What is the official website of MSCI Private Assets ?

The official website of MSCI Private Assets is https://www.msci.com/research-and-insights.

What is MSCI Private Assets's cybersecurity risk score?

MSCI Private Assets has an AI-generated cybersecurity risk score of 763 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has MSCI Private Assets experienced?

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

Has MSCI Private Assets been affected by any supply chain cyber incidents ?

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

Does MSCI Private Assets have SOC 2 Type 1 certification ?

According to Rankiteo, MSCI Private Assets is not certified under SOC 2 Type 1.

Does MSCI Private Assets have SOC 2 Type 2 certification ?

According to Rankiteo, MSCI Private Assets does not hold a SOC 2 Type 2 certification.

Does MSCI Private Assets comply with GDPR ?

According to Rankiteo, MSCI Private Assets is not listed as GDPR compliant.

Does MSCI Private Assets have PCI DSS certification ?

According to Rankiteo, MSCI Private Assets does not currently maintain PCI DSS compliance.

Does MSCI Private Assets comply with HIPAA ?

According to Rankiteo, MSCI Private Assets is not compliant with HIPAA regulations.

Does MSCI Private Assets have ISO 27001 certification ?

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

Which industry does MSCI Private Assets operate in ?

MSCI Private Assets operates primarily in the Financial Services industry.

How many employees does MSCI Private Assets have ?

MSCI Private Assets employs approximately None employees people worldwide.

Does MSCI Private Assets own any subsidiaries ?

MSCI Private Assets presently has no subsidiaries across any sectors.

How many LinkedIn followers does MSCI Private Assets have ?

MSCI Private Assets's official LinkedIn profile has approximately 39,416 followers.

What is the NAICS classification code for MSCI Private Assets ?

MSCI Private Assets is classified under the NAICS code 52, which corresponds to Finance and Insurance.

Does MSCI Private Assets have a Crunchbase profile ?

No, MSCI Private Assets does not have a profile on Crunchbase.

Does MSCI Private Assets have a LinkedIn profile ?

Yes, MSCI Private Assets maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/msci-private-assets.

How many cybersecurity incidents has MSCI Private Assets experienced ?

As of June 23, 2026, Rankiteo reports that MSCI Private Assets has not experienced any cybersecurity incidents.

How many peer or competitor companies does MSCI Private Assets have ?

MSCI Private Assets has an estimated 32,132 peer or competitor companies worldwide.

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763

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Fair

788

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Fair

MSCI Private Assets Vendor Cyber Rating & Cyber Score

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MSCI is the premier independent source of private markets intelligence in the world. Investors partner with us to improve performance benchmarking, risk assessment, and capital allocation decisions across public and private markets. With decision-grade data sourced directly from LPs, cutting-edge analytical capabilities, and integrated tools, we are connecting the industry in new ways and driving its growth.

MPA A.I CyberSecurity Scoring

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MPA

MSCI Private Assets CyberSecurity News & History

Past Incidents

Attack Types

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Impact

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A.I.

MPA 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

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Prediction C

Prediction D

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Underwriter Stats for MPA

Incidents vs Financial Services Industry Avg (This Year)

No incidents recorded for MSCI Private Assets in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for MSCI Private Assets in 2026.

Incident Types MPA vs Financial Services Industry Avg (This Year)

No incidents recorded for MSCI Private Assets in 2026.

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

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SUBSIDIARY

MSCI Private Assets Subsidiaries

Parent Company

MPA

Financial Services

Website: https://www.msci.com/research-and-insights

Company Size: 1,001-5,000 employees

No subsidiary data available for this company.

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NEWS

MSCI Private Assets 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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