AI Security Workshop – Using Artificial Intelligence Safely, in Compliance, and Resiliently
AI applications, RAG systems, and API-based AI services open up new opportunities for companies, but at the same time create new attack vectors. Prompt injection, data exfiltration, manipulated models, and insecure interfaces can jeopardize sensitive information, business processes, and customer trust. Added to this are requirements for compliance, governance, and integration into existing cybersecurity frameworks.
Our AI Security Workshop helps you systematically identify risks, review existing AI solutions, and develop effective protective measures. Together, we’ll examine your models, data flows, integrations, and security processes and develop a practical approach for the secure, auditable, and scalable use of artificial intelligence.
Here's what the AI Security Workshop is all about
- Transparency Regarding Vulnerabilities, Security Risks, and Compliance Gaps
- Specific Protective Measures for Models, Data, APIs, and RAG Workflows
- Real-world tests against current AI threats and attack patterns
- Integrated Security Controls for Secure AI Operations
- Roadmap for Continuous Validation, Monitoring, and Further Development
Content and Agenda of Our AI Security Workshop
The workshop is tailored to your specific AI systems, infrastructure, compliance goals, and current security maturity level. The three pillars can be addressed together or, as needed, as separate areas of focus. We also offer a quick assessment option.
Module 01
Analyze existing AI solutions and assess risks
Result: A clear overview of your current risk and compliance situation, including initial prioritized areas of action for management and security officers.
- List of models used, RAG pipelines, data sources, and system integrations
- Analysis of system boundaries, model behavior, and potentially exposed interfaces
- Development of a threat model for relevant attack surfaces and scenarios
- Assessment of risks based on likelihood of occurrence, impact, and business relevance
- Alignment with the GDPR, ISO 27001 principles, and your internal security policies
Module 02
Effectively Securing AI Components
Result: A multi-layered security concept with specific controls for input, processing, data access, and output.
- Protective measures against harmful content, misuse, and the unintended disclosure of personal information
- Filters and policy controls for detecting and defending against prompt injection attacks
- Securing RAG Applications Through Document Verification, Trusted Sources, and Controlled Outputs
- Protecting APIs through secure authentication, authorization, key management, and access limits
- Implementation of monitoring, logging, and audit trails for traceability and incident response
- Integration of controls into existing IT security and operational processes
Module 03
Test effectiveness and continuously improve
Result: Demonstrable effectiveness of your security measures and a robust approach to sustainable AI security.
- Conducting penetration tests and red team exercises for AI models and applications
- Testing for resistance to jailbreaks, tampering, and malicious inputs
- Stress tests for critical system components and security controls
- Regression testing following changes to the model, data, or configuration
- Definition of appropriate KPIs, metrics, and regular review cycles
- Establishment of a continuous validation and improvement process
Sie suchen etwas anderes? Alle KI-Workshops im Überblick.
Who is the AI Security Workshop intended for?
The workshop is designed for companies and teams that want to develop, operate, or scale AI systems securely.
- CIOs, CISOs, and IT management
- Security Engineers, Architects, and DevSecOps Teams
- Manager of AI, Data, and Platform Architectures
- Data Protection, Compliance, and Governance Officers
- Companies with internal AI assistants or RAG systems
- Organizations with external APIs, customer-facing AI, or third-party integrations
Tangible results—that’s what you’ll get after the AI Security Workshop
After the workshop, you will have concrete information to help you make decisions and technical recommendations for the secure operation of your AI solutions.
- Security Assessment Report: Analysis of the AI Security Landscape, Including Risk Assessment, Prioritization, and Recommended Actions
- Security Pipeline Concept: Optionally includes multi-layered protective measures ranging from input validation to output control
- Technical Documentation: Architecture , Configuration, Policies, and Operational Recommendations Related to Existing IT Security Processes
- Audit Readiness: Audit-Ready Documentation for Governance, Compliance, and Internal Control Requirements
- Testing and Monitoring Strategy: Recommendations for Recurring Security Tests, KPIs, and Control Mechanisms
- Scaling Roadmap: Next Steps, Responsibilities, Timeline, and Priorities for Further Development
AI Security Workshop: Group Size, Location, and Cost
To ensure that the organization, timing, and impact are optimally aligned, we clarify the parameters early on and tailor the format and scope to your goals.
- Group size: Workshops for up to 20 people (larger groups upon request)
- Location & format: on site at your premises, remote or hybrid; on request in our office in Munich
- Cost: Depends on the scope, number of systems, and extent of testing—available upon request
- Additional Services: Follow-ups , Penetration Testing, Red Teaming, Implementation, Secure MLOps, and Security Training
Your contact for the AI Security Workshop
About Ventum Consulting
With over 20 years of consulting experience, we combine in-depth expertise in the implementation of digital innovations—such as artificial intelligence—with tried-and-true methods.
Over 20 years of leadership experience
Leadership, Digitalization, and Culture: A Joint Perspective.
Practical rather than theoretical
Make AI applications a tangible part of day-to-day management.
Leadership Focus
People, teams, and collaboration are at the heart of everything we do.
Hands-On AI Experience
Real AI tools, prompting, and management use cases included.
Integrated Governance & Data Protection
Security and compliance are built right in from the start.
Sustainable Change
Your teams learn directly from real-world experience, with a focus on a long-term culture of learning and leadership rather than short-term initiatives. Project.
Our references and projects
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- Transparent: Systematically Identify Vulnerabilities, Weaknesses, and Compliance Gaps
- Field-Tested: Testing AI Systems Against Prompt Injection, Jailbreaks, Data Leaks, and Other Threats
- Effective: Protect models , RAG pipelines, data, and APIs with multi-layered security controls
- Auditable: Establish governance, monitoring, logging, and evidence of compliance
- Sustainable: Establish continuous testing, clear responsibilities, and a prioritized security roadmap
TISAX and ISO certification apply only to the Munich location
Your message
FAQ – Frequently Asked Questions About the AI Security Workshop
No. The workshop is suitable for both production-ready AI systems and applications in the development or pilot phase. For planned solutions, we review the architecture, data flows, and potential risks early on to ensure that security is taken into account from the very beginning.
Among other things, we will examine large language models, internal AI assistants, RAG applications, chatbots, API-based AI services, and integrations with cloud and enterprise systems. The exact scope will be defined jointly in advance.
Depending on the system, we test for prompt injection, jailbreaks, data leakage, model manipulation, insecure API access, toxic content, and vulnerabilities in RAG pipelines, among other things. The tests are tailored to your specific threat scenarios.
Yes. The workshop takes into account relevant requirements from the GDPR, ISO 27001, internal policies, and your existing governance guidelines. The goal is to align technical security measures with organizational and regulatory requirements.
No. We take a technology-neutral approach and evaluate tools based on their security level, integrability, cost, and long-term suitability. This may include open-source frameworks, cloud services, or existing security solutions.
You’ll receive a structured assessment of your AI security, a prioritized list of risks, specific protective measures, and recommendations for testing, monitoring, and governance. Depending on the scope of the project, this may also include technical documentation, security controls, or a detailed implementation plan.
With constantly changing models and systems, a one-time check is often not enough. That is why, upon request, we develop a continuous approach that includes recurring penetration tests, regression checks, KPIs, monitoring, and clearly defined responsibilities.