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Risk Management

Governing Security Risk Assurance at Sizewell C Nuclear

As embedded Cyber Security Consultant at Sizewell C Nuclear, I owned and governed the end-to-end Security Risk Assessment process for assigned technology products and supplier engagements, ensuring rigorous identification and mitigation of threats to UK Critical National Infrastructure.

Client: Sizewell C Nuclear
Delivered: 2024-04-19
Role: Cyber Security Consultant

The Challenge

Sizewell C is a multi-billion pound nuclear infrastructure programme operating under the most stringent regulatory and security obligations in the UK. The programme generates a continuous pipeline of technology procurement decisions, each carrying potential security risk to CNI systems, sensitive data, and nuclear safety operations.

  • Scale and velocity — dozens of concurrent technology workstreams, each generating SRA submissions with varying levels of rigour and threat awareness
  • Inconsistent submission quality — Business Architects and Project Owners submitting SRAs with underweighted risk ratings, missing threat context, or insufficient supplier evidence
  • Supplier assurance gaps — vendors providing self-attested security claims with no independent verification or OSINT-informed challenge
  • Regulatory exposure — the programme's CNI status demands alignment to NIST CSF 2.0, ISO/IEC 27001:2022, NCSC Cloud Security Principles, and ONR SyAPs, requiring a structured and defensible assessment approach
  • No standardised AI and emerging technology risk coverage — SRA submissions were not consistently addressing AI/ML usage, data residency, or third-party model risk

The Approach

The Stephens SRA Framework

To bring rigour, consistency, and defensibility to the SRA process, I developed and implemented a structured assessment framework — the Stephens SRA Framework — built around a master prompt methodology that drives every assessment through a standardised 13-section output structure. This covers executive summary, supplier OSINT review, architecture analysis, AI/ML risk, a 5x5 risk scoring matrix aligned to the Sizewell C Comprehensive Risk Impact Scoring Matrix, and a MoSCoW-prioritised security requirements table.

The framework operates on a "trust but verify" principle:

  • An initial security questionnaire is issued to the supplier at the outset
  • Responses are reviewed and validated against independent OSINT — covering legal entity, certifications, breach history, CVE exposure, financial stability, and sub-processor transparency
  • Where supplier evidence is unavailable or insufficient, assurance gaps are explicitly stated rather than assumed away
  • Risk scoring is applied across five impact domains: Financial Viability, Legal & Regulatory Compliance, Safety & Environmental, Operational, and Reputational

SRA Review and Approval

  • Each SRA assigned to me is reviewed end-to-end, with risk ratings challenged where they do not reflect the CNI threat environment
  • I hold delegated authority from the CISO to approve completed SRAs once material risks are identified and mitigations are agreed and in place
  • Escalation pathways are clearly defined for Very High and High residual risks requiring senior leadership or CISO sign-off
  • Every assessment concludes with a formal recommendation: Accept / Accept with Conditions / Not Recommended

Stakeholder Assurance and Upskilling

  • Worked directly with Business Architects and Project Owners to raise SRA submission quality at source, reducing rework and accelerating approval timelines
  • Provided structured feedback on underweighted or incomplete submissions, building security risk literacy across non-security programme stakeholders
  • Maintained a clear audit trail for every approved SRA, supporting programme governance and regulatory inspection readiness

Programme Metrics

MetricPosition
SRAs reviewed and approved26–50 across active programme workstreams
Submissions challenged or returned for rework25–50% of all submissions received
Escalations to CISORaised where residual risk remained High or Very High post-mitigation
Assessment framework coverage100% of assigned SRAs delivered through the Stephens SRA Framework
Regulatory alignmentEvery approved SRA evidenced against NIST CSF 2.0, ISO 27001:2022 and NCSC Cloud Security Principles
AI/ML risk coverageEmbedded as standard across all assessments — previously an unaddressed gap

The 25-50% challenge and rework rate is the standout figure. In a CNI environment, a low rework rate would suggest either exceptional submission quality or insufficient scrutiny. This rate signals active, expert-level challenge rather than a rubber-stamp approval process.

The Results

  • Delivered a repeatable, CNI-grade SRA framework adopted as the standard assessment approach for assigned technology products across the programme
  • Identified and escalated multiple instances of underweighted risk ratings submitted by BAs and Project Owners, preventing under-assured technology from entering the programme environment
  • Reduced assessment rework through direct stakeholder engagement and structured submission guidance
  • Ensured every approved SRA carries a defensible, evidence-based assurance position aligned to NIST CSF 2.0, ISO 27001:2022, and NCSC Cloud Security Principles
  • Established consistent AI/ML risk coverage as a standard component of every assessment — a gap that previously went unaddressed

Technologies & Frameworks Utilised

Framework / ToolApplication
NIST CSF 2.0Primary risk framework for all SRA assessments
ISO/IEC 27001:2022Control alignment and Annex A mapping
NCSC Cloud Security PrinciplesCloud and SaaS supplier assurance
ONR SyAPsNuclear-specific safety and security alignment
ISO/IEC 27005Risk assessment methodology
OSINT ToolingIndependent supplier verification and breach analysis
Sizewell C Risk Impact Scoring Matrix5x5 risk scoring across five impact domains
MoSCoW PrioritisationSecurity requirements classification and treatment tracking
Security Risk Assessment Risk Matrix

The SRA Framework is use is built on a simple principle: security risk assessments at CNI level must be evidence-led, independently verified, and produce a decision — not a list of observations. Every assessment I approve carries my name and my professional judgement. That accountability is deliberate.

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