9

CVE-2024-49375

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.
Verknüpft mit AI von unstrukturierten Daten zu bestehenden CPE der NVD
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Daten sind bereitgestellt durch das CVE Programm von einer CVE Numbering Authority (CNA) (Unstrukturiert).
HerstellerRasaHQ
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Produkt rasa-pro-security-advisories
Version < 3.6.21
Status affected
Zu dieser CVE wurde keine CISA KEV oder CERT.AT-Warnung gefunden.
EPSS Metriken
Typ Quelle Score Percentile
EPSS FIRST.org 3.29% 0.87
CVSS Metriken
Quelle Base Score Exploit Score Impact Score Vector String
security-advisories@github.com 9 2.2 6
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
CWE-502 Deserialization of Untrusted Data

The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.

CWE-94 Improper Control of Generation of Code ('Code Injection')

The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.