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Comparison Overview

MCMC
VS
B&QB&Q
MC

MC

Rua João Mendonça 529, Senhora da Hora, Porto, PT, 4460-282

Last Update: 02/04/2026

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Between 750 and 799
https://mc.sonae.pt/
795/1000Fair

MC is a company from the SONAE group, and is a leader in the food retail industry in Portugal. We are a company made by all, to all. With a history of over 35 years of continuous growth, MC has a distinctive positioning in different business areas, with a vast portfoli...

NAICS:43
NAICS Definition:Retail Trade
Employees:12,112
Subsidiaries:2
12-month incidents
0
Known data breaches
0
Attack type number
0
B&Q

B&Q

undefined, Southampton, undefined, undefined, GB

Last Update: 02/04/2026

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791/1000Fair

We are the UK’s leading home improvement and garden living retailer with over 300 stores throughout the UK and Ireland, offering great prices, with over 100,000 products available to order at diy.com for home delivery or click and collect. We launched the UK’s first ho...

NAICS:43
NAICS Definition:Retail Trade
Employees:12,936
Subsidiaries:10
12-month incidents
0
Known data breaches
0
Attack type number
0

Compliance Ranges Comparison

Based On Specific Ai Models Category
MC

MC

-
ISO 27001Not verified
ISO 27001
-
SOC2 Type 1Not verified
SOC2 Type 1
-
SOC2 Type 2Not verified
SOC2 Type 2
-
GDPRNot verified
GDPR
-
PCI DSSNot verified
PCI DSS
-
HIPAANot verified
HIPAA
B&Q

B&Q

-
ISO 27001Not verified
ISO 27001
-
SOC2 Type 1Not verified
SOC2 Type 1
-
SOC2 Type 2Not verified
SOC2 Type 2
-
GDPRNot verified
GDPR
-
PCI DSSNot verified
PCI DSS
-
HIPAANot verified
HIPAA

Benchmark & Cyber Underwriting Signals

Incidents vs Retail Industry Avg (This Year)

No incidents recorded for MC in 2026.

Incidents

Incidents vs Retail Industry Avg (This Year)

No incidents recorded for B&Q in 2026.

Incidents

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

MC cyber incidents detection timeline including parent company and subsidiaries.

No timeline data available
R - Ransomware
C - Cyber Attack
D - Data Breach
V - Vulnerability

Incident History - B&Q (X = Date, Y = Severity)

B&Q cyber incidents detection timeline including parent company and subsidiaries.

No timeline data available
R - Ransomware
C - Cyber Attack
D - Data Breach
V - Vulnerability

Notable Incidents

Last Cyber / HR Incidents / Global...
MC

MC

Incidents
No explicit notable incidents reported.
B&Q

B&Q

Incidents
No explicit notable incidents reported.

FAQ

Between MC company and B&Q company, which one has the best AI Cybersecurity Score ?
Between MC company and B&Q company, which one has experienced more cyber incidents in the past ?
Between MC company and B&Q company, which one has experienced more cyber incidents this year ?
Between MC company and B&Q company, which one has experienced at least one ransomware attack ?
Between MC company and B&Q company, which one has experienced at least one data breach ?
Between MC company and B&Q company, which one has experienced at least one targeted cyberattack ?
Between MC company and B&Q company, which one has experienced at least one vulnerability ?
Between MC company and B&Q company, which one holds the most compliance certifications ?
Between MC company and B&Q company, which one holds the fewest compliance certifications ?
Between MC company and B&Q company, which one has the most subsidiaries ?
Between MC company and B&Q company, which one has the largest number of employees ?
Between MC and B&Q, which company holds both SOC 2 Type 1 certifications ?
Between MC and B&Q, which company holds both SOC 2 Type 2 certifications ?
Which company is ISO 27001 certified - MC or B&Q ?
Which company is PCI DSS compliant - MC or B&Q ?
Between MC and B&Q, which company complies with HIPAA regulations for healthcare data ?
Between MC and B&Q, which company complies with GDPR requirements ?

Latest Global CVEs

CVE-2026-63261
SUMMARY

Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). A low-privileged authenticated user can send a specially crafted request to a Kibana machine learning feature, causing the server to exhaust available memory and become unavailable to all users.

PUBLISHED
Date2026-07-21
UPDATED
Date2026-07-21
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
CVE-2026-63260
SUMMARY

Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated attacker with low-privilege access can trigger a denial of service condition in Kibana by sending a specially crafted, oversized request payload. Processing this user-supplied input requires resource-intensive memory allocation that can exhaust the available heap memory in the Kibana process, causing it to crash and become unavailable to all users.

PUBLISHED
Date2026-07-21
UPDATED
Date2026-07-21
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
CVE-2026-63259
SUMMARY

Authorization Bypass Through User-Controlled Key (CWE-639) in Kibana can lead to information disclosure via user-supplied identifiers that reference scheduled query result data from Kibana Spaces the requester is not authorized to access.

PUBLISHED
Date2026-07-21
UPDATED
Date2026-07-21
RISK INFORMATION (Score: 4.3)
CVSS3
Base Score: 4.3
Complexity: LOW
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N
IMPACT SCORE
1.4
EXPLOITABILITY
2.8
CVE-2026-63145
SUMMARY

Incorrect Authorization (CWE-863) in Kibana can lead to integrity compromise of Machine Learning audit and notification records via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). A vulnerability exists in Kibana's Machine Learning functionality where a Machine Learning management endpoint performs an insufficient authorization check. The endpoint validates only a coarse privilege level but does not verify that the requesting user has access to the specific Machine Learning job or notification resources provided in the request. As a result, a low-privileged user with Machine Learning access in any Kibana space can manipulate Machine Learning audit and notification records for arbitrary jobs—including jobs in other spaces or belonging to other users—by leveraging Kibana's internally elevated credentials to write to restricted Machine Learning system indices that the user cannot access directly.

PUBLISHED
Date2026-07-21
UPDATED
Date2026-07-21
RISK INFORMATION (Score: 4.3)
CVSS3
Base Score: 4.3
Complexity: LOW
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:N
IMPACT SCORE
1.4
EXPLOITABILITY
2.8
CVE-2026-63144
SUMMARY

Uncontrolled Recursion (CWE-674) in Elasticsearch can lead to denial of service via a specially crafted search request submitted by a low-privileged authenticated user. A user with read-level index access can submit a request that triggers unbounded recursive processing within the Elasticsearch query evaluation component, causing a fatal error that terminates the affected node. In single-node deployments, this results in complete service outage; in multi-node clusters, it causes repeated node restarts and sustained availability degradation.

PUBLISHED
Date2026-07-21
UPDATED
Date2026-07-21
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