Rasa Pro is a framework for building scalable, dynamic conversational AI assistants that integrate large language models (LLMs). A vulnerability has been identified in Rasa Pro where voice connectors in Rasa Pro do not properly implement authentication even when a token is configured in the credentials.yml file. This could allow an attacker to submit voice data to the Rasa Pro assistant from an unauthenticated source. This issue has been patched for audiocodes, audiocodes_stream, and genesys connectors in versions 3.9.20, 3.10.19, 3.11.7 and 3.12.6.
This vulnerability carries a MEDIUM severity rating with a CVSS v3.1 score of 6.5, indicating it can be exploited remotely over the network with relatively low complexity without requiring user interaction and does not require pre-existing privileges . The vulnerability impacts limited integrity, and limited availability for affected systems.
Reported in 2025, this vulnerability emerged during an era marked by increased sophistication in supply chain attacks, cloud infrastructure vulnerabilities, and software-as-a-service (SaaS) security challenges. Security practices during this period emphasized zero-trust architectures, container security, and API protection.
2025-04-18T20:15:16.670
2025-04-21T14:23:45.950
Awaiting Analysis
CVSSv3.1: 6.5 (MEDIUM)
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