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The Challenge: Why Traditional Cybersecurity Falls Short

In classical IT environments, security validation is largely about identifying and fixing known weaknesses. Vulnerability scans, penetration testing, and static code analysis answer the question: “Can the system be broken into?”

For web applications or enterprise IT, this approach is usually enough. Vulnerabilities such as SQL injection or authentication bypass have well-understood impacts (data theft, unauthorized access) and fixing them reliably mitigates the risk.

But cyber-physical systems – such as autonomous vehicles, industrial controllers, spacecraft, or medical devices – operate at the intersection of software and the physical world. Here, the question is no longer just “Is there a vulnerability?”, but rather:

• What happens if this vulnerability is triggered?
• Could manipulated data or unexpected states lead to unsafe behavior?
• Do system reactions under attack create cascading real-world risks?

This is where traditional IT security testing reaches its limits – and where Model-Based Cybersecurity Validation begins.

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Our Philosophy: Security Is About Impact, Not Just Vulnerabilities

Security is not defined by the number of vulnerabilities, but by the severity of their consequences.

Our service focuses on the impact of flaws, not just their existence. While penetration tests are essential, they cannot answer questions such as:

• Will a single corrupted sensor input destabilize the entire control logic?
• Does a timing delay create hazardous physical outputs?
• Can a failsafe mechanism be bypassed, leaving the system in an unsafe state?

Only by modeling system behavior under compromised conditions can these risks be revealed, prioritized, and mitigated effectively.

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Compliance, Standards, and Future-Proofing

Regulatory frameworks increasingly expect evidence of safety beyond checklists:

• ISO/SAE 21434 (automotive cybersecurity) requires that security goals are clearly defined and that their achievement can be demonstrated throughout the system lifecycle. While the standard does not prescribe specific methods, in practice this means that goals must be supported by evidence of how the system actually behaves under defined conditions – not merely by documentation.
• ISO 26262 requires that faults are analyzed to determine whether they can lead to hazardous states. Only those faults with the potential to cause a hazardous event must be addressed with safety mechanisms. Demonstrating this requires analyzing system behavior under fault conditions.

Compliance & Model-Based Cybersecurity

Regulation / Standard	What it requires	Where Model-Based Cybersecurity helps
ISO/SAE 21434 (Automotive Cybersecurity)	Definition of cybersecurity goals and requirements, risk assessment (TARA), lifecycle-wide cybersecurity processes.	– Demonstrates through attack simulations that security goals hold under real operating conditions. – Provides auditable evidence of system behavior in compromised states. – Complements TARA with behavioral validation.
ISO 26262 (Functional Safety)	Faults must be analyzed to determine whether they can lead to hazardous states. Those classified as hazardous through the HARA process must be assigned an ASIL level and addressed with appropriate safety mechanisms.	– Fault injection and simulation identify which faults actually lead to hazardous states. – Demonstrates how safety mechanisms respond under cyber-physical attack conditions.
NIS2 (EU Cybersecurity Directive)	Proportionate technical, operational, and organizational risk management measures; service continuity.	– Shows how cyber-physical attack scenarios could affect continuity of essential services. – Provides auditable proof that “proportionate technical measures” are effective. – Eases audits by demonstrating control effectiveness in simulation.
FDA Cybersecurity Guidance (Medical Devices)	Requires cybersecurity risks to be documented, verified, and validated in clinical context.	– Digital twins and simulations model critical device failures and patient safety impacts. – Provides auditable validation of watchdogs, failsafes, and safety mechanisms.
ECSS Standards (Space Systems)	Require modeling of faults, demonstration of fault tolerance, reliability, and security validation.	– Fault injection and attack simulations demonstrate that spacecraft cannot enter unsafe states. – Bridges safety and security validation through system-level modeling.
NIST AI RMF / EU AI Act	AI systems must be trustworthy, risk-assessed, and validated across their lifecycle.	– Proxy models and scenario-based simulations show AI behavior under malicious or unexpected inputs. – For AI-driven CPS (e.g., autonomous vehicles), validates that unsafe states are not reached.

Current industry practice often meets these requirements superficially, through static coverage reports or manual edge-case tests. Our service provides the systematic, simulation-based validation that regulators and auditors will increasingly expect.

Importantly: our approach represents the forward-looking standard of security validation – helping clients stay ahead of compliance demands.

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Conclusion: Where Traditional Testing Ends, Qyntar Begins

Model-Based Cybersecurity Validation is the next step in securing critical systems.

• It does not replace penetration testing – it extends it.
• It shifts the focus from “Are there vulnerabilites?” to “Can those vulnerabilities cause real harm?”
• It delivers systematic, auditable evidence of resilience.

In industries where safety, reliability, and trust are paramount, our approach ensures that your systems are not only compliant – but truly secure.

Whether you design autonomous vehicles, medical devices, industrial robots, or defense systems, we help you prove one thing with confidence: your technology cannot enter unsafe states, even under attack.

Our Toolkit and Methodology

We bring together engineering-grade tools and cybersecurity expertise:

• Model-based design : Captures system behavior and decision logic.
• Formal verification: Identifies code-level issues (memory, overflow, determinism).
• Digital twin environments: Enable safe, repeatable testing of attack scenarios.
• Model-in-the-Loop (MIL) & Hardware-in-the-Loop (HIL): Validate security at different integration levels.

This enables us to not only detect flaws, but also prove system resilience under stress, with visual and auditable evidence.

Business Value Beyond Compliance

Our service is not just a security add-on – it delivers tangible business benefits:

• Reduced late-stage costs: Fewer critical fixes during final integration.
• Optimized design effort: Avoids unnecessary overengineering.
• Faster audits: Clear, auditable simulation evidence.
• Stronger reputation: Demonstrable resilience builds trust with customers, regulators, and investors.
• Future readiness: Aligns with evolving standards and expectations.

In short, we help organizations move from reactive security to proactive, impact-driven resilience.

Attack Scenarios We Simulate

We replicate realistic cyber-physical attack vectors, such as:

• Sensor manipulation (e.g., GPS spoofing, false temperature readings)
• Control signal tampering (e.g., unsafe actuator commands)
• Logic disruption (e.g., invalid state transitions, bypassed failsafes)
• Timing-based attacks (e.g., synchronization faults, induced delays)
• Fail-unsafe conditions (e.g., systems continuing operation unsafely after faults)
• Safety control bypasses (e.g., watchdogs, supervisory checks)

Beyond single attacks, we chain scenarios to expose cascading risks – the kind most dangerous in the real world.