Executive Summary
| Informations | |||
|---|---|---|---|
| Name | CVE-2024-49375 | First vendor Publication | 2025-01-14 |
| Vendor | Cve | Last vendor Modification | 2025-01-14 |
Security-Database Scoring CVSS v3
| Cvss vector : N/A | |||
|---|---|---|---|
| Overall CVSS Score | NA | ||
| Base Score | NA | Environmental Score | NA |
| impact SubScore | NA | Temporal Score | NA |
| Exploitabality Sub Score | NA | ||
| Calculate full CVSS 3.0 Vectors scores | |||
Security-Database Scoring CVSS v2
| Cvss vector : | |||
|---|---|---|---|
| Cvss Base Score | N/A | Attack Range | N/A |
| Cvss Impact Score | N/A | Attack Complexity | N/A |
| Cvss Expoit Score | N/A | Authentication | N/A |
| Calculate full CVSS 2.0 Vectors scores | |||
Detail
| 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. |
Original Source
| Url : http://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2024-49375 |
CWE : Common Weakness Enumeration
| % | Id | Name |
|---|---|---|
| 50 % | CWE-502 | Deserialization of Untrusted Data |
| 50 % | CWE-94 | Failure to Control Generation of Code ('Code Injection') |
Sources (Detail)
| Source | Url |
|---|
Alert History
| Date | Informations |
|---|---|
| 2025-01-15 00:20:33 |
|
