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AI Security

AI security is essential when AI is integrated into value-creating business processes. TRUSTEQ supports you in aligning your cybersecurity with the challenges of artificial intelligence.

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AI on the Rise – Cybersecurity Falling Behind

89%
of companies already use generative AI in critical business processes.
Source: Forrester
29%
of companies with AI systems have already reported security breaches.
Source: Gartner
20%
of companies are actively working to mitigate AI-related risks.
Source: McKinsey & Company

The rapid advancement of artificial intelligence offers tremendous opportunities, but it also introduces significant risks. One of the greatest challenges is implementing AI securely without creating new security vulnerabilities or weaknesses. Protecting sensitive data and preventing cyberattacks and unauthorized AI manipulation are especially critical.

Our Offering

Artificial intelligence is becoming an integral part of modern business and everyday life. To harness its full potential, AI systems must be deployed and operated securely. Without the right safeguards, organizations risk exposing sensitive data, violating ethical principles, and falling short of regulatory requirements, which can result in significant financial, legal, and reputational damage.

We help companies protect their AI applications, reduce security and compliance risks, and build trust in AI-driven solutions. Secure and responsible AI adoption is the foundation for sustainable innovation and long-term competitiveness.

Today’s Cybersecurity

… is falling behind

AI applications are exposed to entirely new types of attacks and therefore require new and different protection measures in addition to traditional security methods.

… must adapt

How is data processed in an AI context? Questions of transparency and accountability often remain unanswered, especially when using third-party AI models.

… treats AI like normal applications

Using AI with sensitive customer data or code can lead to data leaks. Employee training and clear policies are essential.

… is under pressure

Security and compliance teams must address new risks but often lack the necessary methods, resources, or standards to deal with AI-specific threats.

Today’s Cybersecurity

… is falling behind

AI applications are exposed to entirely new types of attacks and therefore require new and different protection measures in addition to traditional security methods.

… must adapt

How is data processed in an AI context? Questions of transparency and accountability often remain unanswered, especially when using third-party AI models.

… treats AI like normal applications

Using AI with sensitive customer data or code can lead to data leaks. Employee training and clear policies are essential.

… is under pressure

Security and compliance teams must address new risks but often lack the necessary methods, resources, or standards to deal with AI-specific threats.

Today’s Cybersecurity

… is falling behind

AI applications are exposed to entirely new types of attacks and therefore require new and different protection measures in addition to traditional security methods.

… must adapt

How is data processed in an AI context? Questions of transparency and accountability often remain unanswered, especially when using third-party AI models.

… treats AI like normal applications

Using AI with sensitive customer data or code can lead to data leaks. Employee training and clear policies are essential.

… is under pressure

Security and compliance teams must address new risks but often lack the necessary methods, resources, or standards to deal with AI-specific threats.

Building Essential AI Security Capabilities Across the AI Lifecycle

1. Strategize & Govern

Sets goals, guardrails, and accountability

Clearly defined strategies and organizational structures create the framework for the secure use of AI across the entire company. They regulate responsibilities and, through tailored controlling of key metrics, enable transparency and effective governance.

2. Develop & Test

Secure development of AI applications

Embedding AI security early in the development process—through qualified teams, clear standards, and consistent approaches to identifying and reducing risks. Complementary technical security measures and corresponding capabilities ensure an appropriate level of protection.

3. Operate & Use

Enables the secure use of AI

Secure, controlled, and auditable operation, as well as responsible use of AI, supported by clear processes, monitoring, and user enablement.

Get in touch with our experts

Customised advice tailored to your strategic goals and regulatory requirements.

Arrange an expert discussion

AI Security Offerings

AI Threat Modeling
We identify relevant AI use cases, analyze risks and vulnerabilities, and develop prioritized security measures. These can be implemented through pilot projects and tailored playbooks. The outcome includes documented risk assessments, catalogs of measures, and roadmaps for operationalization.
Model Scanning
After model sourcing and before deployment, AI model scanning enables early detection of security-relevant vulnerabilities, backdoors, or malicious payloads in selected models before damage can occur.
AI Governance
AI governance ensures the responsible, efficient, and secure use of AI, minimizes a wide range of risks, and strengthens trust and transparency in the handling of AI.
Continuous Automated Red Teaming (CART)
CART uncovers vulnerabilities in highly dynamic and complex systems at an early stage. As a vendor-independent implementation partner, we support our customers from tool selection through implementation to production rollout.

Our Team

Artur Rösch

Head of Cybersecurity

“Our goal is to identify potential security risks, define clear protective measures, and ensure compliance with regulatory requirements.”

Artur Rösch

Head of Cybersecurity

Florian Weiß

Head of AI Security

Florian Weiß

Head of AI Security

Christine Buchmiller

Senior Consultant

Christine Buchmiller

Senior Consultant

AI Security

AI on the Rise – Cybersecurity Falling Behind

89%

of companies already use generative AI in critical business processes.

29%

of companies with AI systems have already reported security breaches.

20%

of companies are actively working to mitigate AI-related risks.

Our Offering

Today’s Cybersecurity

… is falling behind

… must adapt

… treats AI like normal applications

… is under pressure

Today’s Cybersecurity

… is falling behind

… must adapt

… treats AI like normal applications

… is under pressure

Today’s Cybersecurity

… is falling behind

… must adapt

… treats AI like normal applications

… is under pressure

Building Essential AI Security Capabilities Across the AI Lifecycle

1. Strategize & Govern

Sets goals, guardrails, and accountability

2. Develop & Test

Secure development of AI applications

3. Operate & Use

Enables the secure use of AI

Get in touch with our experts

AI Security Offerings

AI Threat Modeling

Model Scanning

AI Governance

Continuous Automated Red Teaming (CART)

Our Team

Artur Rösch

Artur Rösch

Florian Weiß

Florian Weiß

Christine Buchmiller

Christine Buchmiller

Maximilian Eckert

Maximilian Eckert

Do you have any Questions?