CVE-2026-98869
14h55 +00:00
CVE 설명
bpf: Infer zext_dst based on static register liveness analysis
In the Linux kernel, the following vulnerability has been resolved: bpf: Infer zext_dst based on static register liveness analysis As reported in the thread [1], the verifier's 32-bit operations zero extension logic is broken. This logic is responsible for correct semantics of 32-bit operations on s390 architecture. According to BPF semantics, operation `w1 += 1` is supposed to zero extend the upper half of the register `r1`. On s390 the JIT relies on the verifier emitting explicit zero extension before such operations. The verifier attempts to minimize the amount of zero extensions inserted by tracking whether upper halves of the 64-bit registers are ever used. Previously such tracking worked as follows: - bpf_reg_state->subreg_def field was set by do_check_insn() for each operation defining lower but not the upper halves of the register. - Whenever an operation reading the whole register was verified, the verifier checked register's subreg_def and set bpf_insn_aux_data->zext_dst flag as true via a call to mark_insn_zext() function. - After the verification was complete, a special pass bpf_opt_subreg_zext_lo32_rnd_hi32() extended 32-bit operations with bpf_insn_aux_data->zext_dst set as true by adding explicit zero extension. Note that the logic above relies on bpf_reg_state->subreg_def, which is a property of a current verifier state. Before the commit [2] two additional steps happened: - The verifier tracked upper and lower register halves' liveness as flags REG_LIVE_READ{32,64} in bpf_reg_state->live. - The function propagate_liveness() called mark_insn_zext() in order to transfer the knowledge about which registers have their upper halves alive (and thus might require zero extension). The commit [2] removed the two steps described above, hence making possible a situation like below: - The register's upper half is set and is used on some verification path P1 and the register happens not to be marked as precise. - The checkpoint C is created while processing some instruction between register initialization and usage. - On some other verification path P2 the register's upper half is not initialized and that path ends hitting the checkpoint C. - In such a case the register's initialization on path P2 would lack zext_dst mark, making it possible for the program to inject an arbitrary value in the register's upper half. This commit replaces subreg_def based logic with computing zext_dst statically, as a part of the bpf_compute_live_registers() analysis: - The analysis now tracks usage of upper and lower halves of the registers separately. - If some instruction defines a 32-bit subregister, but not the whole register, *and* the upper half of the register is alive after that instruction, the instruction is marked as zext_dst. There is one notable drop in precision: whenever a BPF subprogram is called, all 64 bits of parameter registers are presumed to be used. The assumption is that such a drop in precision would not inflict a noticeable performance penalty. [1] https://lore.kernel.org/bpf/CAGKGUv=sOuqQtA1Ub-5JXfA4FPosJFYKAQE4B79cK+P1erxqtg@mail.gmail.com/ [2] commit 107e16979905 ("bpf: disable and remove registers chain based liveness")CVE 정보
메트릭
| 메트릭 | 점수 | 심각도 | CVSS 벡터 | 출처 |
|---|---|---|---|---|
| V3.1 | 7.8 | HIGH |
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
추가 정보
Base: Exploitabilty MetricsThe 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 MetricsThe 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 MetricsThe 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 MetricsThe 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 MetricsThese 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. |
