Comparison Overview

Australian Museums and Galleries Association

VS

Center for Statistics and Machine Learning

Australian Museums and Galleries Association

Canberra, 2600, AU
Last Update: 2026-01-23
View Profile
Between 750 and 799
https://www.amaga.org.au/

Australian Museums and Galleries Association Incorporated (AMaGA) is the national association and peak advocacy body representing museums and galleries. We encompass a wide and diverse range of national, state, regional and community museums, galleries, historic sites, botanic and zoological gardens, research centres, Indigenous cultural centres, and Keeping Places across Australia. All of our members are, however, linked by a shared dedication to culture, the arts, movable cultural heritage and communities, and the knowledge that Australian cultural life is a dynamic ecosystem that generates creativity and innovation and contributes to the social and economic wellbeing of the country.

NAICS: 712
NAICS Definition: Museums, Historical Sites, and Similar Institutions
Employees: 19
Subsidiaries: 0
12-month incidents
0
Known data breaches
0
Attack type number
0
View Profile

Center for Statistics and Machine Learning

26 Prospect Ave, Princeton, 08540, US
Last Update: 2026-01-23
Between 750 and 799
https://csml.princeton.edu

The Center for Statistics and Machine Learning (CSML) is Princeton University’s focal point for data science education and research on campus. The center’s mission is to foster and support a community of scholars addressing the challenges of modern algorithmic data-driven research, the development of innovative methodologies for extracting information from data across different domains, and the education of students in the foundations of modern data science. The center fulfills this via support of research and teaching that harnesses insights from computation, machine learning, and statistics, to advance both theoretical foundations and scientific discovery. The center offers courses, two certificate programs, and special initiatives for students. The center also co-sponsors seminars that enhance researchers’ knowledge base and workshops that deepen the use and reach of data science on campus. Undergirding all these efforts is the center’s open collaborative, interdisciplinary nature. We work with departments, centers, and others on and off campus. Contact us ( [email protected] ) for more information if you are interested in partnering with us on research or want to know more about our suite of programs.

NAICS: 712
NAICS Definition: Museums, Historical Sites, and Similar Institutions
Employees: 6
Subsidiaries: 0
12-month incidents
0
Known data breaches
0
Attack type number
0

Compliance Badges Comparison

Security & Compliance Standards Overview

https://images.rankiteo.com/companyimages/museums-australia.jpeg
Australian Museums and Galleries Association
—
ISO 27001
ISO 27001 certification not verified
Not verified
—
SOC2 Type 1
SOC2 Type 1 certification not verified
Not verified
—
SOC2 Type 2
SOC2 Type 2 certification not verified
Not verified
—
GDPR
GDPR certification not verified
Not verified
—
PCI DSS
PCI DSS certification not verified
Not verified
—
HIPAA
HIPAA certification not verified
Not verified
https://images.rankiteo.com/companyimages/princeton-csml.jpeg
Center for Statistics and Machine Learning
—
ISO 27001
ISO 27001 certification not verified
Not verified
—
SOC2 Type 1
SOC2 Type 1 certification not verified
Not verified
—
SOC2 Type 2
SOC2 Type 2 certification not verified
Not verified
—
GDPR
GDPR certification not verified
Not verified
—
PCI DSS
PCI DSS certification not verified
Not verified
—
HIPAA
HIPAA certification not verified
Not verified
Compliance Summary
Australian Museums and Galleries Association
100%
Compliance Rate
0/4 Standards Verified
Center for Statistics and Machine Learning
0%
Compliance Rate
0/4 Standards Verified

Benchmark & Cyber Underwriting Signals

Incidents vs Museums, Historical Sites, and Zoos Industry Average (This Year)

No incidents recorded for Australian Museums and Galleries Association in 2026.

Incidents vs Museums, Historical Sites, and Zoos Industry Average (This Year)

No incidents recorded for Center for Statistics and Machine Learning in 2026.

Incident History — Australian Museums and Galleries Association (X = Date, Y = Severity)

Australian Museums and Galleries Association cyber incidents detection timeline including parent company and subsidiaries

Incident History — Center for Statistics and Machine Learning (X = Date, Y = Severity)

Center for Statistics and Machine Learning cyber incidents detection timeline including parent company and subsidiaries

Notable Incidents

Last 3 Security & Risk Events by Company

https://images.rankiteo.com/companyimages/museums-australia.jpeg
Australian Museums and Galleries Association
Incidents

No Incident

https://images.rankiteo.com/companyimages/princeton-csml.jpeg
Center for Statistics and Machine Learning
Incidents

No Incident

FAQ

Both Australian Museums and Galleries Association company and Center for Statistics and Machine Learning company demonstrate a comparable AI Cybersecurity Score, with strong governance and monitoring frameworks in place.

