Sandbox Escape in alf.io via Rhino Java Reflection

Executive Summary

This vulnerability exists in alf.io, an open source ticket reservation system. Before version 2.0-M5-2606, the extension script engine allowed an authenticated administrator to escape the intended sandbox environment and execute arbitrary operating system commands on the server.

The extension system was designed to run restricted JavaScript within a sandboxed Rhino environment. However, due to an unguarded injected Java object called `returnClass` and an incomplete abstract syntax tree (AST) blocklist, the sandbox could be fully escaped using Java reflection without triggering validation errors.

This means that an attacker with administrator privileges could bypass security restrictions and run any OS-level commands on the server hosting alf.io.

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Impact Analysis

This vulnerability can have severe impacts because it allows an authenticated administrator to execute arbitrary operating system commands on the server.

• Complete compromise of the server hosting alf.io.
• Potential unauthorized access to sensitive data stored or processed by the server.
• Disruption of services provided by alf.io, such as ticket reservations for conferences and events.
• Possibility for attackers to install malware, create backdoors, or pivot to other parts of the network.

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Mitigation Strategies

To mitigate this vulnerability, you should upgrade alf.io to version 2.0-M5-2606 or later, as this version patches the sandbox escape issue.

Since the vulnerability allows an authenticated administrator to execute arbitrary OS commands via the extension script engine, restricting administrator access and monitoring for suspicious activity until the upgrade is applied is also advisable.

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Compliance Impact

This vulnerability allows an authenticated administrator to execute arbitrary operating system commands on the server, which can lead to a complete compromise of the system's confidentiality, integrity, and availability.

Such a compromise could result in unauthorized access to sensitive data, including personal or protected health information, thereby potentially violating compliance requirements under standards like GDPR and HIPAA.

Because the vulnerability enables remote code execution with high privileges and scope change, organizations using affected versions of alf.io may face increased risk of data breaches and regulatory non-compliance if the issue is not patched.

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Detection Guidance

This vulnerability can be detected by checking if your alf.io installation is running a vulnerable version (versions ≤ 2.0-M5-2509-1) and by monitoring for suspicious activity related to the extension script engine.

Specifically, the vulnerability is triggered when an extension script is saved via the POST /admin/api/extensions endpoint. An attacker can execute arbitrary OS commands using Java reflection through the injected returnClass object.

To detect exploitation attempts or verify if the vulnerability exists, you can look for unusual commands executed on the server or check logs for unexpected output in invoice number fields or extension logs.

A proof-of-concept uses the command 'id' executed via java.lang.Runtime.getRuntime().exec(), so you might search logs or outputs for this or similar commands.

Suggested commands to detect potential exploitation attempts include:

• Check the alf.io version to confirm if it is vulnerable.
• Monitor HTTP POST requests to /admin/api/extensions for suspicious payloads.
• Search server logs for unusual command outputs, such as the output of 'id' or other shell commands.
• Use commands like `grep -i 'id' /path/to/alfio/logs/*` to find evidence of command execution.
• Audit running processes or recent commands on the server for unexpected activity.

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