Secure development life cycle
Security requirements, threat modelling, code review, testing and vulnerability handling are built into development, following practices such as the NIST Secure Software Development Framework.
GCRI · Cybersecurity and Digital Resilience
Software and safety-critical systems engineering builds software that must not fail dangerously, in medical devices, vehicles, control systems and infrastructure. In this field it connects security to safety: secure development, verification and the assurance that software behaves as intended under attack and fault.
Software and safety-critical systems engineering develops software whose failure could cause harm, loss of life or major disruption. It applies rigorous processes to control-system, medical, aviation and infrastructure software. In cyber and digital resilience and critical infrastructure, safety-critical software practice limits the chance that a software fault cascades through physical infrastructure. It informs assurance requirements for automated control in interconnected systems. The canonical description is on the STEM Commons.
Security requirements, threat modelling, code review, testing and vulnerability handling are built into development, following practices such as the NIST Secure Software Development Framework.
Hazard analysis and threat analysis are performed together so that security measures do not compromise safety functions and vice versa.
Components most exposed to untrusted input are identified for rewriting in memory-safe languages, which removes a large class of vulnerabilities.
Night lights, population density and true-colour imagery over Europe, from NASA GIBS. Each layer carries its own date.
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NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
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Connected activity, framed on Europe.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Layers and dates
Datasets and records used by software and safety-critical systems engineering on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| Vulnerability reports by root cause | Defect classes | REPORTED |
| Static and dynamic analysis results | Code quality | OBSERVED |
| Hazard and threat analyses | Requirements | DECLARED |
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Cybersecurity · Safety-critical and secure · Run R-2252
| REQ-01 safe stop | 32 | 11 | Covered |
| REQ-07 fault detection | 20 | 17 | Gaps |
| REQ-12 timing | 21 | 29 | Covered |
Software is verified through reviews, testing to defined coverage criteria and formal proofs where justified. Independent assessment examines the safety case.
| Check | How it is done |
|---|---|
| Independent verification | Safety-critical software is verified by a team independent of development |
| Coverage measures | Tests meet stated structural coverage criteria |
| Vulnerability root cause tracking | Fixed vulnerabilities are classified by cause to improve practice |
Complex software interacting with uncertain environments cannot be exhaustively tested. Updates and third-party components introduce new failure paths.
Assembled from the Nexus Standards area profile Cyber and digital resilience law alignment: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
Systems and couplings
Controls
NS-10 Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-9 Contextual UNIs (deployments, instances, programme instances)NRS-X6 Cyber and digital security riskNRS-H93 Hazard family: Identity, trust and cryptographic failure (NHS-1 cyber.identity)NRS-K31 Domain pack profile: Cyber national resilience (DOMAIN-031)NRS-H54 Hazard family: Signal and platform disruption (NHS-1 cyber.platform)NRS-H86 Hazard family: Telecom and data-centre failure (NHS-1 infra.digital)NRS-H94 Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)Observation
Example geography
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
The couplings between the systems in safety-critical and secure software: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
Cybersecurity and Digital Resilience stewards software and safety-critical systems engineering for the Consortium and reviews how it is applied across platforms.
Process explorer · Process
8 steps·5 stages
Process
ISO 31000:2018 sets out an iterative risk management process, from scope, context and criteria through assessment and treatment to monitoring, review and reporting.
Outline of an external standard or method, from its public sources. It describes what the framework says, not a record of any run. It does not show that Nexus or any partner performs, certifies or approves a step. A gate is a step of the method, never a Nexus approval.
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