What is the official website of A & B Auto Sales ?

The official website of A & B Auto Sales is http://www.aandbautosales.com.

What is A & B Auto Sales's cybersecurity risk score?

A & B Auto Sales has an AI-generated cybersecurity risk score of 807 out of 1000, indicating a Good security posture according to Rankiteo's assessment.

How many security incidents has A & B Auto Sales experienced?

According to Rankiteo, A & B Auto Sales currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.

Has A & B Auto Sales been affected by any supply chain cyber incidents ?

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

Does A & B Auto Sales have SOC 2 Type 1 certification ?

According to Rankiteo, A & B Auto Sales is not certified under SOC 2 Type 1.

Does A & B Auto Sales have SOC 2 Type 2 certification ?

According to Rankiteo, A & B Auto Sales does not hold a SOC 2 Type 2 certification.

Does A & B Auto Sales comply with GDPR ?

According to Rankiteo, A & B Auto Sales is not listed as GDPR compliant.

Does A & B Auto Sales have PCI DSS certification ?

According to Rankiteo, A & B Auto Sales does not currently maintain PCI DSS compliance.

Does A & B Auto Sales comply with HIPAA ?

According to Rankiteo, A & B Auto Sales is not compliant with HIPAA regulations.

Does A & B Auto Sales have ISO 27001 certification ?

According to Rankiteo,A & B Auto Sales is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.

Which industry does A & B Auto Sales operate in ?

A & B Auto Sales operates primarily in the Motor Vehicle Manufacturing industry.

How many employees does A & B Auto Sales have ?

A & B Auto Sales employs approximately 41 people worldwide.

Does A & B Auto Sales own any subsidiaries ?

A & B Auto Sales presently has no subsidiaries across any sectors.

How many LinkedIn followers does A & B Auto Sales have ?

A & B Auto Sales's official LinkedIn profile has approximately followers.

What is the NAICS classification code for A & B Auto Sales ?

A & B Auto Sales is classified under the NAICS code 3361, which corresponds to Motor Vehicle Manufacturing.

Does A & B Auto Sales have a Crunchbase profile ?

No, A & B Auto Sales does not have a profile on Crunchbase.

Does A & B Auto Sales have a LinkedIn profile ?

Yes, A & B Auto Sales 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-&-b-auto-sales.

How many cybersecurity incidents has A & B Auto Sales experienced ?

As of June 24, 2026, Rankiteo reports that A & B Auto Sales has not experienced any cybersecurity incidents.

How many peer or competitor companies does A & B Auto Sales have ?

A & B Auto Sales has an estimated 12,984 peer or competitor companies worldwide.

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BAS

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807

/1000

Good

832

/1000

Good

A & B Auto Sales Vendor Cyber Rating & Cyber Score

aandbautosales.com

Add Your Compliance Badge

BAS A.I CyberSecurity Scoring

Scoring History

BAS

A & B Auto Sales CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

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No data available

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A.I.

BAS 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

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Underwriter Stats for BAS

Incidents vs Motor Vehicle Manufacturing Industry Avg (This Year)

No incidents recorded for A & B Auto Sales in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for A & B Auto Sales in 2026.

Incident Types BAS vs Motor Vehicle Manufacturing Industry Avg (This Year)

No incidents recorded for A & B Auto Sales in 2026.

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

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SUBSIDIARY

A & B Auto Sales Subsidiaries

Parent Company

BAS

Motor Vehicle Manufacturing

Website: http://www.aandbautosales.com

Company Size: 41

No subsidiary data available for this company.

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NEWS

A & B Auto Sales 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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