CVE-2026-85691 in MegaParse
Summary
by MITRE • 09/04/2026
MegaParse 0.0.55 contains an unauthenticated server-side request forgery vulnerability in the POST /v1/url endpoint that fetches caller-supplied URLs server-side. Attackers can supply internal service URLs or metadata endpoints without authentication to read their responses directly from the JSON response.
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Analysis
by VulDB Data Team • 09/04/2026
The MegaParse application version 0.0.55 is susceptible to an unauthenticated Server-Side Request Forgery vulnerability within its POST /v1/url endpoint. This security flaw arises because the server processes user-supplied URLs without implementing adequate validation or authentication mechanisms before initiating HTTP requests on behalf of the client. In a typical operation, this endpoint is designed to fetch content from external web pages for parsing and analysis purposes. However, due to insufficient input sanitization, an attacker can manipulate the URL parameter to direct the server toward internal network resources that are not intended to be accessible via public-facing interfaces. This misconfiguration allows remote attackers to bypass authentication controls entirely, as no credentials or tokens are required to exploit this specific vector.
The technical nature of this vulnerability falls under CWE-918, which classifies Server-Side Request Forgery (SSRF). The core issue lies in the application's failure to restrict the destination addresses that can be resolved and accessed by the server-side code. By supplying internal service URLs or cloud provider metadata endpoints as input, an attacker forces the vulnerable server to act as a proxy. This behavior enables the retrieval of sensitive data from services such as Kubernetes API servers, internal databases, microservices, or instance metadata stores like AWS EC2 Metadata Service (IMDS). The attack is particularly dangerous because it leverages the trust relationship between the application and its underlying infrastructure, effectively turning the server into an instrument for lateral movement within a network environment.
The operational impact of this vulnerability is significant, primarily revolving around unauthorized data access and potential compromise of internal systems. Since the response from the forged request is returned directly in the JSON output to the attacker, sensitive information such as configuration files, database credentials, or cloud instance metadata can be exfiltrated with ease. In cloud environments, accessing metadata endpoints often yields temporary security credentials for attached roles, which could grant an attacker elevated privileges within that environment. Furthermore, this vulnerability facilitates network reconnaissance by allowing attackers to map internal services and identify other potential attack surfaces based on the responses received from different internal hosts. This aligns with ATT&CK technique T1598, specifically Phishing for Inbound Information or Gathering Victim Host Information through SSRF scenarios where the attacker gathers intelligence about the target's infrastructure.
To mitigate this vulnerability, immediate remediation steps should focus on implementing strict input validation and access controls at both the application and network levels. The most effective technical fix involves whitelisting allowed domains or IP ranges for the URL fetching functionality, ensuring that only public internet resources are accessible while blocking requests to private IP address spaces such as 10.x.x.x, 172.16.x.x through 172.31.x.x, and 192.168.x.x. Additionally, developers should implement DNS rebinding protection mechanisms and ensure that the server does not follow redirects to internal addresses if the initial request was made to an external domain. From a network architecture perspective, deploying web application firewalls can help detect and block suspicious outbound requests originating from the application layer. Regular security audits and static code analysis tools configured to flag SSRF patterns are also recommended to prevent similar issues in future releases of the MegaParse software.