CVE-2024-53275 : 상세 정보

CVE-2024-53275

5.3
/
보통
0.06%V4
2024-12-23
17h13 +00:00
Adjacent
2025-02-18
21h48 +00:00
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알림 관리

CVE 설명

GHSL-2024-091: DNS rebinding attack in home-gallery

Home-Gallery.org is a self-hosted open-source web gallery to browse personal photos and videos. In 1.15.0 and earlier, the default setup of home-gallery is vulnerable to DNS rebinding. Home-gallery is set up without TLS and user authentication by default, leaving it vulnerable to DNS rebinding. In this attack, an attacker will ask a user to visit their website. The attacker website will then change the DNS records of their domain from their IP address to the internal IP address of the home-gallery instance. To tell which IP addresses are valid, we can rebind a subdomain to each IP address we want to check, and see if there is a response. Once potential candidates have been found, the attacker can launch the attack by reading the response of the web server after the IP address has changed. When the attacker domain is fetched, the response will be from the home-gallery instance, not the attacker website, because the IP address has been changed. Due to a lack of authentication, home-gallery photos can then be extracted by the attacker website.

CVE 정보

관련 약점

CWE-ID 약점 이름 출처
CWE-350 Reliance on Reverse DNS Resolution for a Security-Critical Action
The product performs reverse DNS resolution on an IP address to obtain the hostname and make a security decision, but it does not properly ensure that the IP address is truly associated with the hostname.

메트릭

메트릭 점수 심각도 CVSS 벡터 출처
V4.0 5.3 MEDIUM CVSS:4.0/AV:A/AC:L/AT:N/PR:N/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N

Base: Exploitabilty Metrics

The Exploitability metrics reflect the characteristics of the “thing that is vulnerable”, which we refer to formally as the vulnerable system.

Attack Vector

This metric reflects the context by which vulnerability exploitation is possible.

Adjacent

The vulnerable system is bound to a protocol 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 proximity (e.g., Bluetooth, NFC, or IEEE 802.11) or logical network (e.g., local IP subnet), or from within a secure or otherwise limited administrative domain (e.g., MPLS, secure VPN within an administrative network zone).

Attack Complexity

This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit.

Low

The attacker must take no measurable action to exploit the vulnerability. The attack requires no target-specific circumvention to exploit the vulnerability. An attacker can expect repeatable success against the vulnerable system.

Attack Requirements

This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack.

None

The successful attack does not depend on the deployment and execution conditions of the vulnerable system. The attacker can expect to be able to reach the vulnerability and execute the exploit under all or most instances of the vulnerability.

Privileges Required

This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability.

None

The attacker is unauthenticated 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 system.

None

The vulnerable system can be exploited without interaction from any human user, other than the attacker. Examples include: a remote attacker is able to send packets to a target system a locally authenticated attacker executes code to elevate privileges

Base: Impact Metrics

The Impact metrics capture the effects of a successfully exploited vulnerability. 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 managed by the system due to a successfully exploited vulnerability.

Low

There is some loss of confidentiality. Access to some restricted information is obtained, but the attacker does not have control over what information is obtained, or the amount or kind of loss is limited. The information disclosure does not cause a direct, serious loss to the Vulnerable System.

Integrity Impact

This metric measures the impact to integrity of a successfully exploited vulnerability.

None

There is no loss of integrity within the Vulnerable System.

Availability Impact

This metric measures the impact to the availability of the impacted system resulting from a successfully exploited vulnerability.

None

There is no impact to availability within the Vulnerable System.

Sub Confidentiality Impact

Negligible

There is no loss of confidentiality within the Subsequent System or all confidentiality impact is constrained to the Vulnerable System.

Sub Integrity Impact

None

There is no loss of integrity within the Subsequent System or all integrity impact is constrained to the Vulnerable System.

Sub Availability Impact

None

There is no impact to availability within the Subsequent System or all availability impact is constrained to the Vulnerable System.

Threat Metrics

The Threat metrics measure the current state of exploit techniques or code availability for a vulnerability.

Environmental Metrics

These metrics enable the consumer analyst to customize the resulting score depending on the importance of the affected IT asset to a user’s organization, measured in terms of complementary/alternative security controls in place, Confidentiality, Integrity, and Availability. The metrics are the modified equivalent of Base metrics and are assigned values based on the system placement within organizational infrastructure.

Supplemental Metrics

Supplemental metric group provides new metrics that describe and measure additional extrinsic attributes of a vulnerability. While the assessment of Supplemental metrics is provisioned by the provider, the usage and response plan of each metric within the Supplemental metric group is determined by the consumer.

EPSS

EPSS는 취약점이 악용될 가능성을 예측하는 점수 모델입니다.

EPSS 점수

EPSS 모델은 0과 1(0~100%) 사이의 확률 점수를 생성합니다. 점수가 높을수록 취약점이 악용될 가능성이 높습니다.

EPSS 백분위수

백분위수는 EPSS 점수에 따라 CVE의 순위를 매기는 데 사용됩니다. 예를 들어 EPSS 점수 기준 95번째 백분위수의 CVE는 다른 CVE의 95%보다 악용될 가능성이 높습니다.

참고 자료