Comparison Overview

APPG AI

VS

University of Maryland Center for Health and Homeland Security

APPG AI

1 Parliament Square, London, England, SW1A 0AA, GB
Last Update: 2025-11-27
View Profile
Between 700 and 749
https://bicpavilion.com/about_pavilion/appg-artificial-intelligence

The APPG AI was set up in January 2017 to address ethical issues and new industry norms for applying Artificial Intelligence (AI), including machine learning, decision-making, natural language understanding, automated reasoning, autonomous systems, generative AI and other forms. Without being too technical, we will try to understand how AI will impact the lives of UK citizens and organisations, and subsequently, how should it be regulated? How will health, energy, insurance, consulting, financial, legal and knowledge-intensive business services be traded? How should the new business models be regulated, and what about the data? There is a lot to explore and evidence is key for regulation and policy. Pavilion Platform proudly hosts the All-Party Parliamentary Group on Artificial Intelligence (APPG AI), providing a centralised hub for all its resources, including our publications, event registrations and list of members and Associates: Pavilion for PC website: https://bicpavilion.com/ From your mobile: - Pavilion on App Store https://apple.co/4dCawaW - Pavilion on Google Play https://bit.ly/44Da6N3 The APPG AI is Co-Chaired by Allison Gardner, MP (Labour), and Lord Clement-Jones, CBE (Liberal Democrat). The APPG AI Vice Chairs are Dawn Butler MP (Labour) and Lord Ranger of Northwood (Kulveer Ranger) (Conservative). Lord Taylor of Warwick (John David Beckett Taylor) (Non-affiliated) is APPG AI Honorary Vice-Chair. The Group supporters – AMI Limited, Automated Analytics, British Standards Institution, Brunel University London, BT Group, Capgemini, Centre for the Governance of AI, CMS Cameron McKenna Nabarro Olswang, Cognizant, Deloitte, Duolingo, Ernst & Young, Hewlett Packard Enterprise, Innovate UK - UKRI, Onfido, Osborne Clarke, Rialto, Santander, Uptitude, and WindWorkX – enable us to raise the ambition of what we can achieve.

NAICS: 921
NAICS Definition:
Employees: 46
Subsidiaries: 0
12-month incidents
0
Known data breaches
0
Attack type number
0
View Profile

University of Maryland Center for Health and Homeland Security

School of Law, Baltimore, MD, 21201, US
Last Update: 2025-11-27
Between 700 and 749
http://www.mdchhs.com/

The Center for Health and Homeland Security (CHHS) is a non-profit consulting firm and academic center that works with the nation’s top emergency responders in the public and private sector to develop plans, policies, and strategies for government, corporate, and institutional clients that ensure the safety of citizens in the event of natural or man-made catastrophes. We currently have over 50 professionals working on more than 90 contracts world-wide. We provide a unique perspective on emergency preparedness services. Built on an academic foundation, CHHS strives to develop new strategies and creative approaches to fulfill our clients'​ goals. As the experienced CHHS team discovers innovative ways to complete projects efficiently and effectively, we make consistent progress toward our own goal: excellence that exceeds expectations.

NAICS: 921
NAICS Definition:
Employees: 34
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/appg-ai.jpeg
APPG AI
—
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/university-of-maryland-center-for-health-and-homeland-security.jpeg
University of Maryland Center for Health and Homeland Security
—
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
APPG AI
100%
Compliance Rate
0/4 Standards Verified
University of Maryland Center for Health and Homeland Security
0%
Compliance Rate
0/4 Standards Verified

Benchmark & Cyber Underwriting Signals

Incidents vs Public Policy Offices Industry Average (This Year)

No incidents recorded for APPG AI in 2025.

Incidents vs Public Policy Offices Industry Average (This Year)

No incidents recorded for University of Maryland Center for Health and Homeland Security in 2025.

Incident History — APPG AI (X = Date, Y = Severity)

APPG AI cyber incidents detection timeline including parent company and subsidiaries

Incident History — University of Maryland Center for Health and Homeland Security (X = Date, Y = Severity)

University of Maryland Center for Health and Homeland Security cyber incidents detection timeline including parent company and subsidiaries

Notable Incidents

Last 3 Security & Risk Events by Company

https://images.rankiteo.com/companyimages/appg-ai.jpeg
APPG AI
Incidents

No Incident

https://images.rankiteo.com/companyimages/university-of-maryland-center-for-health-and-homeland-security.jpeg
University of Maryland Center for Health and Homeland Security
Incidents

No Incident

FAQ

University of Maryland Center for Health and Homeland Security company demonstrates a stronger AI Cybersecurity Score compared to APPG AI company, reflecting its advanced cybersecurity posture governance and monitoring frameworks.

Historically, University of Maryland Center for Health and Homeland Security company has disclosed a higher number of cyber incidents compared to APPG AI company.

In the current year, University of Maryland Center for Health and Homeland Security company and APPG AI company have not reported any cyber incidents.

Neither University of Maryland Center for Health and Homeland Security company nor APPG AI company has reported experiencing a ransomware attack publicly.

