What is the official website of Alliance Laundry Systems Brasil ?

The official website of Alliance Laundry Systems Brasil is https://alliancelaundry.com.br/.

What is Alliance Laundry Systems Brasil's cybersecurity risk score?

Alliance Laundry Systems Brasil 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 Alliance Laundry Systems Brasil experienced?

According to Rankiteo, Alliance Laundry Systems Brasil currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.

Has Alliance Laundry Systems Brasil been affected by any supply chain cyber incidents ?

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

Does Alliance Laundry Systems Brasil have SOC 2 Type 1 certification ?

According to Rankiteo, Alliance Laundry Systems Brasil is not certified under SOC 2 Type 1.

Does Alliance Laundry Systems Brasil have SOC 2 Type 2 certification ?

According to Rankiteo, Alliance Laundry Systems Brasil does not hold a SOC 2 Type 2 certification.

Does Alliance Laundry Systems Brasil comply with GDPR ?

According to Rankiteo, Alliance Laundry Systems Brasil is not listed as GDPR compliant.

Does Alliance Laundry Systems Brasil have PCI DSS certification ?

According to Rankiteo, Alliance Laundry Systems Brasil does not currently maintain PCI DSS compliance.

Does Alliance Laundry Systems Brasil comply with HIPAA ?

According to Rankiteo, Alliance Laundry Systems Brasil is not compliant with HIPAA regulations.

Does Alliance Laundry Systems Brasil have ISO 27001 certification ?

According to Rankiteo,Alliance Laundry Systems Brasil is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.

Which industry does Alliance Laundry Systems Brasil operate in ?

Alliance Laundry Systems Brasil operates primarily in the Industrial Machinery Manufacturing industry.

How many employees does Alliance Laundry Systems Brasil have ?

Alliance Laundry Systems Brasil employs approximately None employees people worldwide.

Does Alliance Laundry Systems Brasil own any subsidiaries ?

Alliance Laundry Systems Brasil presently has no subsidiaries across any sectors.

How many LinkedIn followers does Alliance Laundry Systems Brasil have ?

Alliance Laundry Systems Brasil's official LinkedIn profile has approximately 2,081 followers.

What is the NAICS classification code for Alliance Laundry Systems Brasil ?

Alliance Laundry Systems Brasil is classified under the NAICS code 3332, which corresponds to Industrial Machinery Manufacturing.

Does Alliance Laundry Systems Brasil have a Crunchbase profile ?

No, Alliance Laundry Systems Brasil does not have a profile on Crunchbase.

Does Alliance Laundry Systems Brasil have a LinkedIn profile ?

Yes, Alliance Laundry Systems Brasil maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/alliancelaundrybrasil.

How many cybersecurity incidents has Alliance Laundry Systems Brasil experienced ?

As of June 23, 2026, Rankiteo reports that Alliance Laundry Systems Brasil has experienced 2 cybersecurity incidents.

How many peer or competitor companies does Alliance Laundry Systems Brasil have ?

Alliance Laundry Systems Brasil has an estimated 7,808 peer or competitor companies worldwide.

What types of cybersecurity incidents has Alliance Laundry Systems Brasil faced ?

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

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746

/1000

Moderate

771

/1000

Fair

Alliance Laundry Systems Brasil Vendor Cyber Rating & Cyber Score

alliancelaundry.com.br

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Com mais de 110 anos de experiência, somos líderes em pesquisa, desenvolvimento e venda de soluções profissionais para lavanderias comerciais, industriais e hospitalares. Nossa produção global, totalmente focada nas tendências e necessidades do público, segue rígidas normas de qualidade e garante a padronização dos equipamentos, feitos com os melhores e mais duráveis componentes. Um ciclo limpo também inclui o meio ambiente. Nossas tecnologias verdes potencializam o desempenho das máquinas, o que aumenta a economia de recursos, controla a quantidade de produtos químicos e reduz o tempo das lavagens. No Brasil, revolucionamos o mercado com três das nossas marcas premium: Primus, Speed Queen e Unimac. Agora é com você, multiplique o

ALSB A.I CyberSecurity Scoring

Scoring History

ALSB

Alliance Laundry Systems Brasil CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

UniMac®

Cyber Attack

100

4/2026

UNIVYN178031684...

Alliance Laundry Sy...

Breach

12/2023

ALL626072525

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A.I.

ALSB 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

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Underwriter Stats for ALSB

Incidents vs Industrial Machinery Manufacturing Industry Avg (This Year)

No incidents recorded for Alliance Laundry Systems Brasil in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Alliance Laundry Systems Brasil in 2026.

Incident Types ALSB vs Industrial Machinery Manufacturing Industry Avg (This Year)

No incidents recorded for Alliance Laundry Systems Brasil in 2026.

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

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SUBSIDIARY

Alliance Laundry Systems Brasil Subsidiaries

ALSB

Industrial Machinery Manufacturing

Website: https://alliancelaundry.com.br/

Company Size: 1,001-5,000 employees

Alliance Laundry Systems LLCMachinery Manufacturing

Primus Laundry EquipmentMachinery Manufacturing

Primus Laundry Equipment FranceMachinery Manufacturing

IPSO Laundry EquipmentMachinery Manufacturing

Huebsch LaundromatMachinery Manufacturing

Alliance Laundry Systems EMEAIMachinery Manufacturing

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NEWS

Alliance Laundry Systems Brasil CyberSecurity News

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

March 13, 2026 05:10 PM

Alliance Laundry (NYSE: ALH) details 2025 results, market share and key risks

Alliance Laundry Holdings Inc. describes itself as the world's largest designer and manufacturer of commercial laundry systems,...

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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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