What is the official website of iSTYLE Hungary ?

The official website of iSTYLE Hungary is http://www.istyle.hu.

What is iSTYLE Hungary's cybersecurity risk score?

iSTYLE Hungary has an AI-generated cybersecurity risk score of 750 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has iSTYLE Hungary experienced?

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

Has iSTYLE Hungary been affected by any supply chain cyber incidents ?

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

Does iSTYLE Hungary have SOC 2 Type 1 certification ?

According to Rankiteo, iSTYLE Hungary is not certified under SOC 2 Type 1.

Does iSTYLE Hungary have SOC 2 Type 2 certification ?

According to Rankiteo, iSTYLE Hungary does not hold a SOC 2 Type 2 certification.

Does iSTYLE Hungary comply with GDPR ?

According to Rankiteo, iSTYLE Hungary is not listed as GDPR compliant.

Does iSTYLE Hungary have PCI DSS certification ?

According to Rankiteo, iSTYLE Hungary does not currently maintain PCI DSS compliance.

Does iSTYLE Hungary comply with HIPAA ?

According to Rankiteo, iSTYLE Hungary is not compliant with HIPAA regulations.

Does iSTYLE Hungary have ISO 27001 certification ?

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

Which industry does iSTYLE Hungary operate in ?

iSTYLE Hungary operates primarily in the IT Services and IT Consulting industry.

How many employees does iSTYLE Hungary have ?

iSTYLE Hungary employs approximately 52 people worldwide.

Does iSTYLE Hungary own any subsidiaries ?

iSTYLE Hungary presently has no subsidiaries across any sectors.

How many LinkedIn followers does iSTYLE Hungary have ?

iSTYLE Hungary's official LinkedIn profile has approximately 2,462 followers.

What is the NAICS classification code for iSTYLE Hungary ?

iSTYLE Hungary is classified under the NAICS code 5415, which corresponds to Computer Systems Design and Related Services.

Does iSTYLE Hungary have a Crunchbase profile ?

No, iSTYLE Hungary does not have a profile on Crunchbase.

Does iSTYLE Hungary have a LinkedIn profile ?

Yes, iSTYLE Hungary maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/istyle-hungary.

How many cybersecurity incidents has iSTYLE Hungary experienced ?

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

How many peer or competitor companies does iSTYLE Hungary have ?

iSTYLE Hungary has an estimated 40,800 peer or competitor companies worldwide.

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iSTYLE Hungary

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750

/1000

Fair

775

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Fair

iSTYLE Hungary Vendor Cyber Rating & Cyber Score

istyle.hu

Add Your Compliance Badge

Az iSTYLE stílusát a legjobb helyeken megtalálható üzletek, a hangulatos berendezés és megjelenés, a barátságos csapat, valamint az egyedülálló áruválaszték jellemzi. Ha többet szeretnél tudni rólunk és a tevékenységünkről, kövess minket Facebookon, Instagramon, vagy látogasd meg üzleteinket. iSTYLE Andrássy út 36 Apple Premium Reseller iSTYLE Westend Apple Premium Reseller iSTYLE Mammut Apple Premium Reseller iSTYLE Árkád Apple Premium Partner iSTYLE Etele Apple Premium Reseller iSTYLE Corvin Plaza 1083 Budapest, Futó utca 37-45. (Corvin Plaza, földszint) iSTYLE Debrecen, Fórum Bevásárlóközpont, 4029, Csapó utca 30. iSTYLE Szeged Árkád Apple Authorised Reseller iSTYLE Győr Árkád Apple Authorised Reseller iSTYLE Kecskeméti utca Apple

iSTYLE Hungary A.I CyberSecurity Scoring

Scoring History

iSTYLE Hungary

iSTYLE Hungary CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

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Incident Details

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No data available

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A.I.

iSTYLE Hungary 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 iSTYLE Hungary

Incidents vs IT Services and IT Consulting Industry Avg (This Year)

No incidents recorded for iSTYLE Hungary in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for iSTYLE Hungary in 2026.

Incident Types iSTYLE Hungary vs IT Services and IT Consulting Industry Avg (This Year)

No incidents recorded for iSTYLE Hungary in 2026.

Incident History - iSTYLE Hungary (X = Date, Y = Severity)

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SUBSIDIARY

iSTYLE Hungary Subsidiaries

iSTYLE Hungary

IT Services and IT Consulting

Website: http://www.istyle.hu

Company Size: 52

Midis GroupIT Services and IT Consulting

MindwareIT Services and IT Consulting

Arab Business MachineComputers and Electronics Manufacturing

iSTYLE MENAIT Services and IT Consulting

MBCOM Technologies, Broadcom RepresentativeIT Services and IT Consulting

Southcomp PolarisIT Services and IT Consulting

ESET Middle EastComputer and Network Security

Arab Computers Co.Computers and Electronics Manufacturing

Micro Conseil InternationalIT Services and IT Consulting

iSTYLE CroatiaIT Services and IT Consulting

GrapheastSoftware Development

iStyle CZ, s.r.o.IT Services and IT Consulting

BlueTech HoldingIT Services and IT Consulting

ESET Greece, Cyprus & MaltaComputer and Network Security

iSTYLE RomaniaIT Services and IT Consulting

HDF sasIT Services and IT Consulting

iSTYLE SerbiaIT Services and IT Consulting

Mindware CloudIT Services and IT Consulting

Apcom SloveniaComputer Hardware Manufacturing

Apcom HungaryIT Services and IT Consulting

iSTYLE SloveniaIT Services and IT Consulting

iSTYLE BulgariaIT Services and IT Consulting

iSTYLE MacedoniaIT Services and IT Consulting

MIBTech FZ LLC - Barracuda NetworksTechnology, Information and Internet

MCI- Midis GroupIT Services and IT Consulting

Polaris DistributionTelecommunications

AC Care - Arab Computers For MaintenanceRepair and Maintenance

iSTYLE CEEIT Services and IT Consulting

iSTYLE SlovakiaIT Services and IT Consulting

Grapheast EducationIT Services and IT Consulting

Apcom RomaniaIT Services and IT Consulting

Apcom BGSoftware Development

OmniSoft ServicesBanking

BMS sas - Business Machines & SolutionsIT Services and IT Consulting

Grapheast jordanIT Services and IT Consulting

SouthComp Polaris S.A.S.Retail Office Equipment

BlueTech Gulf FZ-LLCIT Services and IT Consulting

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NEWS

iSTYLE Hungary 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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