AI Security – Protection against cyber attacks

AI Security encompasses the protection of AI systems against manipulation, data misuse and attacks – as well as the secure use of AI to detect and defend against threats.

AI Security refers to the use and protection of artificial intelligence in a security context. On the one hand, it involves protecting AI systems themselves against manipulation, data poisoning or unauthorised access. On the other hand, AI Security uses intelligent algorithms to detect threats more quickly, automatically fend off attacks and optimise security processes. The aim is a holistically secure, more resilient IT ecosystem.

AI shifts the focus from reactive to proactive security: it identifies patterns, anomalies and risks at an early stage and automates complex analyses.

AI is revolutionising the approach to security by making threat detection and response increasingly automated and proactive. Instead of merely reacting to attacks, organisations can identify risks at an early stage and take preventive action. By analysing vast amounts of data in real time, AI recognises even complex patterns and unknown attack vectors. This transforms cyber security from a reactive discipline into a learning, adaptive system. 

AI takes the pressure off analysts, prioritises alerts, detects unknown attack patterns and speeds up response times – making the SOC smarter, more efficient and more proactive.

AI makes SOCs and SIEM platforms significantly more powerful by automating routine analyses and reducing alarm floods. It helps minimise false alarms, identify unknown attack patterns and drastically shorten response times. Analyses that used to take hours are now completed in seconds. This transforms the SOC into an intelligent, proactive cyber security control centre. Security analysts retain strategic control. The result is a ‘human-in-the-loop’ approach, where AI supports the work of experts and makes decisions more informed, faster and more secure.

Prompt injection is an attack technique in which AI models are tricked into performing undesirable or malicious actions through manipulated inputs (prompts). Attackers attempt to circumvent the system’s original instructions – for example, to disclose confidential information, bypass security policies or alter the AI’s behaviour. Prompt injection is considered one of the key emerging threats in the field of generative AI and requires specific protective measures such as input filtering, context validation and continuous monitoring.

Materna supports organisations in analysing AI deployment scenarios, assessing the security posture whilst taking system architecture into account, and creating a risk profile as a basis for targeted protective measures, for example through a detailed Threat Analysis and Risk Assessment (TARA) document. Using a structured maturity analysis of your AI security architecture, we identify deviations from recognised best practices. Based on this gap analysis, we develop a prioritised roadmap and address critical vulnerabilities in a targeted manner.

Simulations of realistic attacks, such as indirect prompt injections or jailbreaks, can be carried out as a one-off or on an ongoing basis. The findings are incorporated directly into hardening strategies and training programmes.

The development of secure AI architectures focuses on the key security objectives of confidentiality, integrity, availability and traceability. Hardening measures such as input/output guards, dual LLM designs for secure agent systems and human-in-the-loop mechanisms ensure reliable operation.

Our services include the technical securing of workflows, interfaces and plug-ins, as well as monitoring and logging to detect suspicious activity. In addition, we advise on the implementation of Security-by-Design and DevSecOps in software development and carry out code reviews.

We support you with practical training on attack scenarios and best practices. The aim is to raise awareness of AI risks among staff and managers.

We can help you develop clear guidelines, roles and processes for the safe use of AI, and assist with the implementation of standards such as ISO/IEC 42001 and the requirements of the EU AI Act or the GDPR. In addition, we can support you in carrying out audits and fulfilling your reporting obligations.

Your data is the key to successful AI systems and deserves the highest level of protection. We develop comprehensive measures to safeguard sensitive data through pseudonymisation, encryption, secure storage solutions and Data Loss Prevention (DLP). Particularly in RAG environments, we ensure that your information remains confidential and secure by implementing clear access controls and safeguards against data leakage.

Continuous monitoring of models, APIs and workflows enables the early detection of suspicious activity. By integrating with existing SIEM solutions, anomalies are transparently flagged and forwarded to Security Operations in real time. This allows you to take the right action quickly in the event of an incident.

We develop precise procedures for security incidents involving AI systems, covering everything from detection and analysis to a structured response. Tailor-made playbooks ensure that your teams can act quickly and in a coordinated manner in the event of an incident.

This includes assessing third-party AI providers, models and services for security and compliance risks. This makes dependencies transparent and enables you to reliably minimise risks throughout the supply chain.