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monetr: Server-side request forgery in Lunch Flow link creation and refresh

High severity GitHub Reviewed Published Apr 18, 2026 in monetr/monetr • Updated Apr 22, 2026

Package

gomod github.com/monetr/monetr (Go)

Affected versions

< 1.12.5

Patched versions

1.12.5

Description

Impact

A server-side request forgery (SSRF) vulnerability in monetr's Lunch Flow integration allowed any authenticated user on
a self-hosted instance to cause the monetr server to issue HTTP GET requests to arbitrary URLs supplied by the caller,
with the response body from non-200 upstream responses reflected back in the API error message.

The URL validator on POST /api/lunch_flow/link only checked the URL scheme and rejected query parameters; it did not
filter loopback, RFC1918, link-local, or cloud-provider metadata addresses. The outbound HTTP client read the response
body via an unbounded io.ReadAll, and the controller intentionally surfaced the resulting error (which contained the
upstream body) as the JSON error field of the API response.

Who is affected: self-hosted monetr deployments running the default configuration. Out of the box,
LunchFlow.Enabled=true, AllowSignUp=true, and billing is not enforced, so any user who can register on the instance
can reach the vulnerable endpoint. Deployments running in a cloud environment where instance metadata is reachable from
the pod (e.g. AWS EC2 without IMDSv2 enforced) expand the impact to include potential exposure of instance metadata
through the reflected error body.

Who is NOT affected: the hosted my.monetr.app service, which runs with LunchFlow.Enabled=false. Self-hosted
operators who had already disabled public sign-up (MONETR_ALLOW_SIGN_UP=false) substantially reduce their exposure
since only operator-trusted users can reach the endpoint.

A secondary denial-of-service vector also existed: because the outbound response body was read with no size cap, an
attacker-influenced upstream could return a multi-GB body that monetr would fully buffer into memory.

Patches

Fixed in monetr v1.12.5. Users should upgrade to this release or later.

The fix introduces a new config field LunchFlow.AllowedApiUrls (a list of permitted Lunch Flow API URLs) with a
default of ["https://lunchflow.app/api/v1"]. URLs outside the allowlist are rejected both at link-creation time and at
client-construction time, with a server-side warning log on rejection. Response body reads are capped at 10 MiB for both
success and error paths. The UI renders the API URL field as a disabled pre-filled input when a single URL is allowed,
or a dropdown when multiple are allowed, so operators who need to use a staging or self-hosted Lunch Flow API opt in
explicitly via config.

Upgrade note for self-hosters with a custom Lunch Flow URL: if your existing LunchFlowLink records point at a URL
other than https://lunchflow.app/api/v1, set your lunchFlow.allowedApiUrls in your yaml config to include your
custom URL before upgrading. Otherwise existing links will fail on next refresh or sync with a "Rejected Lunch Flow API URL that is not in the configured allowlist" warning in the server log.

Workarounds

For operators who cannot upgrade immediately, any of the following materially reduces or eliminates exposure:

  • Disable public sign-up: set MONETR_ALLOW_SIGN_UP=false so only operator-trusted users can reach the vulnerable
    endpoint. Recommended in general for internet-exposed self-hosted deployments.
  • Disable Lunch Flow entirely: set lunchFlow.enabled: false in your config file. The endpoints will return 404 for
    all callers.
  • Network-level egress restriction: restrict outbound HTTP egress from the monetr pod/container to only
    lunchflow.app (or whichever legitimate Lunch Flow hosts you use). Blocks the SSRF primitive regardless of
    application-layer validation.
  • On AWS EC2 specifically: enforce IMDSv2 on the instance. This eliminates the cloud-metadata exfil path even if the
    SSRF primitive remains reachable.

References

@elliotcourant elliotcourant published to monetr/monetr Apr 18, 2026
Published to the GitHub Advisory Database Apr 22, 2026
Reviewed Apr 22, 2026
Last updated Apr 22, 2026

Severity

High

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 High
Integrity None
Availability Low
Subsequent System Impact Metrics
Confidentiality High
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:H/VI:N/VA:L/SC:H/SI:N/SA:N

EPSS score

Weaknesses

Generation of Error Message Containing Sensitive Information

The product generates an error message that includes sensitive information about its environment, users, or associated data. Learn more on MITRE.

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. Learn more on MITRE.

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-2026-41644

GHSA ID

GHSA-29v9-frvh-c426

Source code

Credits

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