What is the official website of ANDRITZ Separation ?

The official website of ANDRITZ Separation is https://www.andritz.com/separation.

What is ANDRITZ Separation's cybersecurity risk score?

ANDRITZ Separation has an AI-generated cybersecurity risk score of 748 out of 1000, indicating a Moderate security posture according to Rankiteo's assessment.

How many security incidents has ANDRITZ Separation experienced?

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

Has ANDRITZ Separation been affected by any supply chain cyber incidents ?

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

Does ANDRITZ Separation have SOC 2 Type 1 certification ?

According to Rankiteo, ANDRITZ Separation is not certified under SOC 2 Type 1.

Does ANDRITZ Separation have SOC 2 Type 2 certification ?

According to Rankiteo, ANDRITZ Separation does not hold a SOC 2 Type 2 certification.

Does ANDRITZ Separation comply with GDPR ?

According to Rankiteo, ANDRITZ Separation is not listed as GDPR compliant.

Does ANDRITZ Separation have PCI DSS certification ?

According to Rankiteo, ANDRITZ Separation does not currently maintain PCI DSS compliance.

Does ANDRITZ Separation comply with HIPAA ?

According to Rankiteo, ANDRITZ Separation is not compliant with HIPAA regulations.

Does ANDRITZ Separation have ISO 27001 certification ?

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

Which industry does ANDRITZ Separation operate in ?

ANDRITZ Separation operates primarily in the Machinery Manufacturing industry.

How many employees does ANDRITZ Separation have ?

ANDRITZ Separation employs approximately 471 people worldwide.

Does ANDRITZ Separation own any subsidiaries ?

ANDRITZ Separation presently has no subsidiaries across any sectors.

How many LinkedIn followers does ANDRITZ Separation have ?

ANDRITZ Separation's official LinkedIn profile has approximately 28,456 followers.

What is the NAICS classification code for ANDRITZ Separation ?

ANDRITZ Separation is classified under the NAICS code 333, which corresponds to Machinery Manufacturing.

Does ANDRITZ Separation have a Crunchbase profile ?

No, ANDRITZ Separation does not have a profile on Crunchbase.

Does ANDRITZ Separation have a LinkedIn profile ?

Yes, ANDRITZ Separation maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/andritz-separation.

How many cybersecurity incidents has ANDRITZ Separation experienced ?

As of October 6, 2026, Rankiteo reports that ANDRITZ Separation has not experienced any cybersecurity incidents.

How many peer or competitor companies does ANDRITZ Separation have ?

ANDRITZ Separation has an estimated 8,481 peer or competitor companies worldwide.

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ANDRITZ Separation

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748

/1000

Moderate

773

/1000

Fair

ANDRITZ Separation Vendor Cyber Rating & Cyber Score

andritz.com

Add Your Compliance Badge

A WORLD OF SEPARATION SOLUTIONS. ANDRITZ provides mechanical and thermal solid/liquid separation technologies, complemented by comprehensive services, automation, and digitalization solutions for the chemicals, environment, food and beverage, as well as mining and minerals industries. Our customized, innovative solutions focus on minimizing resource consumption and maximizing process efficiency, thus making a substantial contribution towards sustainable environmental protection. With over 150 years of experience and more than 2,700 separation specialists around the globe, we are a driving force in the evolution of separation solutions – enabling industries to meet tomorrow’s demands responsibly. ANDRITZ. FOR GROWTH THAT MATTERS.

ANDRITZ Separation

ANDRITZ Separation 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.

ANDRITZ Separation 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 ANDRITZ Separation

Incidents vs Machinery Manufacturing Industry Avg (This Year)

No incidents recorded for ANDRITZ Separation in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for ANDRITZ Separation in 2026.

Incident Types ANDRITZ Separation vs Machinery Manufacturing Industry Avg (This Year)

No incidents recorded for ANDRITZ Separation in 2026.

