What is the official website of METRO Türkiye ?

The official website of METRO Türkiye is https://www.metro-tr.com/.

What is METRO Türkiye's cybersecurity risk score?

METRO Türkiye has an AI-generated cybersecurity risk score of 762 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has METRO Türkiye experienced?

According to Rankiteo, METRO Türkiye currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.

Has METRO Türkiye been affected by any supply chain cyber incidents ?

According to Rankiteo, METRO Türkiye has not been affected by any supply chain cyber incidents, and no incident IDs are currently listed for the organization.

Does METRO Türkiye have SOC 2 Type 1 certification ?

According to Rankiteo, METRO Türkiye is not certified under SOC 2 Type 1.

Does METRO Türkiye have SOC 2 Type 2 certification ?

According to Rankiteo, METRO Türkiye does not hold a SOC 2 Type 2 certification.

Does METRO Türkiye comply with GDPR ?

According to Rankiteo, METRO Türkiye is not listed as GDPR compliant.

Does METRO Türkiye have PCI DSS certification ?

According to Rankiteo, METRO Türkiye does not currently maintain PCI DSS compliance.

Does METRO Türkiye comply with HIPAA ?

According to Rankiteo, METRO Türkiye is not compliant with HIPAA regulations.

Does METRO Türkiye have ISO 27001 certification ?

According to Rankiteo,METRO Türkiye is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.

Which industry does METRO Türkiye operate in ?

METRO Türkiye operates primarily in the Wholesale industry.

How many employees does METRO Türkiye have ?

METRO Türkiye employs approximately 2,151 people worldwide.

Does METRO Türkiye own any subsidiaries ?

METRO Türkiye presently has no subsidiaries across any sectors.

How many LinkedIn followers does METRO Türkiye have ?

METRO Türkiye's official LinkedIn profile has approximately 169,904 followers.

What is the NAICS classification code for METRO Türkiye ?

METRO Türkiye is classified under the NAICS code 42, which corresponds to Wholesale Trade.

Does METRO Türkiye have a Crunchbase profile ?

No, METRO Türkiye does not have a profile on Crunchbase.

Does METRO Türkiye have a LinkedIn profile ?

Yes, METRO Türkiye maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/metroturkiye.

How many cybersecurity incidents has METRO Türkiye experienced ?

As of June 23, 2026, Rankiteo reports that METRO Türkiye has experienced 1 cybersecurity incidents.

How many peer or competitor companies does METRO Türkiye have ?

METRO Türkiye has an estimated 6,655 peer or competitor companies worldwide.

What types of cybersecurity incidents has METRO Türkiye faced ?

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

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METRO Türkiye

Boost Score +25 with badge (5 left)

762

/1000

Fair

787

/1000

Fair

METRO Türkiye Vendor Cyber Rating & Cyber Score

metro-tr.com

Add Your Compliance Badge

As a leading international food wholesaler, we at METRO are specialized in catering to the needs of hotels, restaurants, caterers (HoReCa), independent merchants (Traders), and more. We are also more than a supplier which inspires the gastronomy sector in more than 30 countries with approximately 15 million customers worldwide! Our unique multichannel mix offers the flexibility of purchasing goods in-store or via our digitally connected Food Service Distribution (FSD) delivery.  Headquartered in Düsseldorf, Germany, METRO Cash & Carry commenced operations in Türkiye in 1990. With its 34 years presence in our country, METRO Türkiye is operating in 20 cities, with 36 stores and over 4.000 employees.  We are a purpose driven company; we

METRO Türkiye A.I CyberSecurity Scoring

Scoring History

METRO Türkiye

METRO Türkiye CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

METRO Türkiye

Cyber Attack

100

10/2022

MET1849291022

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A.I.

METRO Türkiye 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

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Underwriter Stats for METRO Türkiye

Incidents vs Wholesale Industry Avg (This Year)

No incidents recorded for METRO Türkiye in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for METRO Türkiye in 2026.

Incident Types METRO Türkiye vs Wholesale Industry Avg (This Year)

No incidents recorded for METRO Türkiye in 2026.

Incident History - METRO Türkiye (X = Date, Y = Severity)

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SUBSIDIARY

METRO Türkiye Subsidiaries

METRO Türkiye

Wholesale

Website: https://www.metro-tr.com/

Company Size: 1,001-5,000 employees

METRO/MAKROWholesale

METRO FranceWholesale

METRO Global Solution Center INIT Services and IT Consulting

METRO AGWholesale

Makro PortugalWholesale

METRO RomaniaWholesale

Makro NederlandWholesale

METRO Sourcing International LimitedWholesale Import and Export

METRO Deutschland GmbHWholesale

MAKRO PolskaWholesale

METRO SYSTEMS RomaniaInformation Technology & Services

METRO BulgariaWholesale

METRO UkraineWholesale

METRO RussiaWholesale

METRO Food Sourcing - Valencia Trading OfficeWholesale

METRO KazakhstanWholesale

METRO SlovakiaWholesale

METRO MoldovaWholesale

METRO FOOD SOURCING - Concarneau Trading OfficeWholesale

METRO ÖsterreichWholesale

METRO Food Sourcing - Rotterdam Trading Office B.V.Wholesale

METRO MagyarországWholesale

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NEWS

METRO Türkiye CyberSecurity News

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

June 03, 2025 07:00 AM

AI-driven ransomware tops 2025 cyber threats in META, says Kaspersky

The report shows that Türkiye and Kenya recorded the highest share of users impacted by web-based threats (26.1 per cent and 20.1 per cent...

Read Article

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Read Article

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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

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