MLflow 1.1.0 deserialization

CVSS Meta Temp Score
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Current Exploit Price (≈)
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CTI Interest Score
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8.8$0-$5k0.00

Summaryinfo

A vulnerability, which was classified as very critical, has been found in MLflow 1.1.0. This issue affects some unknown processing. Performing a manipulation results in deserialization. This vulnerability is identified as CVE-2024-37053. The attack can be initiated remotely. There is not any exploit available.

Detailsinfo

A vulnerability, which was classified as very critical, was found in MLflow 1.1.0. This affects an unknown functionality. The manipulation with an unknown input leads to a deserialization vulnerability. CWE is classifying the issue as CWE-502. The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid. This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.

It is possible to read the advisory at hiddenlayer.com. This vulnerability is uniquely identified as CVE-2024-37053 since 05/31/2024. The exploitability is told to be easy. It is possible to initiate the attack remotely. No form of authentication is needed for exploitation. It demands that the victim is doing some kind of user interaction. The technical details are unknown and an exploit is not publicly available. The pricing for an exploit might be around 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.

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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-2024-37053 (🔍)
GCVE (CVE): GCVE-0-2024-37053
GCVE (VulDB): GCVE-100-267051

Entryinfo

Created: 06/04/2024 15:10
Updated: 03/26/2025 09:56
Changes: 06/04/2024 15:10 (59), 03/26/2025 09:56 (4)
Complete: 🔍
Cache ID: 216::103

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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