What is the official website of Sbitany ?

The official website of Sbitany is http://www.sbitany.com.

What is Sbitany's cybersecurity risk score?

Sbitany has an AI-generated cybersecurity risk score of 845 out of 1000, indicating a Good security posture according to Rankiteo's assessment.

How many security incidents has Sbitany experienced?

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

Has Sbitany been affected by any supply chain cyber incidents ?

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

Does Sbitany have SOC 2 Type 1 certification ?

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

Does Sbitany have SOC 2 Type 2 certification ?

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

Does Sbitany comply with GDPR ?

According to Rankiteo, Sbitany is not listed as GDPR compliant.

Does Sbitany have PCI DSS certification ?

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

Does Sbitany comply with HIPAA ?

According to Rankiteo, Sbitany is not compliant with HIPAA regulations.

Does Sbitany have ISO 27001 certification ?

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

Which industry does Sbitany operate in ?

Sbitany operates primarily in the Retail industry.

How many employees does Sbitany have ?

Sbitany employs approximately 203 people worldwide.

Does Sbitany own any subsidiaries ?

Sbitany presently has no subsidiaries across any sectors.

How many LinkedIn followers does Sbitany have ?

Sbitany's official LinkedIn profile has approximately 471,452,779 followers.

Does Sbitany have a Crunchbase profile ?

No, Sbitany does not have a profile on Crunchbase.

Does Sbitany have a LinkedIn profile ?

Yes, Sbitany maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/a.-sbitany-&-sons-co.-ltd..

How many cybersecurity incidents has Sbitany experienced ?

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

How many peer or competitor companies does Sbitany have ?

Sbitany has an estimated 15,867 peer or competitor companies worldwide.

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Sbitany

Boost Score +25 with badge (5 left)

845

/1000

Good

870

/1000

Very Good

Sbitany Vendor Cyber Rating & Cyber Score

sbitany.com

Add Your Compliance Badge

A. Sbitany & Sons Co. prides itself in being the industry leader in the retail and wholesale of electrical home appliances. We believe that creating unique experiences is our duty; from shopping at our retail stores to switching on a brand new TV for the first time, we strive to create those moments special for our customers. Founded in 1961 by the late Akram I. Sbitany, Akram Sbitany & Sons (Sbitany) has evolved into the leading company for the importing, marketing, and servicing of Electrical Appliances, Electronics, Commercial and Residential Air Conditions, Mobile Phones, and IT Products for the Palestinian market. With over 500 employees, 19 retails shops, and 200 dealers, Sbitany offers unmatched coverage throughout the Palestinian

Sbitany A.I CyberSecurity Scoring

Scoring History

Sbitany

Sbitany CyberSecurity News & History

Past Incidents

Attack Types

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Type

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Impact

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Blog Details

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A.I.

Sbitany 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 Sbitany

Incidents vs Retail Industry Avg (This Year)

No incidents recorded for Sbitany in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Sbitany in 2026.

Incident Types Sbitany vs Retail Industry Avg (This Year)

No incidents recorded for Sbitany in 2026.

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

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SUBSIDIARY

Sbitany Subsidiaries

Sbitany

Retail

Website: http://www.sbitany.com

Company Size: 203

Sbitany WeCare ProgramPhilanthropic Fundraising Services

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NEWS

Sbitany 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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