What is the official website of Twin Maples Specialty ?

The official website of Twin Maples Specialty is https://twinmaplesspecialty.com/.

What is Twin Maples Specialty's cybersecurity risk score?

Twin Maples Specialty has an AI-generated cybersecurity risk score of 769 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has Twin Maples Specialty experienced?

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

Has Twin Maples Specialty been affected by any supply chain cyber incidents ?

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

Does Twin Maples Specialty have SOC 2 Type 1 certification ?

According to Rankiteo, Twin Maples Specialty is not certified under SOC 2 Type 1.

Does Twin Maples Specialty have SOC 2 Type 2 certification ?

According to Rankiteo, Twin Maples Specialty does not hold a SOC 2 Type 2 certification.

Does Twin Maples Specialty comply with GDPR ?

According to Rankiteo, Twin Maples Specialty is not listed as GDPR compliant.

Does Twin Maples Specialty have PCI DSS certification ?

According to Rankiteo, Twin Maples Specialty does not currently maintain PCI DSS compliance.

Does Twin Maples Specialty comply with HIPAA ?

According to Rankiteo, Twin Maples Specialty is not compliant with HIPAA regulations.

Does Twin Maples Specialty have ISO 27001 certification ?

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

Which industry does Twin Maples Specialty operate in ?

Twin Maples Specialty operates primarily in the Insurance industry.

How many employees does Twin Maples Specialty have ?

Twin Maples Specialty employs approximately None employees people worldwide.

Does Twin Maples Specialty own any subsidiaries ?

Twin Maples Specialty presently has no subsidiaries across any sectors.

How many LinkedIn followers does Twin Maples Specialty have ?

Twin Maples Specialty's official LinkedIn profile has approximately followers.

What is the NAICS classification code for Twin Maples Specialty ?

Twin Maples Specialty is classified under the NAICS code 524, which corresponds to Insurance Carriers and Related Activities.

Does Twin Maples Specialty have a Crunchbase profile ?

No, Twin Maples Specialty does not have a profile on Crunchbase.

Does Twin Maples Specialty have a LinkedIn profile ?

Yes, Twin Maples Specialty maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/twin-maples.

How many cybersecurity incidents has Twin Maples Specialty experienced ?

As of June 23, 2026, Rankiteo reports that Twin Maples Specialty has experienced 1 cybersecurity incidents.

How many peer or competitor companies does Twin Maples Specialty have ?

Twin Maples Specialty has an estimated 15,550 peer or competitor companies worldwide.

What types of cybersecurity incidents has Twin Maples Specialty faced ?

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

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769

/1000

Fair

794

/1000

Fair

Twin Maples Specialty Vendor Cyber Rating & Cyber Score

twinmaplesspecialty.com

Add Your Compliance Badge

Twin Maples offers innovative coverage for middle market and small businesses

TMS A.I CyberSecurity Scoring

Scoring History

TMS

Twin Maples Specialty CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

Starr

Ransomware

100

11/2025

STA1778283287

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A.I.

TMS 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 TMS

Incidents vs Insurance Industry Avg (This Year)

No incidents recorded for Twin Maples Specialty in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Twin Maples Specialty in 2026.

Incident Types TMS vs Insurance Industry Avg (This Year)

No incidents recorded for Twin Maples Specialty in 2026.

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

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SUBSIDIARY

Twin Maples Specialty Subsidiaries

TMS

Insurance

Website: https://twinmaplesspecialty.com/

Company Size: 2-10 employees

StarrInsurance

Starr Travel InsuranceInsurance

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NEWS

Twin Maples Specialty 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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