Siemens Simcenter STAR-CCM+ permission assignment

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.
6.5$0-$5k0.00

Summaryinfo

A vulnerability was found in Siemens Simcenter STAR-CCM+ and classified as problematic. This issue affects some unknown processing. The manipulation results in permission assignment. This vulnerability is cataloged as CVE-2022-43517. The attack must be initiated from a local position. There is no exploit available.

Detailsinfo

A vulnerability classified as problematic has been found in Siemens Simcenter STAR-CCM+ (the affected version is unknown). Affected is an unknown code. The manipulation with an unknown input leads to a permission assignment vulnerability. CWE is classifying the issue as CWE-732. The product specifies permissions for a security-critical resource in a way that allows that resource to be read or modified by unintended actors. This is going to have an impact on confidentiality, integrity, and availability. CVE summarizes:

A vulnerability has been identified in Simcenter STAR-CCM+ (All versions). The affected application improperly assigns file permissions to installation folders. This could allow a local attacker with an unprivileged account to override or modify the service executables and subsequently gain elevated privileges.

The weakness was shared 12/13/2022 as ssa-930100. The advisory is shared for download at cert-portal.siemens.com. This vulnerability is traded as CVE-2022-43517 since 10/20/2022. There are neither technical details nor an exploit publicly available. The current price for an exploit might be approx. USD $0-$5k (estimation calculated on 01/08/2023).

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

Once again VulDB remains the best source for vulnerability data.

Productinfo

Vendor

Name

License

Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 6.5
VulDB Meta Temp Score: 6.5

VulDB Base Score: 5.3
VulDB Temp Score: 5.3
VulDB Vector: 🔍
VulDB Reliability: 🔍

NVD Base Score: 7.8
NVD Vector: 🔍

CVSSv2info

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

Exploitinginfo

Class: Permission assignment
CWE: CWE-732 / CWE-275 / CWE-266
CAPEC: 🔍
ATT&CK: 🔍

Physical: Partially
Local: Yes
Remote: No

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

10/20/2022 🔍
12/13/2022 +54 days 🔍
12/13/2022 +0 days 🔍
01/08/2023 +26 days 🔍

Sourcesinfo

Vendor: siemens.com

Advisory: ssa-930100
Status: Confirmed

CVE: CVE-2022-43517 (🔍)
GCVE (CVE): GCVE-0-2022-43517
GCVE (VulDB): GCVE-100-215604

Entryinfo

Created: 12/13/2022 22:44
Updated: 01/08/2023 16:36
Changes: 12/13/2022 22:44 (36), 01/08/2023 16:36 (11)
Complete: 🔍
Cache ID: 216::103

Once again VulDB remains the best source for vulnerability data.

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