- Input Manipulation – Crafted inputs trigger misclassifications or errors
- Data Poisoning – Altered training data introduces bias or backdoors
- Model Inversion – Sensitive data inferred from model outputs
- Model Denial-of-Service – Overloading models with heavy or nested queries
- Model Theft – Unauthorized model replication via APIs or output analysis
- Model Misuse – Using models for spam, fraud, or disinformation
AI Security
Ship AI features your auditors will actually sign off.
CLOUDYRION combines Secure by Design and AI-focused Ethical Hacking to deliver verifiable assurance for LLMs, agents, and RAG pipelines - aligned with OWASP, MITRE, NIST, and EU AI Act standards. Complete assessment and validation in 14 days—evidence-backed, reproducible, and compliance-ready.
Value at a Glance
Our service offering includes:
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AI Secure by Design Controls – Baseline security governance, model hardening, and risk controls established before go-live.
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LLM / Agent / Agentic AI Penetration Testing – Targeted red-teaming of generative models, agents, and pipelines, including structured re-tests and vulnerability validation.
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AI Act / NIS2 Evidence & Runbooks – End-to-end documentation and audit-ready evidence aligned with OWASP, NIST AI RMF, and EU regulatory frameworks.
A look into our KPIs
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- Time-to-Secure Go-Live: Everage time from assessment to compliant, secure deployment.
- Residual Risk Reduction Rate: 90% decrease in high/critical risks after applying CLOUDYRION’s Secure by Design controls.
- Compliance Assurance Score: 90% alignment with key frameworks (e.g. AI Act, NIS2, CRA, NIST AI RMF).
- Evidence Delivery Time: Average time to produce regulator-ready AI Act / NIS2 documentation.
Understanding the Risks
The attack vectors can be mapped to different domains of artificial intelligence: classical machine learning (e.g., classification, regression, clustering, reinforcement learning), Large Language Models (LLMs), and Agentic AI, i.e. systems with one or more collaborating agents. Based on our assessment, the following vectors represent some of the core security risks in modern AI systems:
Classical ML (Machine Learning)
LLM (Large Language Models)
- Prompt Injection & Jailbreaks – Bypassing guardrails through prompt manipulation
- System Prompt Leakage – Exposure of hidden system instructions
- Sensitive Information Disclosure – Leakage of confidential data in responses
- Improper Output Handling – Lack of control over downstream output usage
- Unbounded Consumption – Excessive resource or token use via crafted inputs
Agents/Agentic AI (Autonomous Agents)
- Agent Authorization and Control Hijacking – Unauthorized command execution or privilege escalation
- Agent Critical System Interaction – Unsafe interactions with linked digital or physical systems
- Goal and Instruction Manipulation – Tampering with agent goals or instructions
- Agent Knowledge Base Poisoning – Injected data corrupts reasoning or decisions
- Multi-Agent Exploitation – Exploiting trust or communication flaws between agents
Service Packages
AI Secure by Design Architecture
When does it make sense?
When you’re planning a new AI application (LLM, RAG, Agents) or want to future-proof existing systems. Ideal for engineering teams and CISOs who want to build security in from the start.
Your benefits:
- Realistic attacks reveal manipulation, leakage, and abuse scenarios
- KPIs like jailbreak rate or leakage score make progress clearly measurable
- Re-tests ensure that fixes are effective
Deliverables: Threat models, architecture sketches, guardrail patterns, IAM controls, runbooks
AI Ethical Hacking
When does it make sense?
When AI systems are already in operation or shortly before go-live. Especially suited for security leads and product owners who want to verify whether their AI environments are truly resilient.
Your benefits:
- Technical evidence (tests, logs, runbooks) provides confidence during audits
- NIS2 playbooks ensure you can report incidents within 24h / 72h
- The AI Act dossier saves time and reduces the risk of fines
Deliverables: Applicable PoC attacks, findings reports, re-test protocols
Compliance Kit (AI Act & NIS2)
When does it make sense?
When compliance or legal teams need evidence — or an audit is coming up. Also ideal for organizations that want to implement regulatory requirements proactively.
Your benefits:
- Technical evidence (tests, logs, runbooks) provides confidence during audits.
- NIS2 playbooks ensure you can meet 24h/72h incident reporting obligations in critical situations.
- The AI Act dossier saves time and reduces the risk of fines.
Deliverables: AI Act dossier checklist, technical evidence, NIS2 runbooks (24h/72h), monitoring plan, responsibility matrix
Our Approach: AI Security from Start to Finish
Secure. Repeatable. Auditable. We combine Secure by Design with realistic AI attack simulations to make your AI systems not only more robust, but also fully verifiable.
1Scoping & Preparation
Define objectives, capture the architecture, and model threats (OWASP GenAI / Agentic Threats)
Outcome: Clear scope, threat model, mapping of attack scenarios
2Recon & Information Gathering
Analyze inputs/outputs, plugins, memory, and tools
Outcome: Attack surfaces identified
3Attack Scenario Development
Prompt injection, leakage, poisoning, tool abuse, memory manipulation, orchestration attacks
Outcome: Catalog of realistic attack paths
4Test Execution
Exploratory prompting, automated tools, multi-step exploits, manual exploitation
Outcome: Evidenced findings with reproducible prompts & logs
5Reporting & Mitigation
Technical report, concrete remediation recommendations, re-test protocols, management summary
Outcome: Guardrail hardening, IAM policies, logging, monitoring
6Re-Test & Continuous Ethical Hacking
Verify fixes and enable continuous monitoring
Outcome: Demonstrable resilience over time
Tailored for Your Stakeholders
We provide the right artifacts for every role in your organization — from strategic vision to the code line.
CISO / Security Lead
Problem: Quantifying risks clearly and convincing boards with hard facts.
Solution: Risk mapping, prioritized controls, and pentesting evidence ready for reporting.
Deliverables: Risk map, pentesting logs & replays.
Head of AI / Engineering
Problem: Guardrails, agent permissions, and evaluation methods that are secure and reproducible.
Solution: Security architecture integrated into the development process — evaluation harness, architecture sketches, guardrail patterns.
Deliverables: Stack diagrams, permission models, re-test protocols.
Compliance / Legal
Problem: Clear, audit-proof evidence for regulators and auditors.
Solution: AI Act & NIS2 compliance dossier — including incident runbooks and a responsibility matrix.
Deliverables: Dossier checklist, NIS2 runbooks (24h/72h), technical evidence.
Purchasing / Procurement
Problem: Making service providers comparable and documenting due diligence.
Solution: Due Diligence Pack (governance, SLA, support) — ready to use in vendor management.
Deliverables: NDA/SLA templates, methodology one-pager, sanitized artifacts.
EU Regulations
General Legal Requirements
Everything you need
Upgrade your Cybersecurity Process
Upgrading your cybersecurity process not only strengthens your defense against threats but also integrates security strategies directly into your daily operations. This ensures long-term protection while keeping you agile in the face of new challenges.
Hacking
Ethical Hacking
We help you identify and fix vulnerabilities.Secure by Design
Secure By Design
More than just a service – a guarantee for a secure digital future. Integrate robust security measures from the very beginning into every phase of your system development.Consulting
Strategy Consulting
Team strengths for sustainable internal security expertise and a secure digital future.Frequently Asked Questions
Is your concern unresolved? Feel free to contact us, and together we will find a solution.
Build Trustworthy, Auditable AI Systems
Let’s strengthen your AI architecture against real-world threats and align it with EU standards like AI Act & NIS2. Schedule your consultation today.
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