What is the official website of JCI Ventures ?

The official website of JCI Ventures is https://www.johnsoncontrols.com/ventures.

What is JCI Ventures's cybersecurity risk score?

JCI Ventures has an AI-generated cybersecurity risk score of 755 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has JCI Ventures experienced?

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

Has JCI Ventures been affected by any supply chain cyber incidents ?

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

Does JCI Ventures have SOC 2 Type 1 certification ?

According to Rankiteo, JCI Ventures is not certified under SOC 2 Type 1.

Does JCI Ventures have SOC 2 Type 2 certification ?

According to Rankiteo, JCI Ventures does not hold a SOC 2 Type 2 certification.

Does JCI Ventures comply with GDPR ?

According to Rankiteo, JCI Ventures is not listed as GDPR compliant.

Does JCI Ventures have PCI DSS certification ?

According to Rankiteo, JCI Ventures does not currently maintain PCI DSS compliance.

Does JCI Ventures comply with HIPAA ?

According to Rankiteo, JCI Ventures is not compliant with HIPAA regulations.

Does JCI Ventures have ISO 27001 certification ?

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

Which industry does JCI Ventures operate in ?

JCI Ventures operates primarily in the Financial Services industry.

How many employees does JCI Ventures have ?

JCI Ventures employs approximately None employees people worldwide.

Does JCI Ventures own any subsidiaries ?

JCI Ventures presently has no subsidiaries across any sectors.

How many LinkedIn followers does JCI Ventures have ?

JCI Ventures's official LinkedIn profile has approximately 1,226 followers.

What is the NAICS classification code for JCI Ventures ?

JCI Ventures is classified under the NAICS code 52, which corresponds to Finance and Insurance.

Does JCI Ventures have a Crunchbase profile ?

No, JCI Ventures does not have a profile on Crunchbase.

Does JCI Ventures have a LinkedIn profile ?

Yes, JCI Ventures maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/jci-ventures.

How many cybersecurity incidents has JCI Ventures experienced ?

As of June 23, 2026, Rankiteo reports that JCI Ventures has experienced 2 cybersecurity incidents.

How many peer or competitor companies does JCI Ventures have ?

JCI Ventures has an estimated 32,132 peer or competitor companies worldwide.

What types of cybersecurity incidents has JCI Ventures faced ?

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

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JCI Ventures

Boost Score +25 with badge (5 left)

755

/1000

Fair

780

/1000

Fair

JCI Ventures Vendor Cyber Rating & Cyber Score

johnsoncontrols.com

Add Your Compliance Badge

JCI Ventures is the corporate venture capital division of Johnson Controls International (JCI), providing access to the company’s global network of resources and customers. We partner with and invest in startups strategic to JCI's markets and market adjacencies. Johnson Controls is a $20+ billion global diversified technology and industrial leader serving a wide range of customers in more than 150 countries. We are focused on creating intelligent, energy efficient, and secure buildings and building environments for the next generation of smart cities and communities.

JCI Ventures A.I CyberSecurity Scoring

Scoring History

JCI Ventures

JCI Ventures CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

JCI Ventures

Vulnerability

100

6/2025

JOH450204510062...

JCI Ventures

Ransomware

09/2023

JOH174511023

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A.I.

JCI Ventures 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 JCI Ventures

Incidents vs Financial Services Industry Avg (This Year)

No incidents recorded for JCI Ventures in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for JCI Ventures in 2026.

Incident Types JCI Ventures vs Financial Services Industry Avg (This Year)

No incidents recorded for JCI Ventures in 2026.

Incident History - JCI Ventures (X = Date, Y = Severity)

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SUBSIDIARY

JCI Ventures Subsidiaries

JCI Ventures

Financial Services

Website: https://www.johnsoncontrols.com/ventures

Company Size: 2-10 employees

Johnson ControlsIndustrial Machinery Manufacturing

Johnson Controls América LatinaIndustrial Machinery Manufacturing

Johnson Controls Middle East and AfricaIndustrial Machinery Manufacturing

Johnson Controls Fire SuppressionIndustrial Machinery Manufacturing

Johnson Controls Asia Pacific工业机械制造业

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

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Read Article

September 13, 2022 07:00 AM

Alcatraz AI Raises $25M To Solve Your Biometric Authentication Needs

Alcatraz AI, the US-Bulgarian company for autonomous access control using 3D facial authentication and AI, raises a $25M Series A round.

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August 30, 2022 07:00 AM

Johnson Controls invests in, signs deal with San Francisco cybersecurity firm

In a move it said will make its smart building technology more secure, Johnson Controls has signed a framework agreement with San...

Read Article

June 23, 2022 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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