CVE-2023-52611 : Detail

CVE-2023-52611

5.5
/
Medium
0.05%V4
Local
2024-03-18
10h07 +00:00
2024-12-19
08h22 +00:00
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CVE Descriptions

wifi: rtw88: sdio: Honor the host max_req_size in the RX path

In the Linux kernel, the following vulnerability has been resolved: wifi: rtw88: sdio: Honor the host max_req_size in the RX path Lukas reports skb_over_panic errors on his Banana Pi BPI-CM4 which comes with an Amlogic A311D (G12B) SoC and a RTL8822CS SDIO wifi/Bluetooth combo card. The error he observed is identical to what has been fixed in commit e967229ead0e ("wifi: rtw88: sdio: Check the HISR RX_REQUEST bit in rtw_sdio_rx_isr()") but that commit didn't fix Lukas' problem. Lukas found that disabling or limiting RX aggregation works around the problem for some time (but does not fully fix it). In the following discussion a few key topics have been discussed which have an impact on this problem: - The Amlogic A311D (G12B) SoC has a hardware bug in the SDIO controller which prevents DMA transfers. Instead all transfers need to go through the controller SRAM which limits transfers to 1536 bytes - rtw88 chips don't split incoming (RX) packets, so if a big packet is received this is forwarded to the host in it's original form - rtw88 chips can do RX aggregation, meaning more multiple incoming packets can be pulled by the host from the card with one MMC/SDIO transfer. This Depends on settings in the REG_RXDMA_AGG_PG_TH register (BIT_RXDMA_AGG_PG_TH limits the number of packets that will be aggregated, BIT_DMA_AGG_TO_V1 configures a timeout for aggregation and BIT_EN_PRE_CALC makes the chip honor the limits more effectively) Use multiple consecutive reads in rtw_sdio_read_port() and limit the number of bytes which are copied by the host from the card in one MMC/SDIO transfer. This allows receiving a buffer that's larger than the hosts max_req_size (number of bytes which can be transferred in one MMC/SDIO transfer). As a result of this the skb_over_panic error is gone as the rtw88 driver is now able to receive more than 1536 bytes from the card (either because the incoming packet is larger than that or because multiple packets have been aggregated). In case of an receive errors (-EILSEQ has been observed by Lukas) we need to drain the remaining data from the card's buffer, otherwise the card will return corrupt data for the next rtw_sdio_read_port() call.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE Other No informations.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 5.5 MEDIUM CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/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.

None

There is no loss of integrity within 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) 6.4 To (excluding) 6.6.14

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.7.2

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.