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CVE-2024-49375

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Date: January 14, 2025

Open source machine learning framework. A vulnerability has been identified in Rasa that enables an attacker who has the ability to load a maliciously crafted model remotely into a Rasa instance to achieve Remote Code Execution. The prerequisites for this are: 1. The HTTP API must be enabled on the Rasa instance eg with "--enable-api". This is not the default configuration. 2. For unauthenticated RCE to be exploitable, the user must not have configured any authentication or other security controls recommended in our documentation. 3. For authenticated RCE, the attacker must posses a valid authentication token or JWT to interact with the Rasa API. This issue has been addressed in rasa version 3.6.21 and all users are advised to upgrade. Users unable to upgrade should ensure that they require authentication and that only trusted users are given access.

Severity Score

Severity Score

Weakness Type (CWE)

Improper Control of Generation of Code ('Code Injection')

CWE-94

Deserialization of Untrusted Data

CWE-502

Top Fix

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Upgrade Version

Upgrade to version rasa - no_fix;rasa-pro - 3.8.18;rasa-pro - 3.9.16;rasa-pro - 3.10.12

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CVSS v3.1

Base Score:
Attack Vector (AV): NETWORK
Attack Complexity (AC): HIGH
Privileges Required (PR): NONE
User Interaction (UI): NONE
Scope (S): CHANGED
Confidentiality (C): HIGH
Integrity (I): HIGH
Availability (A): HIGH

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