CVE-2024-49375
What it is
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.
At a glance
- Exploitability
- Can be exploited over the network without logging in. High risk of data exposure, data tampering, service disruption.
- Exploit odds
- 0.9% chance of exploitation in the next 30 days (EPSS).
- Fix
- A patch, advisory or fixed version is referenced. Upgrade or apply it.
Timeline
- PublishedDisclosed publicly on CVE.org and NVD
- Last updatedMost recent change to the record
Details
- Published
- Last modified
- Exploit probability
- 0.9% · EPSS, next 30 days
- Weakness
- CWE-94 · Code injection
- Record status
- Deferred
Attack profile CVSS 3.1 · 9.0
- Attack vector
- Network
- Complexity
- High
- Privileges needed
- None
- User interaction
- None
- Scope
- Changed
- Confidentiality
- High
- Integrity
- High
- Availability
- High
Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H