What is the official website of PARKnSHOP ?

The official website of PARKnSHOP is https://www.pns.hk/zh-hk/.

What is PARKnSHOP's cybersecurity risk score?

PARKnSHOP has an AI-generated cybersecurity risk score of 770 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has PARKnSHOP experienced?

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

Has PARKnSHOP been affected by any supply chain cyber incidents ?

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

Does PARKnSHOP have SOC 2 Type 1 certification ?

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

Does PARKnSHOP have SOC 2 Type 2 certification ?

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

Does PARKnSHOP comply with GDPR ?

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

Does PARKnSHOP have PCI DSS certification ?

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

Does PARKnSHOP comply with HIPAA ?

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

Does PARKnSHOP have ISO 27001 certification ?

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

Which industry does PARKnSHOP operate in ?

PARKnSHOP operates primarily in the Retail industry.

How many employees does PARKnSHOP have ?

PARKnSHOP employs approximately 298 people worldwide.

Does PARKnSHOP own any subsidiaries ?

PARKnSHOP presently has no subsidiaries across any sectors.

How many LinkedIn followers does PARKnSHOP have ?

PARKnSHOP's official LinkedIn profile has approximately 3,134 followers.

What is the NAICS classification code for PARKnSHOP ?

PARKnSHOP is classified under the NAICS code 43, which corresponds to Retail Trade.

Does PARKnSHOP have a Crunchbase profile ?

No, PARKnSHOP does not have a profile on Crunchbase.

Does PARKnSHOP have a LinkedIn profile ?

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

How many cybersecurity incidents has PARKnSHOP experienced ?

As of June 23, 2026, Rankiteo reports that PARKnSHOP has experienced 1 cybersecurity incidents.

How many peer or competitor companies does PARKnSHOP have ?

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

What types of cybersecurity incidents has PARKnSHOP faced ?

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

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PARKnSHOP

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770

/1000

Fair

795

/1000

Fair

PARKnSHOP Vendor Cyber Rating & Cyber Score

pns.hk

Add Your Compliance Badge

PARKnSHOP Supermarket is part of AS Watson Group, the world’s largest international health and beauty retailer operating over 16,500 stores under 12 retail brands in 28 markets, with about 130,000 employees worldwide. For the fiscal year 2023, AS Watson Group recorded revenue of US$23 billion. Every year, we are serving over 5.5 billion shoppers via our O+O (Offline plus Online) technology-enabled platforms. Established in 1972, PARKnSHOP is Hong Kong's leading O+O supermarket chain and one of the most trusted brands in Hong Kong. PARKnSHOP now operates nearly 250 stores in Hong Kong and Macau. PARKnSHOP continues to innovate and offer the best value for money, the widest number of product choices, freshness and safety, and different

PARKnSHOP A.I CyberSecurity Scoring

Scoring History

PARKnSHOP

PARKnSHOP CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

PARKnSHOP

Breach

08/2018

SUP23281122

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A.I.

PARKnSHOP 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 PARKnSHOP

Incidents vs Retail Industry Avg (This Year)

No incidents recorded for PARKnSHOP in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for PARKnSHOP in 2026.

Incident Types PARKnSHOP vs Retail Industry Avg (This Year)

No incidents recorded for PARKnSHOP in 2026.

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

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SUBSIDIARY

PARKnSHOP Subsidiaries

PARKnSHOP

Retail

Website: https://www.pns.hk/zh-hk/

Company Size: 298

AS WatsonRetail

Watsons TurkeyRetail

SuperdrugRetail

Watsons SingaporeRetail

MARIONNAUDRetail

Marionnaud ItalyRetail

Marionnaud SwitzerlandEinzelhandel: Gesundheits- und Körperpflegeprodukte

Marionnaud AustriaEinzelhandel: Gesundheits- und Körperpflegeprodukte

Marionnaud Czech RepublicMaloobchod

Watsons MalaysiaRetail

Watsons PhilippinesRetail

AS Watson BeneluxRetail

KruidvatRetail

AS Watson BeneluxRetail

ICI PARIS XLRetail

AS Watson BeneluxRetail

TrekpleisterRetail

AS Watson BeneluxRetail

Drogas ASRetail

Watsons ThailandRetail

Watsons VietnamRetail

The Perfume ShopRetail

Watsons TaiwanRetail

Watsons IndonesiaRetail

eLab Tech @ A.S. WatsonVendita al dettaglio

AS Watson BeneluxRetail

Watsons UkraineRetail

Fortress 豐澤Retail

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NEWS

PARKnSHOP CyberSecurity News

Latest updates, reports, and threat intel affecting the global network.

China Resources may join Tesco to bid for Hong Kong's ParknShop

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Read Article

International analysis: Will Walmart acquire Hong Kong’s Park n Shop?

Hong Kong-based conglomerate AS Watson has confirmed it is conducting a strategic review of grocery retail business Park n Shop (PnS).

Read Article

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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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