CVE-2024-29018 : Detail

CVE-2024-29018

7.5
/
High
0.14%V4
Network
2024-03-20
20h27 +00:00
2024-08-13
17h00 +00:00
CVE.org
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CVE Descriptions

External DNS requests from 'internal' networks could lead to data exfiltration

Moby is an open source container framework that is a key component of Docker Engine, Docker Desktop, and other distributions of container tooling or runtimes. Moby's networking implementation allows for many networks, each with their own IP address range and gateway, to be defined. This feature is frequently referred to as custom networks, as each network can have a different driver, set of parameters and thus behaviors. When creating a network, the `--internal` flag is used to designate a network as _internal_. The `internal` attribute in a docker-compose.yml file may also be used to mark a network _internal_, and other API clients may specify the `internal` parameter as well. When containers with networking are created, they are assigned unique network interfaces and IP addresses. The host serves as a router for non-internal networks, with a gateway IP that provides SNAT/DNAT to/from container IPs. Containers on an internal network may communicate between each other, but are precluded from communicating with any networks the host has access to (LAN or WAN) as no default route is configured, and firewall rules are set up to drop all outgoing traffic. Communication with the gateway IP address (and thus appropriately configured host services) is possible, and the host may communicate with any container IP directly. In addition to configuring the Linux kernel's various networking features to enable container networking, `dockerd` directly provides some services to container networks. Principal among these is serving as a resolver, enabling service discovery, and resolution of names from an upstream resolver. When a DNS request for a name that does not correspond to a container is received, the request is forwarded to the configured upstream resolver. This request is made from the container's network namespace: the level of access and routing of traffic is the same as if the request was made by the container itself. As a consequence of this design, containers solely attached to an internal network will be unable to resolve names using the upstream resolver, as the container itself is unable to communicate with that nameserver. Only the names of containers also attached to the internal network are able to be resolved. Many systems run a local forwarding DNS resolver. As the host and any containers have separate loopback devices, a consequence of the design described above is that containers are unable to resolve names from the host's configured resolver, as they cannot reach these addresses on the host loopback device. To bridge this gap, and to allow containers to properly resolve names even when a local forwarding resolver is used on a loopback address, `dockerd` detects this scenario and instead forward DNS requests from the host namework namespace. The loopback resolver then forwards the requests to its configured upstream resolvers, as expected. Because `dockerd` forwards DNS requests to the host loopback device, bypassing the container network namespace's normal routing semantics entirely, internal networks can unexpectedly forward DNS requests to an external nameserver. By registering a domain for which they control the authoritative nameservers, an attacker could arrange for a compromised container to exfiltrate data by encoding it in DNS queries that will eventually be answered by their nameservers. Docker Desktop is not affected, as Docker Desktop always runs an internal resolver on a RFC 1918 address. Moby releases 26.0.0, 25.0.4, and 23.0.11 are patched to prevent forwarding any DNS requests from internal networks. As a workaround, run containers intended to be solely attached to internal networks with a custom upstream address, which will force all upstream DNS queries to be resolved from the container's network namespace.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-669 Incorrect Resource Transfer Between Spheres
The product does not properly transfer a resource/behavior to another sphere, or improperly imports a resource/behavior from another sphere, in a manner that provides unintended control over that resource.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 5.9 MEDIUM CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/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.

Network

The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).

Attack Complexity

This metric describes the conditions beyond the attacker’s control that must exist in order to exploit the vulnerability.

High

successful attack depends on conditions beyond the attacker's control. That is, a successful attack cannot be accomplished at will, but requires the attacker to invest in some measurable amount of effort in preparation or execution against the vulnerable component before a successful attack can be expected.

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.

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.

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 7.5 HIGH CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/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.

Network

The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).

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.

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.

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.

 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

Mobyproject>>Moby >> Version To (excluding) 23.0.11

Mobyproject>>Moby >> Version From (including) 24.0.0 To (excluding) 25.0.5

Mobyproject>>Moby >> Version 26.0.0

Mobyproject>>Moby >> Version 26.0.0

Mobyproject>>Moby >> Version 26.0.0

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.