What is the official website of ARMS Reliability ?

The official website of ARMS Reliability is http://www.armsreliability.com.

What is ARMS Reliability's cybersecurity risk score?

ARMS Reliability has an AI-generated cybersecurity risk score of 751 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has ARMS Reliability experienced?

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

Has ARMS Reliability been affected by any supply chain cyber incidents ?

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

Does ARMS Reliability have SOC 2 Type 1 certification ?

According to Rankiteo, ARMS Reliability is not certified under SOC 2 Type 1.

Does ARMS Reliability have SOC 2 Type 2 certification ?

According to Rankiteo, ARMS Reliability does not hold a SOC 2 Type 2 certification.

Does ARMS Reliability comply with GDPR ?

According to Rankiteo, ARMS Reliability is not listed as GDPR compliant.

Does ARMS Reliability have PCI DSS certification ?

According to Rankiteo, ARMS Reliability does not currently maintain PCI DSS compliance.

Does ARMS Reliability comply with HIPAA ?

According to Rankiteo, ARMS Reliability is not compliant with HIPAA regulations.

Does ARMS Reliability have ISO 27001 certification ?

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

Which industry does ARMS Reliability operate in ?

ARMS Reliability operates primarily in the Operations Consulting industry.

How many employees does ARMS Reliability have ?

ARMS Reliability employs approximately 74 people worldwide.

Does ARMS Reliability own any subsidiaries ?

ARMS Reliability presently has no subsidiaries across any sectors.

How many LinkedIn followers does ARMS Reliability have ?

ARMS Reliability's official LinkedIn profile has approximately 32,161 followers.

What is the NAICS classification code for ARMS Reliability ?

ARMS Reliability is classified under the NAICS code 541614, which corresponds to Process, Physical Distribution, and Logistics Consulting Services.

Does ARMS Reliability have a Crunchbase profile ?

No, ARMS Reliability does not have a profile on Crunchbase.

Does ARMS Reliability have a LinkedIn profile ?

Yes, ARMS Reliability maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/armsreliability.

How many cybersecurity incidents has ARMS Reliability experienced ?

As of June 23, 2026, Rankiteo reports that ARMS Reliability has experienced 1 cybersecurity incidents.

How many peer or competitor companies does ARMS Reliability have ?

ARMS Reliability has an estimated 93 peer or competitor companies worldwide.

What types of cybersecurity incidents has ARMS Reliability faced ?

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

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ARMS Reliability

Boost Score +25 with badge (5 left)

751

/1000

Fair

776

/1000

Fair

ARMS Reliability Vendor Cyber Rating & Cyber Score

armsreliability.com

Add Your Compliance Badge

ARMS Reliability is a leading, global provider of reliability solutions. We're transforming the way asset intensive organizations manage asset reliability, through innovative technology, advisory services and decades of reliability engineering experience. Pioneers of best practice approach; Asset Strategy Management, powered by OnePM®, we are fundamentally changing the way Industry manages reliability to deliver a step-change in asset performance and achieve the optimal balance of cost, risk, and performance. Continuing our journey to make reliability a reality for our customers, we are now a part of Baker Hughes, a global energy technology company, within the Bently Nevada portfolio. Combining our broad range of asset management and

ARMS Reliability A.I CyberSecurity Scoring

Scoring History

ARMS Reliability

ARMS Reliability CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

Baker Hughes

Cyber Attack

100

12/2025

LA-BAK176711658...

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A.I.

ARMS Reliability 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 ARMS Reliability

Incidents vs Operations Consulting Industry Avg (This Year)

No incidents recorded for ARMS Reliability in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for ARMS Reliability in 2026.

Incident Types ARMS Reliability vs Operations Consulting Industry Avg (This Year)

No incidents recorded for ARMS Reliability in 2026.

Incident History - ARMS Reliability (X = Date, Y = Severity)

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SUBSIDIARY

ARMS Reliability Subsidiaries

ARMS Reliability

Operations Consulting

Website: http://www.armsreliability.com

Company Size: 74

Bently Nevada, a Baker Hughes businessOil and Gas

Baker HughesEnergy Technology

Cordant™Energy Technology

Process & Pipeline ServicesOil and Gas

Masoneilan Control ValvesOil and Gas

Consolidated™ Pressure Relief DevicesOil and Gas

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ARMS Reliability Similar Companies

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NEWS

ARMS Reliability CyberSecurity News

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

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November 10, 2025 08:00 AM

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October 27, 2025 07:00 AM

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August 29, 2025 07:00 AM

Winning the AI Arms Race in Financial Services Cybersecurity

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August 16, 2025 07:00 AM

China’s Military Employment of Artificial Intelligence and Its Security Implications

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July 18, 2025 07:00 AM

Roborock’s Saros Z70 With OmniGrip Still Can’t Put Away My Flip-Flops

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May 24, 2025 07:00 AM

Rio Cybersecurity Wi-Fi Router review

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April 04, 2025 07:00 AM

Cyberattacks by AI agents are coming

Agents could make it easier and cheaper for criminals to hack systems at scale. We need to be ready.

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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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