CVE-2024-40918 : Detail

CVE-2024-40918

7.8
/
High
0.04%V4
Local
2024-07-12
12h25 +00:00
2026-08-04
09h27 +00:00
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CVE Descriptions

parisc: Try to fix random segmentation faults in package builds

In the Linux kernel, the following vulnerability has been resolved: parisc: Try to fix random segmentation faults in package builds PA-RISC systems with PA8800 and PA8900 processors have had problems with random segmentation faults for many years. Systems with earlier processors are much more stable. Systems with PA8800 and PA8900 processors have a large L2 cache which needs per page flushing for decent performance when a large range is flushed. The combined cache in these systems is also more sensitive to non-equivalent aliases than the caches in earlier systems. The majority of random segmentation faults that I have looked at appear to be memory corruption in memory allocated using mmap and malloc. My first attempt at fixing the random faults didn't work. On reviewing the cache code, I realized that there were two issues which the existing code didn't handle correctly. Both relate to cache move-in. Another issue is that the present bit in PTEs is racy. 1) PA-RISC caches have a mind of their own and they can speculatively load data and instructions for a page as long as there is a entry in the TLB for the page which allows move-in. TLBs are local to each CPU. Thus, the TLB entry for a page must be purged before flushing the page. This is particularly important on SMP systems. In some of the flush routines, the flush routine would be called and then the TLB entry would be purged. This was because the flush routine needed the TLB entry to do the flush. 2) My initial approach to trying the fix the random faults was to try and use flush_cache_page_if_present for all flush operations. This actually made things worse and led to a couple of hardware lockups. It finally dawned on me that some lines weren't being flushed because the pte check code was racy. This resulted in random inequivalent mappings to physical pages. The __flush_cache_page tmpalias flush sets up its own TLB entry and it doesn't need the existing TLB entry. As long as we can find the pte pointer for the vm page, we can get the pfn and physical address of the page. We can also purge the TLB entry for the page before doing the flush. Further, __flush_cache_page uses a special TLB entry that inhibits cache move-in. When switching page mappings, we need to ensure that lines are removed from the cache. It is not sufficient to just flush the lines to memory as they may come back. This made it clear that we needed to implement all the required flush operations using tmpalias routines. This includes flushes for user and kernel pages. After modifying the code to use tmpalias flushes, it became clear that the random segmentation faults were not fully resolved. The frequency of faults was worse on systems with a 64 MB L2 (PA8900) and systems with more CPUs (rp4440). The warning that I added to flush_cache_page_if_present to detect pages that couldn't be flushed triggered frequently on some systems. Helge and I looked at the pages that couldn't be flushed and found that the PTE was either cleared or for a swap page. Ignoring pages that were swapped out seemed okay but pages with cleared PTEs seemed problematic. I looked at routines related to pte_clear and noticed ptep_clear_flush. The default implementation just flushes the TLB entry. However, it was obvious that on parisc we need to flush the cache page as well. If we don't flush the cache page, stale lines will be left in the cache and cause random corruption. Once a PTE is cleared, there is no way to find the physical address associated with the PTE and flush the associated page at a later time. I implemented an updated change with a parisc specific version of ptep_clear_flush. It fixed the random data corruption on Helge's rp4440 and rp3440, as well as on my c8000. At this point, I realized that I could restore the code where we only flush in flush_cache_page_if_present if the page has been accessed. However, for this, we also need to flush the cache when the accessed bit is cleared in ---truncated---

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE Other No informations.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 7.8 HIGH CVSS:3.1/AV:L/AC:L/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.

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.

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.

V3.1 6.3 MEDIUM CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/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.

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.

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.

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.

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.

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.

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version To (excluding) 6.6.35

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.9.6

Linux>>Linux_kernel >> Version 6.10

Linux>>Linux_kernel >> Version 6.10

Linux>>Linux_kernel >> Version 6.10

References