CVE-2024-50164 : Detail

CVE-2024-50164

7.1
/
High
0.04%V4
Local
2024-11-07
09h31 +00:00
2025-04-09
14h51 +00:00
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CVE Descriptions

bpf: Fix overloading of MEM_UNINIT's meaning

In the Linux kernel, the following vulnerability has been resolved: bpf: Fix overloading of MEM_UNINIT's meaning Lonial reported an issue in the BPF verifier where check_mem_size_reg() has the following code: if (!tnum_is_const(reg->var_off)) /* For unprivileged variable accesses, disable raw * mode so that the program is required to * initialize all the memory that the helper could * just partially fill up. */ meta = NULL; This means that writes are not checked when the register containing the size of the passed buffer has not a fixed size. Through this bug, a BPF program can write to a map which is marked as read-only, for example, .rodata global maps. The problem is that MEM_UNINIT's initial meaning that "the passed buffer to the BPF helper does not need to be initialized" which was added back in commit 435faee1aae9 ("bpf, verifier: add ARG_PTR_TO_RAW_STACK type") got overloaded over time with "the passed buffer is being written to". The problem however is that checks such as the above which were added later via 06c1c049721a ("bpf: allow helpers access to variable memory") set meta to NULL in order force the user to always initialize the passed buffer to the helper. Due to the current double meaning of MEM_UNINIT, this bypasses verifier write checks to the memory (not boundary checks though) and only assumes the latter memory is read instead. Fix this by reverting MEM_UNINIT back to its original meaning, and having MEM_WRITE as an annotation to BPF helpers in order to then trigger the BPF verifier checks for writing to memory. Some notes: check_arg_pair_ok() ensures that for ARG_CONST_SIZE{,_OR_ZERO} we can access fn->arg_type[arg - 1] since it must contain a preceding ARG_PTR_TO_MEM. For check_mem_reg() the meta argument can be removed altogether since we do check both BPF_READ and BPF_WRITE. Same for the equivalent check_kfunc_mem_size_reg().

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE Other No informations.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 7.1 HIGH CVSS:3.1/AV:L/AC:L/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.

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.

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.
EPSS First.org

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 5.19 To (excluding) 6.6.59

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.11.6

Linux>>Linux_kernel >> Version 6.12

Linux>>Linux_kernel >> Version 6.12

Linux>>Linux_kernel >> Version 6.12

Linux>>Linux_kernel >> Version 6.12

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.