What is the official website of Marubeni Green Power - Thailand ?

The official website of Marubeni Green Power - Thailand is https://www.marubeni-mgp.com/.

What is Marubeni Green Power - Thailand's cybersecurity risk score?

Marubeni Green Power - Thailand has an AI-generated cybersecurity risk score of 753 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has Marubeni Green Power - Thailand experienced?

According to Rankiteo, Marubeni Green Power - Thailand currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.

Has Marubeni Green Power - Thailand been affected by any supply chain cyber incidents ?

According to Rankiteo, Marubeni Green Power - Thailand has not been affected by any supply chain cyber incidents, and no incident IDs are currently listed for the organization.

Does Marubeni Green Power - Thailand have SOC 2 Type 1 certification ?

According to Rankiteo, Marubeni Green Power - Thailand is not certified under SOC 2 Type 1.

Does Marubeni Green Power - Thailand have SOC 2 Type 2 certification ?

According to Rankiteo, Marubeni Green Power - Thailand does not hold a SOC 2 Type 2 certification.

Does Marubeni Green Power - Thailand comply with GDPR ?

According to Rankiteo, Marubeni Green Power - Thailand is not listed as GDPR compliant.

Does Marubeni Green Power - Thailand have PCI DSS certification ?

According to Rankiteo, Marubeni Green Power - Thailand does not currently maintain PCI DSS compliance.

Does Marubeni Green Power - Thailand comply with HIPAA ?

According to Rankiteo, Marubeni Green Power - Thailand is not compliant with HIPAA regulations.

Does Marubeni Green Power - Thailand have ISO 27001 certification ?

According to Rankiteo,Marubeni Green Power - Thailand is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.

Which industry does Marubeni Green Power - Thailand operate in ?

Marubeni Green Power - Thailand operates primarily in the Solar Electric Power Generation industry.

How many employees does Marubeni Green Power - Thailand have ?

Marubeni Green Power - Thailand employs approximately 14 people worldwide.

Does Marubeni Green Power - Thailand own any subsidiaries ?

Marubeni Green Power - Thailand presently has no subsidiaries across any sectors.

How many LinkedIn followers does Marubeni Green Power - Thailand have ?

Marubeni Green Power - Thailand's official LinkedIn profile has approximately 669 followers.

What is the NAICS classification code for Marubeni Green Power - Thailand ?

Marubeni Green Power - Thailand is classified under the NAICS code 221114, which corresponds to Solar Electric Power Generation.

Does Marubeni Green Power - Thailand have a Crunchbase profile ?

No, Marubeni Green Power - Thailand does not have a profile on Crunchbase.

Does Marubeni Green Power - Thailand have a LinkedIn profile ?

Yes, Marubeni Green Power - Thailand maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/marubeni-green-power.

How many cybersecurity incidents has Marubeni Green Power - Thailand experienced ?

As of June 24, 2026, Rankiteo reports that Marubeni Green Power - Thailand has experienced 2 cybersecurity incidents.

How many peer or competitor companies does Marubeni Green Power - Thailand have ?

Marubeni Green Power - Thailand has an estimated 220 peer or competitor companies worldwide.

What types of cybersecurity incidents has Marubeni Green Power - Thailand faced ?

Incident Types: The types of cybersecurity incidents that have occurred include Breach.

NEWRankiteo Cyber Underwriting Desktop - Score, price, and bind from your desktop

WindowsmacOSLinux

Download

Badge your company to reduce your risk score and your cyber insurance costs!

Link verified badges to your company page to build trust with insurers and customers.

Apply now and get your badge!

Internal validation & live display

Insurers and partners see a safer profile

Faster underwriting decisions

Trusted by insurers. Chosen by leaders.

Proud contributor to the Society of Actuaries.

MGPT

Boost Score +25 with badge (5 left)

753

/1000

Fair

778

/1000

Fair

Marubeni Green Power - Thailand Vendor Cyber Rating & Cyber Score

marubeni-mgp.com

Add Your Compliance Badge

Marubeni Green Power (MGP) is a subsidiary of Marubeni Corporation, an international versatile energy solution provider. Founded on June 14, 2021. We have been established to provide renewable energy solutions to customers in Thailand and Vietnam. We are Proving and Service of Solar for “Private PPA” and "EPC" solutions to industrial and commercial customers in seven countries (Thailand, Vietnam, Japan, Taiwan, Philippines, Singapore and Mexico). In addition, Marubeni Green provided Solar Rooftop power generation system, Solar Small Power Grid System (Microgrid), the Energy Storage System (ESS), Electric vehicle (EV) and EV Charging Station. We are a part of Marubeni group and deliver our services by full support of global resources of

MGPT A.I CyberSecurity Scoring

Scoring History

MGPT

Marubeni Green Power - Thailand CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

Marubeni Green Powe...

