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Kimai has Server-Side Request Forgery in Invoice PDF Rendering via Markdown Image URLs

Moderate severity GitHub Reviewed Published Jun 3, 2026 in kimai/kimai • Updated Jul 10, 2026

Package

composer kimai/kimai (Composer)

Affected versions

<= 2.57.0

Patched versions

2.58.0

Description

Summary

Kimai 2.56.0 contains a server-side request forgery vulnerability in its invoice PDF preview and generation workflow. If an attacker can control Markdown content that is later rendered into an invoice PDF, such as Customer.invoiceText, the server-side PDF renderer will fetch remote image URLs embedded in Markdown image syntax.

This allows the application server to issue outbound requests to attacker-controlled or internal targets during PDF rendering. The behavior can be used for internal network probing, server-side reachability checks, and potentially follow-on exploitation depending on deployment environment and accessible internal services.

Details

The vulnerable behavior occurs in the invoice rendering chain when user-controlled Markdown is transformed into HTML and then rendered by mPDF.

  • First, customer invoice text is copied into the invoice model.
    . Second, the default PDF invoice template renders that field through the Markdown-to-HTML filter.
  • Third, md2html enables full Markdown rendering.
  • Although safe mode is enabled, the tested Markdown image syntax still survives into the rendered HTML chain in a form that causes the PDF renderer to fetch the image resource.
  • Finally, the HTML is handed to mPDF.

The live test confirms that mPDF attempts to retrieve the remote image URL from the server side during PDF preview. This means the issue is not a template-injection problem but an SSRF condition caused by the rendering pipeline:

  • attacker-controlled Markdown
  • Markdown converted to HTML
  • HTML rendered by mPDF
  • mPDF fetches remote image resources from the server side

A PoC was provided, but removed for security reasons.

Impact

This vulnerability allows an attacker who can influence invoice-rendered Markdown fields to cause the Kimai server to make outbound requests to arbitrary destinations. In real deployments, this can be used to probe internal services, test access to internal administrative or metadata endpoints, and confirm server-side reachability to attacker-controlled infrastructure.

Depending on the environment, SSRF can also become a stepping stone toward more serious outcomes, such as triggering side effects on internal HTTP services or extracting sensitive information from services reachable only by the server. Because invoice generation is commonly performed by administrative or finance-related users, the feature is realistically reachable in business workflows.

Solution

  • Kimai does not allow to use markdown images any longer and converts them to HTML links instead
  • Kimai uses a specialized HttpClient for mPDF (called NoPrivateNetworkHttpClient), which prevents access to a variety of URLs, the full list can be fetched from the documentation
  • This change can be a BC break, if someone used
    • the Kimai domain for hosting invoice or export template images
    • an internal IP for hosting invoice or export template images

See https://www.kimai.org/en/security/ghsa-pj8j-p4g4-4vw8

References

@kevinpapst kevinpapst published to kimai/kimai Jun 3, 2026
Published to the GitHub Advisory Database Jul 10, 2026
Reviewed Jul 10, 2026
Last updated Jul 10, 2026

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality Low
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
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. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the 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. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:N/SC:L/SI:N/SA:N

EPSS score

Weaknesses

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. Learn more on MITRE.

CVE ID

CVE-2026-49865

GHSA ID

GHSA-pj8j-p4g4-4vw8

Source code

Credits

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