CVE-2026-5921 : Detail

CVE-2026-5921

8.9
/
High
Server-Side Request Forgery - SSRF
A10-Server-Side Req. Forgery (SSRF)
0.05%V4
Network
2026-04-21
22h11 +00:00
2026-04-22
13h18 +00:00
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CVE Descriptions

Server-Side Request Forgery in GitHub Enterprise Server allowed extraction of sensitive environment variables via timing side-channel attack

A server-side request forgery (SSRF) vulnerability was identified in GitHub Enterprise Server that allowed an attacker to extract sensitive environment variables from the instance through a timing side-channel attack against the notebook rendering service. When private mode was disabled, the notebook viewer followed HTTP redirects without revalidating the destination host, enabling an unauthenticated SSRF to internal services. By chaining this with regex filter queries against an internal API and measuring response time differences, an attacker could infer secret values character by character. Exploitation required that private mode be disabled and that the attacker be able to chain the instance's open redirect endpoint through an external redirect to reach internal services. This vulnerability affected all versions of GitHub Enterprise Server prior to 3.21 and was fixed in versions 3.14.26, 3.15.21, 3.16.17, 3.17.14, 3.18.8, 3.19.5, and 3.20.1. This vulnerability was reported via the GitHub Bug Bounty program.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-918 Server-Side Request Forgery (SSRF)
The web server receives a URL or similar request from an upstream component and retrieves the contents of this URL, but it does not sufficiently ensure that the request is being sent to the expected destination.

Metrics

Metrics Score Severity CVSS Vector Source
V4.0 8.9 HIGH CVSS:4.0/AV:N/AC:H/AT:P/PR:N/UI:N/VC:H/VI:H/VA:L/SC:H/SI:H/SA:L/E:P

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.

Network

The vulnerable system 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 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.

High

The successful attack depends on the evasion or circumvention of security-enhancing techniques in place that would otherwise hinder the attack. These include: Evasion of exploit mitigation techniques. The attacker must have additional methods available to bypass security measures in place. For example, circumvention of address space randomization (ASLR) or data execution prevention (DEP) must be performed for the attack to be successful. Obtaining target-specific secrets. The attacker must gather some target-specific secret before the attack can be successful. A secret is any piece of information that cannot be obtained through any amount of reconnaissance. To obtain the secret the attacker must perform additional attacks or break otherwise secure measures (e.g. knowledge of a secret key may be needed to break a crypto channel). This operation must be performed for each attacked target.

Attack Requirements

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

Present

The successful attack depends on the presence of specific deployment and execution conditions of the vulnerable system that enable the attack. These include: A race condition must be won to successfully exploit the vulnerability. The successfulness of the attack is conditioned on execution conditions that are not under full control of the attacker. The attack may need to be launched multiple times against a single target before being successful. Network injection. The attacker must inject themselves into the logical network path between the target and the resource requested by the victim (e.g. vulnerabilities requiring an on-path attacker).

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.

High

There is a total loss of confidentiality, resulting in all information within the Vulnerable System 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.

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 Vulnerable System. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the Vulnerable System.

Availability Impact

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

Low

Performance is reduced or there are interruptions in resource availability. Even if repeated exploitation of the vulnerability is possible, the attacker does not have the ability to completely deny service to legitimate users. The resources in the Vulnerable System are either partially available all of the time, or fully available only some of the time, but overall there is no direct, serious consequence to the Vulnerable System.

Sub Confidentiality Impact

High

There is a total loss of confidentiality, resulting in all resources within the Subsequent System 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.

Sub Integrity Impact

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 Subsequent System. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the Subsequent System.

Sub Availability Impact

Low

Performance is reduced or there are interruptions in resource availability. Even if repeated exploitation of the vulnerability is possible, the attacker does not have the ability to completely deny service to legitimate users. The resources in the Subsequent System are either partially available all of the time, or fully available only some of the time, but overall there is no direct, serious consequence to the Subsequent System.

Threat Metrics

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

Exploit Code Maturity

This metric measures the likelihood of the vulnerability being attacked, and is based on the current state of exploit techniques, exploit code availability, or active, 'in-the-wild' exploitation.

Proof-of-Concept

Based on available threat intelligence each of the following must apply: Proof-of-concept exploit code is publicly available No knowledge of reported attempts to exploit this vulnerability No knowledge of publicly available solutions used to simplify attempts to exploit the vulnerability (i.e., the “Attacked” value does not apply)

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

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.

References