Breach

11/2022

COL21151222

Marubeni Green Powe...

Breach

3/2022

COL420072725

Loading…

A.I.

MGPT Company Scoring based on AI Models

Cyber Incidents Likelihood 3 - 6 - 9 months

Actual

Prediction

Incident Predictions locked

Access Monitoring Plan

A.I Risk Score Likelihood 3 - 6 - 9 months

Actual

Prediction A

Prediction B

Prediction C

Prediction D

A.I. Risk Score Predictions locked

Access Monitoring Plan

Loading…

Underwriter Stats for MGPT

Incidents vs Solar Electric Power Generation Industry Avg (This Year)

No incidents recorded for Marubeni Green Power - Thailand in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Marubeni Green Power - Thailand in 2026.

Incident Types MGPT vs Solar Electric Power Generation Industry Avg (This Year)

No incidents recorded for Marubeni Green Power - Thailand in 2026.

Incident History - MGPT (X = Date, Y = Severity)

Loading…

SUBSIDIARY

Marubeni Green Power - Thailand Subsidiaries

MGPT

Solar Electric Power Generation

Website: https://www.marubeni-mgp.com/

Company Size: 11-50 employees

Marubeni CorporationInternational Trade and Development

BJITOutsourcing and Offshoring Consulting

Maynilad Water Services, Inc.Utilities

Marubeni-Komatsu LtdMachinery Manufacturing

Marubeni-Komatsu Used EquipmentConstruction

Komatsu Hybrid Excavator HB215LC-2Construction

SmartestEnergyUtilities

SmartestEnergy UKUtilities

SmartestEnergy BusinessUtilities

SmartestEnergy AustraliaUtilities

SmartestEnergy USUtilities

DASIAviation and Aerospace Component Manufacturing

Zamine PerúMining

Orffa Animal Feed Manufacturing

Marubeni America CorporationFinancial Services

GasvalpoOil and Gas

Creekstone Farms Premium BeefFood and Beverage Manufacturing

Marubeni EuropeInternational Trade and Development

Marubeni Europe Speciality ChemicalsChemical Manufacturing

Magellan Aviation GroupAirlines and Aviation

Magellan ExpendablesAirlines and Aviation

Marubeni Citizen-Cincom Inc.Machinery Manufacturing

AquasisIT Services and IT Consulting

Aquaman IndustryAtividades dos serviços de tecnologia da informação

Swissport Japan Ltd.Airlines and Aviation

Viacore SolutionsMining

Marubeni Brasil S.A.International Trade and Development

Columbia Grain InternationalFood and Beverage Manufacturing

Power Train Technologies Chile S.A.Mining

Eastern FishFood and Beverage Manufacturing

Marubeni Middle-East and Africa Power LimitedRenewable Energy Semiconductor Manufacturing

MAXIMA MACHINERIES, INC.Wholesale Machinery

Marubeni EuropowerFinancial Services

HyBont Green Hydrogen ProjectRenewable Energy Power Generation

KiwapowerRenewable Energy Semiconductor Manufacturing

Marubeni Power International, Inc.Renewables & Environment

Marubeni Ventures Inc.Financial Services

DTDS Technology Pte Ltd., Marubeni GroupSemiconductor Manufacturing

DOLBIX CONSULTING Inc.Business Consulting and Services

Loading…

Marubeni Green Power - Thailand Similar Companies

Loading…

NEWS

Marubeni Green Power - Thailand CyberSecurity News

Latest updates, reports, and threat intel affecting the global network.

Loading…

CVE

Latest

Global CVEs (Not Company-Specific)

