What is the official website of Columbus McKinnon EMEA ?

The official website of Columbus McKinnon EMEA is https://www.cmco.com/en-de/.

What is Columbus McKinnon EMEA's cybersecurity risk score?

Columbus McKinnon EMEA has an AI-generated cybersecurity risk score of 746 out of 1000, indicating a Moderate security posture according to Rankiteo's assessment.

How many security incidents has Columbus McKinnon EMEA experienced?

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

Has Columbus McKinnon EMEA been affected by any supply chain cyber incidents ?

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

Does Columbus McKinnon EMEA have SOC 2 Type 1 certification ?

According to Rankiteo, Columbus McKinnon EMEA is not certified under SOC 2 Type 1.

Does Columbus McKinnon EMEA have SOC 2 Type 2 certification ?

According to Rankiteo, Columbus McKinnon EMEA does not hold a SOC 2 Type 2 certification.

Does Columbus McKinnon EMEA comply with GDPR ?

According to Rankiteo, Columbus McKinnon EMEA is not listed as GDPR compliant.

Does Columbus McKinnon EMEA have PCI DSS certification ?

According to Rankiteo, Columbus McKinnon EMEA does not currently maintain PCI DSS compliance.

Does Columbus McKinnon EMEA comply with HIPAA ?

According to Rankiteo, Columbus McKinnon EMEA is not compliant with HIPAA regulations.

Does Columbus McKinnon EMEA have ISO 27001 certification ?

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

Which industry does Columbus McKinnon EMEA operate in ?

Columbus McKinnon EMEA operates primarily in the Machinery Manufacturing industry.

How many employees does Columbus McKinnon EMEA have ?

Columbus McKinnon EMEA employs approximately 0 people worldwide.

Does Columbus McKinnon EMEA own any subsidiaries ?

Columbus McKinnon EMEA presently has no subsidiaries across any sectors.

How many LinkedIn followers does Columbus McKinnon EMEA have ?

Columbus McKinnon EMEA's official LinkedIn profile has approximately 3,499 followers.

What is the NAICS classification code for Columbus McKinnon EMEA ?

Columbus McKinnon EMEA is classified under the NAICS code 333, which corresponds to Machinery Manufacturing.

Does Columbus McKinnon EMEA have a Crunchbase profile ?

No, Columbus McKinnon EMEA does not have a profile on Crunchbase.

Does Columbus McKinnon EMEA have a LinkedIn profile ?

Yes, Columbus McKinnon EMEA maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/columbusmckinnon-emea.

How many cybersecurity incidents has Columbus McKinnon EMEA experienced ?

As of June 23, 2026, Rankiteo reports that Columbus McKinnon EMEA has not experienced any cybersecurity incidents.

How many peer or competitor companies does Columbus McKinnon EMEA have ?

Columbus McKinnon EMEA has an estimated 8,429 peer or competitor companies worldwide.

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746

/1000

Moderate

771

/1000

Fair

Columbus McKinnon EMEA Vendor Cyber Rating & Cyber Score

cmco.com

Add Your Compliance Badge

Since 1875, Columbus McKinnon - with well-known Brands like Yale and pfaff-silberblau - has helped to make material handling easier and safer, and, today, is your single source for complete floor-to-ceiling lifting systems. From below-the-hook attachments, chain, rigging products, manual and powered chain hoists to electric wire rope hoists, cranes, enclosed track systems and specially engineered products, Columbus McKinnon has the engineering expertise to meet the most demanding applications.

CME A.I CyberSecurity Scoring

Scoring History

CME

Columbus McKinnon EMEA CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

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No data available

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A.I.

CME 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 CME

Incidents vs Machinery Manufacturing Industry Avg (This Year)

No incidents recorded for Columbus McKinnon EMEA in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Columbus McKinnon EMEA in 2026.

Incident Types CME vs Machinery Manufacturing Industry Avg (This Year)

No incidents recorded for Columbus McKinnon EMEA in 2026.

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

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SUBSIDIARY

Columbus McKinnon EMEA Subsidiaries

CME

Machinery Manufacturing

Website: https://www.cmco.com/en-de/

Company Size: 0

Columbus McKinnonMachinery Manufacturing

STAHL CraneSystems GmbHMachinery Manufacturing

MagnetekAppliances, Electrical, and Electronics Manufacturing

Magnetek ElevatorAppliances, Electrical, and Electronics Manufacturing

Magnetek Material HandlingAutomation Machinery Manufacturing

Magnetek MiningMachinery Manufacturing

Magnetek Mobile HydraulicAutomation Machinery Manufacturing

Columbus McKinnon Engineered Products GmbHMachinery Manufacturing

Columbus McKinnon Industrial Products GmbHMachinery Manufacturing

Duff-NortonAutomation Machinery Manufacturing

Columbus McKinnon (Latinoamérica)Machinery Manufacturing

Unified Industries, Inc.Industrial Automation

Columbus Mckinnon Italia srlMachinery Manufacturing

Columbus McKinnon APACMachinery Manufacturing

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NEWS

Columbus McKinnon EMEA CyberSecurity News

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

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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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