What is the official website of Ebsray, a PSG brand ?

The official website of Ebsray, a PSG brand is https://ow.ly/gQ0Q50WKiAp.

What is Ebsray, a PSG brand's cybersecurity risk score?

Ebsray, a PSG brand has an AI-generated cybersecurity risk score of 745 out of 1000, indicating a Moderate security posture according to Rankiteo's assessment.

How many security incidents has Ebsray, a PSG brand experienced?

According to Rankiteo, Ebsray, a PSG brand currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.

Has Ebsray, a PSG brand been affected by any supply chain cyber incidents ?

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

Does Ebsray, a PSG brand have SOC 2 Type 1 certification ?

According to Rankiteo, Ebsray, a PSG brand is not certified under SOC 2 Type 1.

Does Ebsray, a PSG brand have SOC 2 Type 2 certification ?

According to Rankiteo, Ebsray, a PSG brand does not hold a SOC 2 Type 2 certification.

Does Ebsray, a PSG brand comply with GDPR ?

According to Rankiteo, Ebsray, a PSG brand is not listed as GDPR compliant.

Does Ebsray, a PSG brand have PCI DSS certification ?

According to Rankiteo, Ebsray, a PSG brand does not currently maintain PCI DSS compliance.

Does Ebsray, a PSG brand comply with HIPAA ?

According to Rankiteo, Ebsray, a PSG brand is not compliant with HIPAA regulations.

Does Ebsray, a PSG brand have ISO 27001 certification ?

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

Which industry does Ebsray, a PSG brand operate in ?

Ebsray, a PSG brand operates primarily in the Oil and Gas industry.

How many employees does Ebsray, a PSG brand have ?

Ebsray, a PSG brand employs approximately None employees people worldwide.

Does Ebsray, a PSG brand own any subsidiaries ?

Ebsray, a PSG brand presently has no subsidiaries across any sectors.

How many LinkedIn followers does Ebsray, a PSG brand have ?

Ebsray, a PSG brand's official LinkedIn profile has approximately 826 followers.

What is the NAICS classification code for Ebsray, a PSG brand ?

Ebsray, a PSG brand is classified under the NAICS code 211, which corresponds to Oil and Gas Extraction.

Does Ebsray, a PSG brand have a Crunchbase profile ?

No, Ebsray, a PSG brand does not have a profile on Crunchbase.

Does Ebsray, a PSG brand have a LinkedIn profile ?

Yes, Ebsray, a PSG brand maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/ebsray-pumps.

How many cybersecurity incidents has Ebsray, a PSG brand experienced ?

As of June 23, 2026, Rankiteo reports that Ebsray, a PSG brand has not experienced any cybersecurity incidents.

How many peer or competitor companies does Ebsray, a PSG brand have ?

Ebsray, a PSG brand has an estimated 10,951 peer or competitor companies worldwide.

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EPB

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745

/1000

Moderate

770

/1000

Fair

Ebsray, a PSG brand Vendor Cyber Rating & Cyber Score

ow.ly

Add Your Compliance Badge

Ebsray® is a leader in the design of regenerative turbine and positive displacement pump technologies, including sliding vane, gear and lobe pumps, for a wide range of applications. Founded in Australia in the 1920s, Ebsray has grown into a leading brand and supplier of specialized pumps for use in a wide array of industries, including chemical, petroleum liquids, mining, and transport, among others. Ebsray is a brand of PSG®, a Dover company. To learn more about Ebsray, please visit https://ow.ly/gQ0Q50WKiAp

EPB A.I CyberSecurity Scoring

Scoring History

EPB

Ebsray, a PSG brand 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.

EPB 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 EPB

Incidents vs Oil and Gas Industry Avg (This Year)

No incidents recorded for Ebsray, a PSG brand in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Ebsray, a PSG brand in 2026.

Incident Types EPB vs Oil and Gas Industry Avg (This Year)

No incidents recorded for Ebsray, a PSG brand in 2026.

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

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SUBSIDIARY

Ebsray, a PSG brand Subsidiaries

EPB

Oil and Gas

Website: https://ow.ly/gQ0Q50WKiAp

Company Size: 1,001-5,000 employees

Dover CorporationMachinery Manufacturing

Cook CompressionMachinery Manufacturing

SWEPIndustrial Machinery Manufacturing

OK International, a Dover CompanyAppliances, Electrical, and Electronics Manufacturing

MetcalAppliances, Electrical, and Electronics Manufacturing

TechconAutomation Machinery Manufacturing

CPC - Colder Products CompanyPlastics Manufacturing

BelvacMachinery Manufacturing

ARC PacificMachinery Manufacturing

Waukesha Bearings CorporationMachinery Manufacturing

TWG, A Dover companyMachinery Manufacturing

CDS Visual, a Dover companySoftware Development

PSG, a Dover companyMachinery Manufacturing

Hydro, a PSG brandMachinery Manufacturing

Malema, a PSG brandAutomation Machinery Manufacturing

Malema Life SciencesBiotechnology Research

Wilden, a PSG brandMachinery Manufacturing

Blackmer, a PSG brandMachinery Manufacturing

Griswold, a PSG brandMachinery Manufacturing

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Ebsray, a PSG brand Similar Companies

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NEWS

Ebsray, a PSG brand 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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