Incident History - ANDRITZ Separation (X = Date, Y = Severity)

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SUBSIDIARY

ANDRITZ Separation Subsidiaries

Parent Company

ANDRITZ Separation

Machinery Manufacturing

Website: https://www.andritz.com/separation

Company Size: 10,001+ employees

No subsidiary data available for this company.

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NEWS

ANDRITZ Separation CyberSecurity News

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

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CVE

Latest

Global CVEs (Not Company-Specific)

CVE-2026-105761

SUMMARY

Dify is an open-source LLM app development platform. Prior to 1.16.0, the PUT /console/api/apps/<app_id>/server endpoint in api/controllers/console/app/mcp_server.py used AppMCPServerController.put() to retrieve an AppMCPServer by the client-supplied server ID without verifying that the server belonged to the requested application and tenant. An authenticated workspace member could therefore change another application's MCP server status and parameters, potentially redirecting data or disabling the service. This issue is fixed in version 1.16.0.

Published

Date2026-10-05

Updated

Date2026-10-05

RISK INFORMATION (Score: 7.1)

cvss3

Base Score: 7.1

Complexity: LOW

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

Impact Score

4.2

Exploitability

2.8

REFERENCES

CVE-2026-105760

SUMMARY

vLLM is an inference and serving engine for large language models. Prior to 0.30.0, a caller can use the request-level media_io_kwargs field to select the GLMGA video backend and supply large values for the fps and max_frames options without a strict work ceiling. GLMGA constructs and deduplicates an attacker-sized pre-decode frame-index list, allowing a compact request and tiny valid video to consume disproportionate CPU time and memory in the shared media-loading executor. This issue is fixed in version 0.30.0.

Published

Date2026-10-05

Updated

Date2026-10-05

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:N/I:N/A:L

Impact Score

1.4

Exploitability

3.9

REFERENCES

CVE-2026-105759

SUMMARY

vLLM is an inference and serving engine for large language models. Prior to 0.30.0, the Rust frontend's track_http_metrics middleware records the raw HTTP method token as a Prometheus label for requests reaching registered routes. An unauthenticated attacker can send unique arbitrary method tokens to unguarded routes such as /tokenize, causing Prometheus's Family::get_or_create function to permanently create counter and histogram label sets. Those label sets increase process memory usage and enlarge the /metrics response until the service or monitoring path is exhausted. This issue is fixed in version 0.30.0.

Published

Date2026-10-05

Updated

Date2026-10-05

RISK INFORMATION (Score: 5.9)

cvss3

Base Score: 5.9

Complexity: HIGH

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

Impact Score

3.6

Exploitability

2.2

REFERENCES

CVE-2026-105758

SUMMARY

vLLM is an inference and serving engine for large language models. From 0.24.0 until 0.30.0, the Qwen2VLVideoBackend and Qwen3VLVideoBackend classes accept request-level values for the media_io_kwargs.video.max_frames and media_io_kwargs.video.fps fields without enforcing server-side ceilings. An unauthenticated caller can submit these values to the /tokenize endpoint, causing the sampler to decode every frame selected from attacker-controlled video input, consume disproportionate frontend memory, and potentially terminate the API process before scheduling or admission control. The Rust frontend is not affected because it rejects the media_io_kwargs field. This issue is fixed in version 0.30.0.

Published

Date2026-10-05

Updated

Date2026-10-05

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:N/I:N/A:L

Impact Score

1.4

Exploitability

3.9

REFERENCES

CVE-2026-105757

SUMMARY

vLLM is an inference and serving engine for large language models. Prior to 0.30.0, structured-output request failures can escape request-scoped validation and reach the EngineCore fatal-error path. A per-request backend mismatch can re-raise a grammar compilation exception, padding produced by the ngram_gpu speculative-decoding mode can pass a negative token to guidance validation, and the Rust frontend can admit empty structured-output values that the Python frontend rejects, allowing ordinary constrained-generation requests to terminate the shared engine. This issue is fixed in version 0.30.0.

Published

Date2026-10-05

Updated

Date2026-10-05

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

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ANDRITZ Separation Vendor Cyber Rating & Cyber Score

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ANDRITZ Separation Company Scoring based on AI Models