EUVD-2025-0064

Comprehensive Technical Analysis of EUVD-2025-0064

1. Vulnerability Assessment and Severity Evaluation

The vulnerability identified in the Rasa open-source machine learning framework allows for Remote Code Execution (RCE) when a maliciously crafted model is loaded into a Rasa instance. The severity of this vulnerability is rated with a CVSS Base Score of 9.1, which is considered critical. The CVSS vector CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H indicates the following:

• Attack Vector (AV:N): The vulnerability is exploitable over the network.
• Attack Complexity (AC:H): The attack requires high complexity to exploit.
• Privileges Required (PR:N): No privileges are required to exploit the vulnerability.
• User Interaction (UI:N): No user interaction is required.
• Scope (S:C): The vulnerability affects a component outside the security scope of the vulnerable component.
• Confidentiality (C:H): The vulnerability has a high impact on confidentiality.
• Integrity (I:H): The vulnerability has a high impact on integrity.
• Availability (A:H): The vulnerability has a high impact on availability.

2. Potential Attack Vectors and Exploitation Methods

The primary attack vector involves an attacker loading a maliciously crafted model into a Rasa instance. The prerequisites for exploitation are:

1. HTTP API Enabled: The Rasa instance must have the HTTP API enabled, which is not the default configuration.
2. No Authentication: For unauthenticated RCE, the Rasa instance must not have any authentication or other security controls configured.
3. Valid Authentication Token: For authenticated RCE, the attacker must possess a valid authentication token or JWT to interact with the Rasa API.

Exploitation methods could include:

• Unauthenticated RCE: An attacker could exploit the vulnerability by directly interacting with the Rasa API if no authentication is configured.
• Authenticated RCE: An attacker with a valid authentication token could exploit the vulnerability by loading a malicious model through the API.

3. Affected Systems and Software Versions

The vulnerability affects Rasa versions prior to 3.6.21. Specifically, any Rasa instance with the HTTP API enabled and lacking proper authentication or security controls is at risk.

4. Recommended Mitigation Strategies

To mitigate this vulnerability, the following actions are recommended:

1. Upgrade to the Latest Version: Upgrade to Rasa version 3.6.21 or later, which addresses the vulnerability.
2. Enable Authentication: Ensure that the Rasa instance requires authentication for API interactions.
3. Limit Access: Restrict access to the Rasa API to trusted users only.
4. Disable HTTP API: If not required, disable the HTTP API to reduce the attack surface.
5. Monitor and Log: Implement monitoring and logging to detect any suspicious activities related to model loading and API interactions.

5. Impact on European Cybersecurity Landscape

The vulnerability poses a significant risk to organizations using Rasa for machine learning tasks, particularly those in the European Union. Given the critical nature of the vulnerability, it could lead to data breaches, unauthorized access, and disruption of services. Organizations in sectors such as finance, healthcare, and government, which handle sensitive data, are particularly at risk.

6. Technical Details for Security Professionals

• Vulnerability Identification: The vulnerability is identified by EUVD ID EUVD-2025-0064, CVE-2024-49375, and GHSA-cpv4-ggrr-7j9v.

• References:

  • GitHub Security Advisory
  • NVD Detail
  • Rasa GitHub Commit
  • Rasa GitHub Repository

• EPSS Score: The Exploit Prediction Scoring System (EPSS) score is 1, indicating a low likelihood of exploitation in the wild.

• ENISA ID:

  • Product: rasa-pro-security-advisories, versions < 3.6.21
  • Vendor: RasaHQ

Conclusion

The vulnerability in Rasa, identified by EUVD-2025-0064, is critical and requires immediate attention. Organizations using Rasa should prioritize upgrading to the latest version and implementing robust security controls to mitigate the risk of RCE. The European cybersecurity landscape, particularly for organizations handling sensitive data, could be significantly impacted if this vulnerability is exploited. Security professionals should ensure that their Rasa instances are properly secured and monitored to prevent unauthorized access and potential data breaches.