Estimate what a cyber incident could cost your energy operations.
Use public cyber benchmarks to model a typical one-time impact, a severe stress case, and an expected annual exposure number for your site or portfolio.
The calculator runs in-browser after access is granted, and share links include inputs in the URL, so avoid sensitive values.
1
Enter capacity
Use a single site, a regional portfolio, or your full fleet in MW or GW.
2
Set planning likelihood
Choose a conservative, moderate, or elevated annual likelihood for budgeting and tabletop discussions.
3
Use the three outputs
Median for planning, severe for stress testing, and ALE for annual exposure conversations.
Inputs
%
Likelihood is a planning lever, not a claim. Set it to fit your operating environment, control maturity, and risk appetite.
Under the hood: we normalize selected public anchors into $/MW and scale linearly to your capacity.
Impact overview
Typical one-time impact (median)
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Severe one-time impact (high end)
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Expected annual impact (ALE)
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How to read this: typical is a median planning anchor, severe is a high-end stress case from selected public incidents, and expected annual impact is the median multiplied by your planning likelihood.
Executive brief
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- Use typical impact for budget and board discussions.
- Use severe impact for tabletop exercises and resilience planning.
- Use ALE as a simple annual exposure number, not a forecast.
Method, benchmarks, and sources
What the cost represents
Public figures can reflect different components. In practice, a material incident often includes some mix of:
- Incident response: containment, forensics, restoration, and overtime
- Operational disruption: downtime, lost production, manual workarounds
- External support: IR retainers, OT specialists, legal, PR, notifications
- Regulatory and contractual impacts: penalties, audits, customer remediation
Method (transparent math)
impact_per_MW = published_amount_USD / reference_MW
one_time = impact_per_MW * your_capacity_MW
ALE = one_time(median) * (annual_likelihood / 100)
Reference MW is disclosed per benchmark so the normalization is auditable.
Assumptions and limitations
- Linear scaling is an intentional simplification for executive translation (blast radius and architecture vary).
- Benchmarks mix different bases (demand vs paid vs disclosed costs vs survey medians). Each row is labeled.
- Expected annual impact (ALE) is a planning metric. It is not a forecast and not underwriting.
Security and privacy
- Registration details are used only to provide access to this page.
- No external scripts/fonts and no third-party network calls (links below are only for user navigation).
- Share links encode inputs in the URL query string. Avoid using sensitive values if you plan to share.
Benchmarks in use
Toggle benchmarks on/off for sensitivity or to align the basis (demand/paid/disclosed/survey). This updates the results above.
Benchmarks and citations
| Benchmark | Published | Basis | Reference MW | Normalized | Sources |
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Normalized impact summary (selected benchmarks)
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Legal / usage
BreachCalc is an executive translation aid. It is not financial, legal, or insurance advice.
Public figures may not represent total loss. Use with professional judgement.