carefully selected reference sources. CVE data is provided by MITRE Corporation and the National Vulnerability Database (NVD). The Known Exploited Vulnerabilities (KEV) catalog is sourced from the Cybersecurity and Infrastructure Security Agency (CISA), while EPSS scores come from FIRST.org. Additionally, data regarding software weaknesses (CWE) and common attack patterns (CAPEC) is maintained by MITRE Corporation, and information on hardware and software configurations (CPE) is provided by the NVD.