CVE-2026-45933 : Detail

CVE-2026-45933

7.8
/
High
0.01%V4
Local
2026-05-27
14h17 +00:00
2026-06-24
17h11 +00:00
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CVE Descriptions

In the Linux kernel, the following vulnerability has been resolved: bpf: Preserve id of register in sync_linked_regs() sync_linked_regs() copies the id of known_reg to reg when propagating bounds of known_reg to reg using the off of known_reg, but when known_reg was linked to reg like: known_reg = reg ; both known_reg and reg get same id known_reg += 4 ; known_reg gets off = 4, and its id gets BPF_ADD_CONST now when a call to sync_linked_regs() happens, let's say with the following: if known_reg >= 10 goto pc+2 known_reg's new bounds are propagated to reg but now reg gets BPF_ADD_CONST from the copy. This means if another link to reg is created like: another_reg = reg ; another_reg should get the id of reg but assign_scalar_id_before_mov() sees BPF_ADD_CONST on reg and assigns a new id to it. As reg has a new id now, known_reg's link to reg is broken. If we find new bounds for known_reg, they will not be propagated to reg. This can be seen in the selftest added in the next commit: 0: (85) call bpf_get_prandom_u32#7 ; R0=scalar() 1: (57) r0 &= 255 ; R0=scalar(smin=smin32=0,smax=umax=smax32=umax32=255,var_off=(0x0; 0xff)) 2: (bf) r1 = r0 ; R0=scalar(id=1,smin=smin32=0,smax=umax=smax32=umax32=255,var_off=(0x0; 0xff)) R1=scalar(id=1,smin=smin32=0,smax=umax=smax32=umax32=255,var_off=(0x0; 0xff)) 3: (07) r1 += 4 ; R1=scalar(id=1+4,smin=umin=smin32=umin32=4,smax=umax=smax32=umax32=259,var_off=(0x0; 0x1ff)) 4: (a5) if r1 < 0xa goto pc+4 ; R1=scalar(id=1+4,smin=umin=smin32=umin32=10,smax=umax=smax32=umax32=259,var_off=(0x0; 0x1ff)) 5: (bf) r2 = r0 ; R0=scalar(id=2,smin=umin=smin32=umin32=6,smax=umax=smax32=umax32=255) R2=scalar(id=2,smin=umin=smin32=umin32=6,smax=umax=smax32=umax32=255) 6: (a5) if r1 < 0xe goto pc+2 ; R1=scalar(id=1+4,smin=umin=smin32=umin32=14,smax=umax=smax32=umax32=259,var_off=(0x0; 0x1ff)) 7: (35) if r0 >= 0xa goto pc+1 ; R0=scalar(id=2,smin=umin=smin32=umin32=6,smax=umax=smax32=umax32=9,var_off=(0x0; 0xf)) 8: (37) r0 /= 0 div by zero When 4 is verified, r1's bounds are propagated to r0 but r0 also gets BPF_ADD_CONST (bug). When 5 is verified, r0 gets a new id (2) and its link with r1 is broken. After 6 we know r1 has bounds [14, 259] and therefore r0 should have bounds [10, 255], therefore the branch at 7 is always taken. But because r0's id was changed to 2, r1's new bounds are not propagated to r0. The verifier still thinks r0 has bounds [6, 255] before 7 and execution can reach div by zero. Fix this by preserving id in sync_linked_regs() like off and subreg_def.

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.

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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) 6.11 To (excluding) 6.12.75

Linux>>Linux_kernel >> Version From (including) 6.13 To (excluding) 6.18.14

Linux>>Linux_kernel >> Version From (including) 6.19 To (excluding) 6.19.4

References