opengeos streamlit-geospatial up to 380 1_????_Timelapse.py eval palette input validation

CVSS Meta Temp Score
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CTI Interest Score
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9.7$0-$5k0.00

Summaryinfo

A vulnerability was found in opengeos streamlit-geospatial up to 380. It has been classified as very critical. Affected by this issue is the function eval of the file pages/1_????_Timelapse.py. This manipulation of the argument palette causes input validation. This vulnerability is registered as CVE-2024-41112. Remote exploitation of the attack is possible. No exploit is available. To fix this issue, it is recommended to deploy a patch.

Detailsinfo

A vulnerability has been found in opengeos streamlit-geospatial up to 380 and classified as very critical. Affected by this vulnerability is the function eval of the file pages/1_????_Timelapse.py. The manipulation of the argument palette with an unknown input leads to a input validation vulnerability. The CWE definition for the vulnerability is CWE-20. The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly. As an impact it is known to affect confidentiality, integrity, and availability. The summary by CVE is:

streamlit-geospatial is a streamlit multipage app for geospatial applications. Prior to commit c4f81d9616d40c60584e36abb15300853a66e489, the palette variable in `pages/1_????_Timelapse.py` takes user input, which is later used in the `eval()` function on line 380, leading to remote code execution. Commit c4f81d9616d40c60584e36abb15300853a66e489 fixes this issue.

It is possible to read the advisory at securitylab.github.com. This vulnerability is known as CVE-2024-41112 since 07/15/2024. The exploitation appears to be easy. The attack can be launched remotely. The exploitation doesn't need any form of authentication. Technical details of the vulnerability are known, but there is no available exploit. The pricing for an exploit might be around USD $0-$5k at the moment (estimation calculated on 08/26/2024).

Applying the patch c4f81d9616d40c60584e36abb15300853a66e489 is able to eliminate this problem. The bugfix is ready for download at github.com.

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

Productinfo

Vendor

Name

Version

License

Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 9.8
VulDB Meta Temp Score: 9.7

VulDB Base Score: 9.8
VulDB Temp Score: 9.4
VulDB Vector: 🔍
VulDB Reliability: 🔍

NVD Base Score: 9.8
NVD Vector: 🔍

CNA Base Score: 9.8
CNA Vector (GitHub_M): 🔍

CVSSv2info

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

Exploitinginfo

Class: Input validation
CWE: 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: Patch
Status: 🔍

0-Day Time: 🔍

Patch: c4f81d9616d40c60584e36abb15300853a66e489

Timelineinfo

07/15/2024 🔍
07/26/2024 +11 days 🔍
07/26/2024 +0 days 🔍
08/26/2024 +31 days 🔍

Sourcesinfo

Product: github.com

Advisory: GHSL-2024-100
Status: Confirmed

CVE: CVE-2024-41112 (🔍)
GCVE (CVE): GCVE-0-2024-41112
GCVE (VulDB): GCVE-100-272515

Entryinfo

Created: 07/26/2024 22:55
Updated: 08/26/2024 22:09
Changes: 07/26/2024 22:55 (67), 07/30/2024 12:01 (1), 08/26/2024 22:09 (11)
Complete: 🔍
Cache ID: 216::103

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

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