CVE-2026-102923 in SparkyFitness
Summary
by MITRE • 10/16/2026
SparkyFitness is a self-hosted, AI-powered health and fitness tracker for families. Prior to 1.6.0, SparkyFitnessServer/services/chatService.ts and SparkyFitnessServer/services/labelScanService.ts do not validate destinations supplied in custom AI service settings. An authenticated user saves a custom AI service URL and invokes an affected AI flow. The user can save a custom AI service URL and trigger an outbound request. Successful exploitation can send server-side POST requests with a controlled bearer value, probe internal services, and disclose the AI system prompt. This issue is fixed in version 1.6.0.
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Analysis
by VulDB Data Team • 10/16/2026
The vulnerability identified in SparkyFitness versions prior to 1.6.0 represents a critical Server-Side Request Forgery (SSRF) flaw rooted in insufficient input validation within the application's AI service configuration modules. Specifically, the files chatService.ts and labelScanService.ts fail to rigorously validate or sanitize destination URLs provided by authenticated users when configuring custom AI services. This architectural oversight allows an attacker who has obtained valid authentication credentials for a SparkyFitness account to inject maliciously crafted URL destinations into the system's settings interface. By saving these configurations, the user effectively instructs the server to initiate outbound network requests to arbitrary endpoints controlled by the attacker or targeted internal infrastructure.
From a technical perspective, this flaw exploits the trust relationship between the application and its own backend services. When an authenticated user triggers an affected AI flow after configuring the malicious URL, the SparkyFitness server acts as a proxy, forwarding HTTP POST requests to the specified destination. Crucially, these outbound requests include headers that are derived from or controlled by the attacker's input, such as custom bearer tokens or authentication values. This capability transforms what might otherwise be a simple SSRF into a more potent attack vector capable of bypassing internal security controls that rely on header-based authentication mechanisms. The vulnerability aligns with CWE-918, which classifies Server-Side Request Forgery, and is further characterized by the lack of URL scheme validation and domain allowlisting typically required to mitigate such risks.
The operational impact of this vulnerability extends beyond simple network reconnaissance. An attacker can leverage this flaw to probe internal services that are not exposed to the public internet but remain accessible within the server's local network or container environment. By manipulating request headers, specifically by injecting controlled bearer values, an adversary may authenticate against other backend microservices, APIs, or administrative interfaces running on the same host or in adjacent network segments. This can lead to unauthorized access to sensitive internal systems, data exfiltration from protected databases, and lateral movement within the deployment environment. Furthermore, if the targeted AI service returns error messages or debug information, it may inadvertently disclose the system prompt of the underlying large language model, revealing proprietary logic, instructions, or confidential context embedded in the application's configuration.
This attack pattern is consistent with MITRE ATT&CK technique T1598, specifically Phishing for Information within Cloud Environments, as well as T1046, Network Service Discovery, when used to map internal service topology. The ability to send server-side POST requests with controlled headers also touches upon aspects of credential access and privilege escalation if the targeted services have higher security privileges than the SparkyFitness application itself. For organizations relying on self-hosted instances of SparkyFitness for family health tracking, this vulnerability poses a significant risk to both data privacy and infrastructure integrity, as it allows an authenticated user to pivot from their limited account permissions into broader network access.
To mitigate this vulnerability, immediate action is required to upgrade the SparkyFitness server to version 1.6.0 or later, where the developers have implemented proper validation for custom AI service URLs. In environments where upgrading is not immediately feasible, administrators should implement strict egress filtering at the firewall level to restrict outbound connections from the application host to only known and necessary external domains. Additionally, deploying a reverse proxy with URL sanitization capabilities can help intercept and validate requests before they reach the backend services. It is also advisable to enforce least-privilege principles for service accounts used by the AI modules, ensuring that even if an SSRF attack succeeds, the compromised identity lacks permissions to access sensitive internal resources or modify critical configurations. Regular security audits of input validation logic in all user-controlled configuration fields are essential to prevent similar flaws from being introduced in future updates.