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CVE-2020-15811 : Détail

CVE-2020-15811

6.5
/
MEDIUM
0.15%V3
Network
2020-09-02 14:35 +00:00
2021-02-26 07:06 +00:00
CVE.org
NVD

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Gestion des alertes

Descriptions

An issue was discovered in Squid before 4.13 and 5.x before 5.0.4. Due to incorrect data validation, HTTP Request Splitting attacks may succeed against HTTP and HTTPS traffic. This leads to cache poisoning. This allows any client, including browser scripts, to bypass local security and poison the browser cache and any downstream caches with content from an arbitrary source. Squid uses a string search instead of parsing the Transfer-Encoding header to find chunked encoding. This allows an attacker to hide a second request inside Transfer-Encoding: it is interpreted by Squid as chunked and split out into a second request delivered upstream. Squid will then deliver two distinct responses to the client, corrupting any downstream caches.

Informations

Faiblesses connexes

CWE-ID Nom de la faiblesse Source
CWE-697 Incorrect Comparison
The product compares two entities in a security-relevant context, but the comparison is incorrect, which may lead to resultant weaknesses.

Metrics

Metric Score Sévérité CVSS Vecteur Source
V3.1 6.5 MEDIUM CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/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.

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.

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.

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.

 nvd@nist.gov
V2 4 AV:N/AC:L/Au:S/C:N/I:P/A:N nvd@nist.gov

EPSS

EPSS est un modèle de notation qui prédit la probabilité qu'une vulnérabilité soit exploitée.

EPSS Score

Le modèle EPSS produit un score de probabilité compris entre 0 et 1 (0 et 100 %). Plus la note est élevée, plus la probabilité qu'une vulnérabilité soit exploitée est grande.

EPSS Percentile

Le percentile est utilisé pour classer les CVE en fonction de leur score EPSS. Par exemple, une CVE dans le 95e percentile selon son score EPSS est plus susceptible d'être exploitée que 95 % des autres CVE. Ainsi, le percentile sert à comparer le score EPSS d'une CVE par rapport à d'autres CVE.
EPSS First.org

Products Mentioned

Configuraton 0

Squid-cache>>Squid >> Version To (excluding) 4.13

Squid-cache>>Squid >> Version From (including) 5.0 To (excluding) 5.0.4

Configuraton 0

Canonical>>Ubuntu_linux >> Version 16.04

Canonical>>Ubuntu_linux >> Version 18.04

Canonical>>Ubuntu_linux >> Version 20.04

Configuraton 0

Debian>>Debian_linux >> Version 9.0

Debian>>Debian_linux >> Version 10.0

Configuraton 0

Fedoraproject>>Fedora >> Version 31

Fedoraproject>>Fedora >> Version 32

Fedoraproject>>Fedora >> Version 33

Configuraton 0

Opensuse>>Leap >> Version 15.1

Opensuse>>Leap >> Version 15.2

References

https://www.debian.org/security/2020/dsa-4751
Tags : vendor-advisory, x_refsource_DEBIAN
https://usn.ubuntu.com/4477-1/
Tags : vendor-advisory, x_refsource_UBUNTU
https://usn.ubuntu.com/4551-1/
Tags : vendor-advisory, x_refsource_UBUNTU

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