CVE-2026-54236

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, the fix for CVE-2026-22778, which introduced a sanitize_message helper that strips object-repr memory addresses from error messages before they reach the client, is incomplete: several response paths echo str(exc) directly to clients without calling sanitize_message. The unsanitized sites include the Anthropic API router in vllm/entrypoints/anthropic/api_router.py (the POST /v1/messages and POST /v1/messages/count_tokens handlers), the Server-Sent Events streaming converter in vllm/entrypoints/anthropic/serving.py, and the realtime speech-to-text WebSocket in vllm/entrypoints/speech_to_text/realtime/connection.py. These paths catch the exception inside the route coroutine and construct the JSONResponse themselves, bypassing the sanitizing global FastAPI exception handler, and WebSocket frames do not traverse that handler chain at all. Using the same primitive as the parent issue, an unauthenticated attacker can send malformed image bytes through the Anthropic Messages API image content parts so that PIL.Image.open raises an UnidentifiedImageError whose message contains the BytesIO object repr, leaking the heap memory address verbatim in the error.message field of the response body. This vulnerability is fixed in 0.23.1rc0.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: 5.3)

cvss3

Base Score: 5.3

Complexity: LOW

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

Impact Score

1.4

Exploitability

3.9

REFERENCES

CVE-2026-54235

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, ll temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. This vulnerability is fixed in 0.23.1rc0.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: )

cvss4

Base Score: 6.9

Complexity: LOW

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

Impact Score

Exploitability

REFERENCES

CVE-2026-54233

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, vLLM's /v1/audio/transcriptions endpoint limits compressed upload size but not decoded PCM output. A 25MB OPUS file expands to ~14.9GB of float32 PCM at decode time. This vulnerability is fixed in 0.23.1rc0.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: 6.5)

cvss3

Base Score: 6.5

Complexity: LOW

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

Impact Score

3.6

Exploitability

2.8

REFERENCES

CVE-2026-54232

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.1, the vLLM Dockerfile is vulnerable to a dependency confusion attack through the flashinfer-jit-cache package. The package is installed from a custom index (flashinfer.ai/whl/) using --extra-index-url, but the package name was not registered on PyPI, and UV_INDEX_STRATEGY="unsafe-best-match" is set globally. An attacker who registers flashinfer-jit-cache on PyPI with version 0.6.11.post2 can execute arbitrary code as root during the Docker build and backdoor every resulting container image, enabling exfiltration of all user prompts, API credentials, and model data from production vLLM deployments This vulnerability is fixed in 0.22.1.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: 8.8)

cvss3

Base Score: 8.8

Complexity: LOW

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

Impact Score

5.9

Exploitability

2.8

REFERENCES

https://github.com/vllm-project/vllm/security/advisories/GHSA-jrf6-vqxq-pjv2

CVE-2026-53923

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). From 0.5.5 until 0.23.1rc0, integer truncation of tensor dimensions in vLLM's GGUF dequantize kernels (csrc/quantization/gguf/gguf_kernel.cu) causes partial tensor processing. The output tensor is allocated at full size via torch::empty (uninitialized memory), but the dequantize CUDA kernel processes only a truncated number of elements. The unfilled portion of the output tensor retains whatever was previously in GPU memory. In multi-tenant inference deployments, this residual GPU memory may contain tensor data from other users' inference requests, constituting information disclosure. This vulnerability is fixed in 0.23.1rc0.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: )

cvss4

Base Score: 5.3

Complexity: LOW

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:L/VI:L/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

Impact Score

Exploitability

REFERENCES

Loading…

API

Access Data Using Our API

Get company history

curl -i -X GET 'https://api.rankiteo.com/underwriter-getcompany-history?
linkedin_id=axa' -H 'apikey: YOUR_API_KEY_HERE'

Try It API Documentation Rapid

MEASURE

What Do We Measure ?

Incident

Finding

Grade

Digital Assets

Every week, Rankiteo analyzes billions of signals to give organizations a sharper, faster view of emerging risks. With deeper, more actionable intelligence at their fingertips, security teams can outpace threat actors, respond instantly to Zero-Day attacks, and dramatically shrink their risk exposure window.

These are some of the factors we use to calculate the overall score:

Network SecurityIdentify exposed access points, detect misconfigured SSL certificates, and uncover vulnerabilities across the network infrastructure.

SBOM (Software Bill of Materials)Gain visibility into the software components used within an organization to detect vulnerabilities, manage risk, and ensure supply chain security.

CMDB (Configuration Management Database)Monitor and manage all IT assets and their configurations to ensure accurate, real-time visibility across the company's technology environment.

Threat IntelligenceLeverage real-time insights on active threats, malware campaigns, and emerging vulnerabilities to proactively defend against evolving cyberattacks.

Rankiteo

By Rankiteo

★ ★ ★ ★ ★

View on G2.com

Rankiteo is a unified scoring and risk platform that analyzes billions of signals weekly to help organizations gain faster, more actionable insights into emerging threats. Empowering teams to outpace adversaries and reduce exposure.

View latest plans →View all security reports →

MILESTONEG

Users
Love Us

Loading…