Historically, Center for Statistics and Machine Learning company has disclosed a higher number of cyber incidents compared to Australian Museums and Galleries Association company.

In the current year, Center for Statistics and Machine Learning company and Australian Museums and Galleries Association company have not reported any cyber incidents.

Neither Center for Statistics and Machine Learning company nor Australian Museums and Galleries Association company has reported experiencing a ransomware attack publicly.

Neither Center for Statistics and Machine Learning company nor Australian Museums and Galleries Association company has reported experiencing a data breach publicly.

Neither Center for Statistics and Machine Learning company nor Australian Museums and Galleries Association company has reported experiencing targeted cyberattacks publicly.

Neither Australian Museums and Galleries Association company nor Center for Statistics and Machine Learning company has reported experiencing or disclosing vulnerabilities publicly.

Neither Australian Museums and Galleries Association nor Center for Statistics and Machine Learning holds any compliance certifications.

Neither company holds any compliance certifications.

Neither Australian Museums and Galleries Association company nor Center for Statistics and Machine Learning company has publicly disclosed detailed information about the number of their subsidiaries.

Australian Museums and Galleries Association company employs more people globally than Center for Statistics and Machine Learning company, reflecting its scale as a Museums, Historical Sites, and Zoos.

Neither Australian Museums and Galleries Association nor Center for Statistics and Machine Learning holds SOC 2 Type 1 certification.

Neither Australian Museums and Galleries Association nor Center for Statistics and Machine Learning holds SOC 2 Type 2 certification.

Neither Australian Museums and Galleries Association nor Center for Statistics and Machine Learning holds ISO 27001 certification.

Neither Australian Museums and Galleries Association nor Center for Statistics and Machine Learning holds PCI DSS certification.

Neither Australian Museums and Galleries Association nor Center for Statistics and Machine Learning holds HIPAA certification.

Neither Australian Museums and Galleries Association nor Center for Statistics and Machine Learning holds GDPR certification.

Latest Global CVEs (Not Company-Specific)

Description

Typemill is a flat-file, Markdown-based CMS designed for informational documentation websites. A reflected Cross-Site Scripting (XSS) exists in the login error view template `login.twig` of versions 2.19.1 and below. The `username` value can be echoed back without proper contextual encoding when authentication fails. An attacker can execute script in the login page context. This issue has been fixed in version 2.19.2.

Published
Date
2026-01-23
Updated
Date
2026-01-23
Risk Information
cvss3
Base: 5.4
Severity: LOW
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:L/I:L/A:N
References
Description

A DOM-based Cross-Site Scripting (XSS) vulnerability exists in the DomainCheckerApp class within domain/script.js of Sourcecodester Domain Availability Checker v1.0. The vulnerability occurs because the application improperly handles user-supplied data in the createResultElement method by using the unsafe innerHTML property to render domain search results.

Published
Date
2026-01-23
Updated
Date
2026-01-23
References
Description

A Remote Code Execution (RCE) vulnerability exists in Sourcecodester Modern Image Gallery App v1.0 within the gallery/upload.php component. The application fails to properly validate uploaded file contents. Additionally, the application preserves the user-supplied file extension during the save process. This allows an unauthenticated attacker to upload arbitrary PHP code by spoofing the MIME type as an image, leading to full system compromise.

Published
Date
2026-01-23
Updated
Date
2026-01-23
References
Description

A UNIX symbolic link following issue in the jailer component in Firecracker version v1.13.1 and earlier and 1.14.0 on Linux may allow a local host user with write access to the pre-created jailer directories to overwrite arbitrary host files via a symlink attack during the initialization copy at jailer startup, if the jailer is executed with root privileges. To mitigate this issue, users should upgrade to version v1.13.2 or 1.14.1 or above.

Published
Date
2026-01-23
Updated
Date
2026-01-23
Risk Information
cvss3
Base: 6.0
Severity: LOW
CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:N/I:H/A:H
cvss4
Base: 6.0
Severity: LOW
CVSS:4.0/AV:L/AC:L/AT:N/PR:H/UI:N/VC:N/VI:N/VA:N/SC:N/SI:H/SA:H/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
References
Description

An information disclosure vulnerability exists in the /srvs/membersrv/getCashiers endpoint of the Aptsys gemscms backend platform thru 2025-05-28. This unauthenticated endpoint returns a list of cashier accounts, including names, email addresses, usernames, and passwords hashed using MD5. As MD5 is a broken cryptographic function, the hashes can be easily reversed using public tools, exposing user credentials in plaintext. This allows remote attackers to perform unauthorized logins and potentially gain access to sensitive POS operations or backend functions.

Published
Date
2026-01-23
Updated
Date
2026-01-23
References