CVE-2022-48629 : 詳細

CVE-2022-48629

8.1
/
高
0.02%V4
2024-03-05
11h18 +00:00
Adjacent
2026-08-04
09h01 +00:00
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CVE の説明

crypto: qcom-rng - ensure buffer for generate is completely filled

In the Linux kernel, the following vulnerability has been resolved: crypto: qcom-rng - ensure buffer for generate is completely filled The generate function in struct rng_alg expects that the destination buffer is completely filled if the function returns 0. qcom_rng_read() can run into a situation where the buffer is partially filled with randomness and the remaining part of the buffer is zeroed since qcom_rng_generate() doesn't check the return value. This issue can be reproduced by running the following from libkcapi: kcapi-rng -b 9000000 > OUTFILE The generated OUTFILE will have three huge sections that contain all zeros, and this is caused by the code where the test 'val & PRNG_STATUS_DATA_AVAIL' fails. Let's fix this issue by ensuring that qcom_rng_read() always returns with a full buffer if the function returns success. Let's also have qcom_rng_generate() return the correct value. Here's some statistics from the ent project (https://www.fourmilab.ch/random/) that shows information about the quality of the generated numbers: $ ent -c qcom-random-before Value Char Occurrences Fraction 0 606748 0.067416 1 33104 0.003678 2 33001 0.003667 ... 253 � 32883 0.003654 254 � 33035 0.003671 255 � 33239 0.003693 Total: 9000000 1.000000 Entropy = 7.811590 bits per byte. Optimum compression would reduce the size of this 9000000 byte file by 2 percent. Chi square distribution for 9000000 samples is 9329962.81, and randomly would exceed this value less than 0.01 percent of the times. Arithmetic mean value of data bytes is 119.3731 (127.5 = random). Monte Carlo value for Pi is 3.197293333 (error 1.77 percent). Serial correlation coefficient is 0.159130 (totally uncorrelated = 0.0). Without this patch, the results of the chi-square test is 0.01%, and the numbers are certainly not random according to ent's project page. The results improve with this patch: $ ent -c qcom-random-after Value Char Occurrences Fraction 0 35432 0.003937 1 35127 0.003903 2 35424 0.003936 ... 253 � 35201 0.003911 254 � 34835 0.003871 255 � 35368 0.003930 Total: 9000000 1.000000 Entropy = 7.999979 bits per byte. Optimum compression would reduce the size of this 9000000 byte file by 0 percent. Chi square distribution for 9000000 samples is 258.77, and randomly would exceed this value 42.24 percent of the times. Arithmetic mean value of data bytes is 127.5006 (127.5 = random). Monte Carlo value for Pi is 3.141277333 (error 0.01 percent). Serial correlation coefficient is 0.000468 (totally uncorrelated = 0.0). This change was tested on a Nexus 5 phone (msm8974 SoC).

CVE の情報

関連する弱点

CWE-ID 弱点名 出典
CWE Other 情報がありません。

メトリクス

メトリクス スコア 深刻度 CVSS ベクター 出典
V3.1 8.1 HIGH CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N

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.

Adjacent

The vulnerable component is bound to the network stack, but the attack is limited at the protocol level to a logically adjacent topology. This can mean an attack must be launched from the same shared physical (e.g., Bluetooth or IEEE 802.11) or logical (e.g., local IP subnet) network, or from within a secure or otherwise limited administrative domain (e.g., MPLS, secure VPN to an administrative network zone).

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.

None

The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an attack.

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.

None

There is no impact to availability within the impacted component.

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.

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は脆弱性が悪用される可能性を予測するスコアリングモデルです。

EPSSスコア

EPSSモデルは0から1(0〜100%)の確率スコアを算出します。スコアが高いほど、脆弱性が悪用される可能性が高いことを示します。

EPSSパーセンタイル

パーセンタイルはCVEをEPSSスコアで順位付けするために使用されます。例えば、EPSSスコアで95パーセンタイルにあるCVEは、他の95%のCVEよりも悪用される可能性が高いことを意味します。パーセンタイルはCVEのEPSSスコアを他のCVEと比較するために使用されます。

関連製品

構成 0

Linux>>Linux_kernel >> Version ~から(含む) 4.19 ~まで(含まない) 4.19.236

Linux>>Linux_kernel >> Version ~から(含む) 4.20 ~まで(含まない) 5.4.187

Linux>>Linux_kernel >> Version ~から(含む) 5.5 ~まで(含まない) 5.10.108

Linux>>Linux_kernel >> Version ~から(含む) 5.11 ~まで(含まない) 5.15.31

Linux>>Linux_kernel >> Version ~から(含む) 5.16 ~まで(含まない) 5.16.17

Linux>>Linux_kernel >> Version 5.17

Linux>>Linux_kernel >> Version 5.17

Linux>>Linux_kernel >> Version 5.17

Linux>>Linux_kernel >> Version 5.17

Linux>>Linux_kernel >> Version 5.17

Linux>>Linux_kernel >> Version 5.17

Linux>>Linux_kernel >> Version 5.17

Linux>>Linux_kernel >> Version 5.17

参考資料