What is the official website of Guidehouse Lithuania ?

The official website of Guidehouse Lithuania is https://guidehouse.com/regions/lithuania.

What is Guidehouse Lithuania's cybersecurity risk score?

Guidehouse Lithuania has an AI-generated cybersecurity risk score of 754 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has Guidehouse Lithuania experienced?

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

Has Guidehouse Lithuania been affected by any supply chain cyber incidents ?

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

Does Guidehouse Lithuania have SOC 2 Type 1 certification ?

According to Rankiteo, Guidehouse Lithuania is not certified under SOC 2 Type 1.

Does Guidehouse Lithuania have SOC 2 Type 2 certification ?

According to Rankiteo, Guidehouse Lithuania does not hold a SOC 2 Type 2 certification.

Does Guidehouse Lithuania comply with GDPR ?

According to Rankiteo, Guidehouse Lithuania is not listed as GDPR compliant.

Does Guidehouse Lithuania have PCI DSS certification ?

According to Rankiteo, Guidehouse Lithuania does not currently maintain PCI DSS compliance.

Does Guidehouse Lithuania comply with HIPAA ?

According to Rankiteo, Guidehouse Lithuania is not compliant with HIPAA regulations.

Does Guidehouse Lithuania have ISO 27001 certification ?

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

Which industry does Guidehouse Lithuania operate in ?

Guidehouse Lithuania operates primarily in the Financial Services industry.

How many employees does Guidehouse Lithuania have ?

Guidehouse Lithuania employs approximately None employees people worldwide.

Does Guidehouse Lithuania own any subsidiaries ?

Guidehouse Lithuania presently has no subsidiaries across any sectors.

How many LinkedIn followers does Guidehouse Lithuania have ?

Guidehouse Lithuania's official LinkedIn profile has approximately 191 followers.

What is the NAICS classification code for Guidehouse Lithuania ?

Guidehouse Lithuania is classified under the NAICS code 52, which corresponds to Finance and Insurance.

Does Guidehouse Lithuania have a Crunchbase profile ?

No, Guidehouse Lithuania does not have a profile on Crunchbase.

Does Guidehouse Lithuania have a LinkedIn profile ?

Yes, Guidehouse Lithuania maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/guidehouse-lithuania.

How many cybersecurity incidents has Guidehouse Lithuania experienced ?

As of June 23, 2026, Rankiteo reports that Guidehouse Lithuania has not experienced any cybersecurity incidents.

How many peer or competitor companies does Guidehouse Lithuania have ?

Guidehouse Lithuania has an estimated 32,124 peer or competitor companies worldwide.

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Guidehouse Lithuania

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754

/1000

Fair

779

/1000

Fair

Guidehouse Lithuania Vendor Cyber Rating & Cyber Score

guidehouse.com

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Guidehouse is a global AI-led professional services firm delivering advisory, technology, and managed services to the commercial and government sectors. With an integrated business technology approach, Guidehouse drives efficiency and resilience in the healthcare, financial services, energy, infrastructure, and national security markets. Built to help clients across industries outwit complexity, the firm brings together approximately 18,000 professionals to achieve lasting impact and shape a meaningful future.

Guidehouse Lithuania A.I CyberSecurity Scoring

Scoring History

Guidehouse Lithuania

Guidehouse Lithuania CyberSecurity News & History

Past Incidents

Attack Types

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Impact

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A.I.

Guidehouse Lithuania 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

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Underwriter Stats for Guidehouse Lithuania

Incidents vs Financial Services Industry Avg (This Year)

No incidents recorded for Guidehouse Lithuania in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Guidehouse Lithuania in 2026.

Incident Types Guidehouse Lithuania vs Financial Services Industry Avg (This Year)

No incidents recorded for Guidehouse Lithuania in 2026.

Incident History - Guidehouse Lithuania (X = Date, Y = Severity)

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SUBSIDIARY

Guidehouse Lithuania Subsidiaries

Parent Company

Guidehouse Lithuania

Financial Services

Website: https://guidehouse.com/regions/lithuania

Company Size: None employees

No subsidiary data available for this company.

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NEWS

Guidehouse Lithuania 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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