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Libredesk has a SSRF Vulnerability in Webhooks

Moderate severity GitHub Reviewed Published Feb 15, 2026 in abhinavxd/libredesk • Updated Feb 20, 2026

Package

gomod github.com/abhinavxd/libredesk (Go)

Affected versions

< 1.0.2-0.20260215211005-727213631ce6

Patched versions

1.0.2-0.20260215211005-727213631ce6

Description

Date: 2025-12-07
Vulnerability: Server-Side Request Forgery (SSRF)
Component: Webhooks Module

Executive Summary

A critical security vulnerability exists in the LibreDesk Webhooks module that allows an authenticated "Application Admin" to compromise the underlying cloud infrastructure or internal corporate network where this service is being hosted.

The application fails to validate destination URLs for webhooks. This allows an attacker to force the server to make HTTP requests to arbitrary internal destinations.

Confirmed Attack Vectors

1. Internal Port Scanning (Network Mapping)

Attackers can map the internal network by observing the difference between successful connections and connection errors. This works even if the response body is not returned.

Proof of Exploitation (from Server Logs):

  • Open Port (8890): The server connects successfully. 
    timestamp=... level=info message="webhook delivered successfully" ... status_code=200
  • Closed Port (8891): The server fails to connect. 
    timestamp=... level=error message="webhook delivery failed" ... error="... connect: connection refused"

Impact: An attacker can identify running services (databases, caches, internal apps) on the local network (e.g., localhost, 192.168.x.x).

2. Information Leakage (Error-Based)

If the internal service returns a non-2xx response (e.g., 403 Forbidden, 404 Not Found, 500 Error), the application logs the full response body.

Proof of Exploitation (from Server Logs):

timestamp=... level=error message="webhook delivery failed" ... 
response="{\"secret_key\": \"xxx123\", \"role\": \"admin\"}"

Impact: An attacker can extract sensitive data by targeting endpoints that return errors or by forcing errors on internal services.

Technical Root Cause

  1. Missing Input Validation: cmd/webhooks.go only checks if the URL is empty, not if it resolves to a private IP.
  2. Unrestricted HTTP Client: internal/webhook/webhook.go uses a default http.Client that follows redirects and connects to any IP.
  3. Verbose Error Logging: The application logs the full response body on failure, creating a side-channel for data exfiltration.

Remediation Required

To prevent this, the application must implement Defense in Depth:

  1. Input Validation: Block URLs resolving to private IP ranges (RFC 1918) and Link-Local addresses.
  2. Safe HTTP Client: Use a custom http.Transport that verifies the destination IP address after DNS resolution to prevent DNS rebinding attacks.

References

@abhinavxd abhinavxd published to abhinavxd/libredesk Feb 15, 2026
Published to the GitHub Advisory Database Feb 18, 2026
Reviewed Feb 18, 2026
Published by the National Vulnerability Database Feb 20, 2026
Last updated Feb 20, 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 None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality Low
Integrity Low
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:N/UI:N/VC:N/VI:N/VA:N/SC:L/SI:L/SA:N

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(12th percentile)

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.

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-2026-26957

GHSA ID

GHSA-wgm6-9rvv-3438

Source code

Credits

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