CVE-2024-26586 : Detail

CVE-2024-26586

6.7
/
Medium
Overflow
0.04%V3
Local
2024-02-22
16h13 +00:00
2024-12-19
08h43 +00:00
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CVE Descriptions

mlxsw: spectrum_acl_tcam: Fix stack corruption

In the Linux kernel, the following vulnerability has been resolved: mlxsw: spectrum_acl_tcam: Fix stack corruption When tc filters are first added to a net device, the corresponding local port gets bound to an ACL group in the device. The group contains a list of ACLs. In turn, each ACL points to a different TCAM region where the filters are stored. During forwarding, the ACLs are sequentially evaluated until a match is found. One reason to place filters in different regions is when they are added with decreasing priorities and in an alternating order so that two consecutive filters can never fit in the same region because of their key usage. In Spectrum-2 and newer ASICs the firmware started to report that the maximum number of ACLs in a group is more than 16, but the layout of the register that configures ACL groups (PAGT) was not updated to account for that. It is therefore possible to hit stack corruption [1] in the rare case where more than 16 ACLs in a group are required. Fix by limiting the maximum ACL group size to the minimum between what the firmware reports and the maximum ACLs that fit in the PAGT register. Add a test case to make sure the machine does not crash when this condition is hit. [1] Kernel panic - not syncing: stack-protector: Kernel stack is corrupted in: mlxsw_sp_acl_tcam_group_update+0x116/0x120 [...] dump_stack_lvl+0x36/0x50 panic+0x305/0x330 __stack_chk_fail+0x15/0x20 mlxsw_sp_acl_tcam_group_update+0x116/0x120 mlxsw_sp_acl_tcam_group_region_attach+0x69/0x110 mlxsw_sp_acl_tcam_vchunk_get+0x492/0xa20 mlxsw_sp_acl_tcam_ventry_add+0x25/0xe0 mlxsw_sp_acl_rule_add+0x47/0x240 mlxsw_sp_flower_replace+0x1a9/0x1d0 tc_setup_cb_add+0xdc/0x1c0 fl_hw_replace_filter+0x146/0x1f0 fl_change+0xc17/0x1360 tc_new_tfilter+0x472/0xb90 rtnetlink_rcv_msg+0x313/0x3b0 netlink_rcv_skb+0x58/0x100 netlink_unicast+0x244/0x390 netlink_sendmsg+0x1e4/0x440 ____sys_sendmsg+0x164/0x260 ___sys_sendmsg+0x9a/0xe0 __sys_sendmsg+0x7a/0xc0 do_syscall_64+0x40/0xe0 entry_SYSCALL_64_after_hwframe+0x63/0x6b

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-787 Out-of-bounds Write
The product writes data past the end, or before the beginning, of the intended buffer.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 6.7 MEDIUM CVSS:3.1/AV:L/AC:L/PR:H/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.

High

The attacker requires privileges that provide significant (e.g., administrative) control over the vulnerable component allowing access to component-wide settings and files.

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.

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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.

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 4.19.0 To (excluding) 5.10.209

Linux>>Linux_kernel >> Version From (including) 5.11.0 To (excluding) 5.15.148

Linux>>Linux_kernel >> Version From (including) 5.16.0 To (excluding) 6.1.79

Linux>>Linux_kernel >> Version From (including) 6.2.0 To (excluding) 6.6.14

Linux>>Linux_kernel >> Version From (including) 6.7.0 To (excluding) 6.7.2

References