MLflow 2.0.0rc0 Tensorflow Model deserialization

CVSS Meta Temp Score
CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.
Current Exploit Price (≈)
Our analysts are monitoring exploit markets and are in contact with vulnerability brokers. The range indicates the observed or calculated exploit price to be seen on exploit markets. A good indicator to understand the monetary effort required for and the popularity of an attack.
CTI Interest Score
Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
8.8$0-$5k0.00

Summaryinfo

A vulnerability described as very critical has been identified in MLflow 2.0.0rc0. This impacts an unknown function of the component Tensorflow Model Handler. Executing a manipulation can lead to deserialization. The identification of this vulnerability is CVE-2024-37057. The attack may be launched remotely. There is no exploit available.

Detailsinfo

A vulnerability has been found in MLflow 2.0.0rc0 and classified as very critical. This vulnerability affects an unknown code block of the component Tensorflow Model Handler. The manipulation with an unknown input leads to a deserialization vulnerability. The CWE definition for the vulnerability is CWE-502. The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid. As an impact it is known to affect confidentiality, integrity, and availability. CVE summarizes:

Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.0.0rc0 or newer, enabling a maliciously uploaded Tensorflow model to run arbitrary code on an end user’s system when interacted with.

The advisory is available at hiddenlayer.com. This vulnerability was named CVE-2024-37057 since 05/31/2024. The exploitation appears to be easy. The attack can be initiated remotely. No form of authentication is required for a successful exploitation. Successful exploitation requires user interaction by the victim. The technical details are unknown and an exploit is not available. The structure of the vulnerability defines a possible price range of USD $0-$5k at the moment (estimation calculated on 06/04/2024).

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

If you want to get best quality of vulnerability data, you may have to visit VulDB.

Productinfo

Name

Version

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 8.8
VulDB Meta Temp Score: 8.8

VulDB Base Score: 8.8
VulDB Temp Score: 8.8
VulDB Vector: 🔍
VulDB Reliability: 🔍

CNA Base Score: 8.8
CNA Vector (HiddenLayer): 🔍

CVSSv2info

AVACAuCIA
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VectorComplexityAuthenticationConfidentialityIntegrityAvailability
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍

Exploitinginfo

Class: Deserialization
CWE: CWE-502 / CWE-20
CAPEC: 🔍
ATT&CK: 🔍

Physical: No
Local: No
Remote: Yes

Availability: 🔍
Status: Not defined

EPSS Score: 🔍
EPSS Percentile: 🔍

Price Prediction: 🔍
Current Price Estimation: 🔍

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔍

Timelineinfo

05/31/2024 🔍
06/04/2024 +4 days 🔍
06/04/2024 +0 days 🔍
03/26/2025 +295 days 🔍

Sourcesinfo

Advisory: hiddenlayer.com
Status: Not defined

CVE: CVE-2024-37057 (🔍)
GCVE (CVE): GCVE-0-2024-37057
GCVE (VulDB): GCVE-100-267034

Entryinfo

Created: 06/04/2024 15:04
Updated: 03/26/2025 11:01
Changes: 06/04/2024 15:04 (60), 03/26/2025 11:01 (4)
Complete: 🔍
Cache ID: 216::103

If you want to get best quality of vulnerability data, you may have to visit VulDB.

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