What is the official website of IFT Food Engineering Division ?

The official website of IFT Food Engineering Division is https://www.ift.org/community/interest-groups-divisions.

What is IFT Food Engineering Division's cybersecurity risk score?

IFT Food Engineering Division has an AI-generated cybersecurity risk score of 748 out of 1000, indicating a Moderate security posture according to Rankiteo's assessment.

How many security incidents has IFT Food Engineering Division experienced?

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

Has IFT Food Engineering Division been affected by any supply chain cyber incidents ?

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

Does IFT Food Engineering Division have SOC 2 Type 1 certification ?

According to Rankiteo, IFT Food Engineering Division is not certified under SOC 2 Type 1.

Does IFT Food Engineering Division have SOC 2 Type 2 certification ?

According to Rankiteo, IFT Food Engineering Division does not hold a SOC 2 Type 2 certification.

Does IFT Food Engineering Division comply with GDPR ?

According to Rankiteo, IFT Food Engineering Division is not listed as GDPR compliant.

Does IFT Food Engineering Division have PCI DSS certification ?

According to Rankiteo, IFT Food Engineering Division does not currently maintain PCI DSS compliance.

Does IFT Food Engineering Division comply with HIPAA ?

According to Rankiteo, IFT Food Engineering Division is not compliant with HIPAA regulations.

Does IFT Food Engineering Division have ISO 27001 certification ?

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

Which industry does IFT Food Engineering Division operate in ?

IFT Food Engineering Division operates primarily in the Food and Beverage Manufacturing industry.

How many employees does IFT Food Engineering Division have ?

IFT Food Engineering Division employs approximately 0 people worldwide.

Does IFT Food Engineering Division own any subsidiaries ?

IFT Food Engineering Division presently has no subsidiaries across any sectors.

How many LinkedIn followers does IFT Food Engineering Division have ?

IFT Food Engineering Division's official LinkedIn profile has approximately 1,576 followers.

What is the NAICS classification code for IFT Food Engineering Division ?

IFT Food Engineering Division is classified under the NAICS code 311, which corresponds to Food Manufacturing.

Does IFT Food Engineering Division have a Crunchbase profile ?

No, IFT Food Engineering Division does not have a profile on Crunchbase.

Does IFT Food Engineering Division have a LinkedIn profile ?

Yes, IFT Food Engineering Division maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/ift-food-engineering-division.

How many cybersecurity incidents has IFT Food Engineering Division experienced ?

As of July 22, 2026, Rankiteo reports that IFT Food Engineering Division has not experienced any cybersecurity incidents.

How many peer or competitor companies does IFT Food Engineering Division have ?

IFT Food Engineering Division has an estimated 4,456 peer or competitor companies worldwide.

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IFED

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748

/1000

Moderate

773

/1000

Fair

IFT Food Engineering Division Vendor Cyber Rating & Cyber Score

ift.org

Add Your Compliance Badge

Application of engineering principles to design industrial processes and equipment for sustainable large scale production of high quality, safe, and nutritious foods.

IFED A.I CyberSecurity Scoring

Scoring History

IFED

IFT Food Engineering Division CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

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Incident Details

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A.I.

IFED 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 IFED

Incidents vs Food and Beverage Manufacturing Industry Avg (This Year)

No incidents recorded for IFT Food Engineering Division in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for IFT Food Engineering Division in 2026.

Incident Types IFED vs Food and Beverage Manufacturing Industry Avg (This Year)

No incidents recorded for IFT Food Engineering Division in 2026.

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

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SUBSIDIARY

IFT Food Engineering Division Subsidiaries

Parent Company

IFED

Food and Beverage Manufacturing

Website: https://www.ift.org/community/interest-groups-divisions

Company Size: 0

No subsidiary data available for this company.

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NEWS

IFT Food Engineering Division CyberSecurity News

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

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CVE

Latest

Global CVEs (Not Company-Specific)

CVE-2026-63261

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

REFERENCES

https://discuss.elastic.co/t/kibana-8-19-19-9-3-8-9-4-4-security-update-esa-2026-72/388575

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

REFERENCES

https://discuss.elastic.co/t/kibana-8-19-19-9-3-8-9-4-4-security-update-esa-2026-71/388574

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

REFERENCES

https://discuss.elastic.co/t/kibana-9-4-4-security-update-esa-2026-70/388573

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

REFERENCES

https://discuss.elastic.co/t/kibana-8-19-19-9-3-8-9-4-4-security-update-esa-2026-69/388572

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

REFERENCES

https://discuss.elastic.co/t/elasticsearch-8-19-19-9-3-8-9-4-4-security-update-esa-2026-68/388571

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