Neither University of Maryland Center for Health and Homeland Security company nor APPG AI company has reported experiencing a data breach publicly.

Neither University of Maryland Center for Health and Homeland Security company nor APPG AI company has reported experiencing targeted cyberattacks publicly.

Neither APPG AI company nor University of Maryland Center for Health and Homeland Security company has reported experiencing or disclosing vulnerabilities publicly.

Neither APPG AI nor University of Maryland Center for Health and Homeland Security holds any compliance certifications.

Neither company holds any compliance certifications.

Neither APPG AI company nor University of Maryland Center for Health and Homeland Security company has publicly disclosed detailed information about the number of their subsidiaries.

APPG AI company employs more people globally than University of Maryland Center for Health and Homeland Security company, reflecting its scale as a Public Policy Offices.

Neither APPG AI nor University of Maryland Center for Health and Homeland Security holds SOC 2 Type 1 certification.

Neither APPG AI nor University of Maryland Center for Health and Homeland Security holds SOC 2 Type 2 certification.

Neither APPG AI nor University of Maryland Center for Health and Homeland Security holds ISO 27001 certification.

Neither APPG AI nor University of Maryland Center for Health and Homeland Security holds PCI DSS certification.

Neither APPG AI nor University of Maryland Center for Health and Homeland Security holds HIPAA certification.

Neither APPG AI nor University of Maryland Center for Health and Homeland Security holds GDPR certification.

Latest Global CVEs (Not Company-Specific)

Description

Angular is a development platform for building mobile and desktop web applications using TypeScript/JavaScript and other languages. Prior to versions 19.2.16, 20.3.14, and 21.0.1, there is a XSRF token leakage via protocol-relative URLs in angular HTTP clients. The vulnerability is a Credential Leak by App Logic that leads to the unauthorized disclosure of the Cross-Site Request Forgery (XSRF) token to an attacker-controlled domain. Angular's HttpClient has a built-in XSRF protection mechanism that works by checking if a request URL starts with a protocol (http:// or https://) to determine if it is cross-origin. If the URL starts with protocol-relative URL (//), it is incorrectly treated as a same-origin request, and the XSRF token is automatically added to the X-XSRF-TOKEN header. This issue has been patched in versions 19.2.16, 20.3.14, and 21.0.1. A workaround for this issue involves avoiding using protocol-relative URLs (URLs starting with //) in HttpClient requests. All backend communication URLs should be hardcoded as relative paths (starting with a single /) or fully qualified, trusted absolute URLs.

Published
Date
2025-11-26
Updated
Date
2025-11-26
Risk Information
cvss4
Base: 7.7
Severity: LOW
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:N/SC:H/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
References
Description

Forge (also called `node-forge`) is a native implementation of Transport Layer Security in JavaScript. An Uncontrolled Recursion vulnerability in node-forge versions 1.3.1 and below enables remote, unauthenticated attackers to craft deep ASN.1 structures that trigger unbounded recursive parsing. This leads to a Denial-of-Service (DoS) via stack exhaustion when parsing untrusted DER inputs. This issue has been patched in version 1.3.2.

Published
Date
2025-11-26
Updated
Date
2025-11-26
Risk Information
cvss4
Base: 8.7
Severity: LOW
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/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
References
Description

Forge (also called `node-forge`) is a native implementation of Transport Layer Security in JavaScript. An Integer Overflow vulnerability in node-forge versions 1.3.1 and below enables remote, unauthenticated attackers to craft ASN.1 structures containing OIDs with oversized arcs. These arcs may be decoded as smaller, trusted OIDs due to 32-bit bitwise truncation, enabling the bypass of downstream OID-based security decisions. This issue has been patched in version 1.3.2.

Published
Date
2025-11-26
Updated
Date
2025-11-26
Risk Information
cvss4
Base: 6.3
Severity: LOW
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/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
References
Description

Suricata is a network IDS, IPS and NSM engine developed by the OISF (Open Information Security Foundation) and the Suricata community. Prior to versions 7.0.13 and 8.0.2, working with large buffers in Lua scripts can lead to a stack overflow. Users of Lua rules and output scripts may be affected when working with large buffers. This includes a rule passing a large buffer to a Lua script. This issue has been patched in versions 7.0.13 and 8.0.2. A workaround for this issue involves disabling Lua rules and output scripts, or making sure limits, such as stream.depth.reassembly and HTTP response body limits (response-body-limit), are set to less than half the stack size.

Published
Date
2025-11-26
Updated
Date
2025-11-26
Risk Information
cvss3
Base: 7.5
Severity: LOW
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
References
Description

Suricata is a network IDS, IPS and NSM engine developed by the OISF (Open Information Security Foundation) and the Suricata community. In versions from 8.0.0 to before 8.0.2, a NULL dereference can occur when the entropy keyword is used in conjunction with base64_data. This issue has been patched in version 8.0.2. A workaround involves disabling rules that use entropy in conjunction with base64_data.

Published
Date
2025-11-26
Updated
Date
2025-11-26
Risk Information
cvss3
Base: 7.5
Severity: LOW
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
References