CVE-2025-29786 : 상세 정보

CVE-2025-29786

7.5
/
높음
0.1%V4
2025-03-17
13h15 +00:00
Network
2026-01-23
16h29 +00:00
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CVE 설명

Memory Exhaustion in Expr Parser with Unrestricted Input

Expr is an expression language and expression evaluation for Go. Prior to version 1.17.0, if the Expr expression parser is given an unbounded input string, it will attempt to compile the entire string and generate an Abstract Syntax Tree (AST) node for each part of the expression. In scenarios where input size isn’t limited, a malicious or inadvertent extremely large expression can consume excessive memory as the parser builds a huge AST. This can ultimately lead to*excessive memory usage and an Out-Of-Memory (OOM) crash of the process. This issue is relatively uncommon and will only manifest when there are no restrictions on the input size, i.e. the expression length is allowed to grow arbitrarily large. In typical use cases where inputs are bounded or validated, this problem would not occur. The problem has been patched in the latest versions of the Expr library. The fix introduces compile-time limits on the number of AST nodes and memory usage during parsing, preventing any single expression from exhausting resources. Users should upgrade to Expr version 1.17.0 or later, as this release includes the new node budget and memory limit safeguards. Upgrading to v1.17.0 ensures that extremely deep or large expressions are detected and safely aborted during compilation, avoiding the OOM condition. For users who cannot immediately upgrade, the recommended workaround is to impose an input size restriction before parsing. In practice, this means validating or limiting the length of expression strings that your application will accept. For example, set a maximum allowable number of characters (or nodes) for any expression and reject or truncate inputs that exceed this limit. By ensuring no unbounded-length expression is ever fed into the parser, one can prevent the parser from constructing a pathologically large AST and avoid potential memory exhaustion. In short, pre-validate and cap input size as a safeguard in the absence of the patch.

CVE 정보

관련 약점

CWE-ID 약점 이름 출처
CWE-770 Allocation of Resources Without Limits or Throttling
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.

메트릭

메트릭 점수 심각도 CVSS 벡터 출처
V3.1 7.5 HIGH CVSS:3.1/AV:N/AC:L/PR:N/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.

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.

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.

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