Cross-Site Request Forgery (CSRF)

CVE-2024-3083

Summary

A “CWE-352: Cross-Site Request Forgery (CSRF)” can be exploited by remote attackers to perform state-changing operations with administrative privileges by luring authenticated victims into visiting a malicious web page.

Impact

Impact associated to the vulnerability is mainly in terms of integrity, however also availability must be taken into consideration in a scenario where the CSRF is leveraged to modify the network configuration of the sensor to an invalid one.

Issue Date

July 7, 2023

Affects

Sensor Net Connect V2 (FW version 2.24)

CVE Name

CVE-2024-3083

CVSS Details

CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:L/I:H/A:H

CVSS Score

8.3

Solution

No official patch available from vendor. Implement strict access controls for the temperature monitoring infrastructure. This includes preventing regular clients from accessing the web configuration interface, thereby limiting potential points of exploitation. Conduct regular and thorough reviews of logs and user accounts on systems running the Thermoscan IP software. This will help identify and address any suspicious activities early, ensuring that any potential security breaches are caught and remediated swiftly.

Mitigations

Acknowledgements

Diego Zaffaroni of Nozomi Networks

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Research Projects

TRITON

TRITON is the first known cyberattack that directly interacted with a Safety Instrumented System (SIS). Labs reverse engineered the TriStation suite of software and delivered a report and two free tools for security researchers. This research was presented at Black Hat USA 2018.

GreyEnergy

The Labs team reverse engineered the GreyEnergy malicious document (maldoc) that leads to the installation of the malware (backdoor) on a victim’s network. Project outcomes include a report, multiple blogs and two free tools for security researchers.

IEC 62351

IEC Working Group 15 (WG15) is developing technology standards for secure-by-design power systems. Labs contributes to the standards and has demonstrated how they can be used to identify hard-to-detect cyberattacks. Research from this effort was presented at Black Hat USA 2019.

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