What is the official website of Philips Sleep & Respiratory Care ?

The official website of Philips Sleep & Respiratory Care is http://www.respironics.com/.

What is Philips Sleep & Respiratory Care's cybersecurity risk score?

Philips Sleep & Respiratory Care has an AI-generated cybersecurity risk score of 765 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has Philips Sleep & Respiratory Care experienced?

According to Rankiteo, Philips Sleep & Respiratory Care currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.

Has Philips Sleep & Respiratory Care been affected by any supply chain cyber incidents ?

According to Rankiteo, Philips Sleep & Respiratory Care has been affected by a supply chain cyber incident involving ODIDO, with the incident ID ODI1771093701.

Does Philips Sleep & Respiratory Care have SOC 2 Type 1 certification ?

According to Rankiteo, Philips Sleep & Respiratory Care is not certified under SOC 2 Type 1.

Does Philips Sleep & Respiratory Care have SOC 2 Type 2 certification ?

According to Rankiteo, Philips Sleep & Respiratory Care does not hold a SOC 2 Type 2 certification.

Does Philips Sleep & Respiratory Care comply with GDPR ?

According to Rankiteo, Philips Sleep & Respiratory Care is not listed as GDPR compliant.

Does Philips Sleep & Respiratory Care have PCI DSS certification ?

According to Rankiteo, Philips Sleep & Respiratory Care does not currently maintain PCI DSS compliance.

Does Philips Sleep & Respiratory Care comply with HIPAA ?

According to Rankiteo, Philips Sleep & Respiratory Care is not compliant with HIPAA regulations.

Does Philips Sleep & Respiratory Care have ISO 27001 certification ?

According to Rankiteo,Philips Sleep & Respiratory Care is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.

Which industry does Philips Sleep & Respiratory Care operate in ?

Philips Sleep & Respiratory Care operates primarily in the Hospitals and Health Care industry.

How many employees does Philips Sleep & Respiratory Care have ?

Philips Sleep & Respiratory Care employs approximately None employees people worldwide.

Does Philips Sleep & Respiratory Care own any subsidiaries ?

Philips Sleep & Respiratory Care presently has no subsidiaries across any sectors.

How many LinkedIn followers does Philips Sleep & Respiratory Care have ?

Philips Sleep & Respiratory Care's official LinkedIn profile has approximately 10,540 followers.

What is the NAICS classification code for Philips Sleep & Respiratory Care ?

Philips Sleep & Respiratory Care is classified under the NAICS code 62, which corresponds to Health Care and Social Assistance.

Does Philips Sleep & Respiratory Care have a Crunchbase profile ?

No, Philips Sleep & Respiratory Care does not have a profile on Crunchbase.

Does Philips Sleep & Respiratory Care have a LinkedIn profile ?

Yes, Philips Sleep & Respiratory Care maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/philips-respiratory.

How many cybersecurity incidents has Philips Sleep & Respiratory Care experienced ?

As of June 23, 2026, Rankiteo reports that Philips Sleep & Respiratory Care has experienced 2 cybersecurity incidents.

How many peer or competitor companies does Philips Sleep & Respiratory Care have ?

Philips Sleep & Respiratory Care has an estimated 33,111 peer or competitor companies worldwide.

What types of cybersecurity incidents has Philips Sleep & Respiratory Care faced ?

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

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765

/1000

Fair

790

/1000

Fair

Philips Sleep & Respiratory Care Vendor Cyber Rating & Cyber Score

respironics.com

Add Your Compliance Badge

At Philips, we are committed to what matters most: safe and effective solutions that advance sleep and respiratory care. Our House Rules: https://www.philips.com/a-w/social-media.html

PSRC A.I CyberSecurity Scoring

Scoring History

PSRC

Philips Sleep & Respiratory Care CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

Philips

Breach

2/2026

ODIDO

ODI1771093701

Philips Sleep & Res...

Ransomware

100

5/2023

PHI258072525

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A.I.

PSRC 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 PSRC

Incidents vs Hospitals and Health Care Industry Avg (This Year)

No incidents recorded for Philips Sleep & Respiratory Care in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Philips Sleep & Respiratory Care in 2026.

Incident Types PSRC vs Hospitals and Health Care Industry Avg (This Year)

No incidents recorded for Philips Sleep & Respiratory Care in 2026.

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

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SUBSIDIARY

Philips Sleep & Respiratory Care Subsidiaries

PSRC

Hospitals and Health Care

Website: http://www.respironics.com/

Company Size: None employees

Philips FoundationNon-profit Organization Management

Volcano CorporationMedical Equipment Manufacturing

SpectraneticsMedical Device

Philips LifelineMedical Equipment Manufacturing

PhilipsHospitals and Health Care

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NEWS

Philips Sleep & Respiratory Care CyberSecurity News

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

November 06, 2025 08:00 AM

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November 05, 2025 08:00 AM

Philips etches small profit gain in third quarter

THE HAGUE, Netherlands ― Dutch electronics and medical device manufacturer Philips reported a slight gain in third-quarter net profits...

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October 24, 2025 07:00 AM

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Philips Valuation in Focus After Recent FDA Clearance for Sleep Device in 2025

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Read Article

October 08, 2025 07:00 AM

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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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