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FICTIONAL PLANNING REGISTER

World-event scenarios, 2027–2036

Explore 3,000 annualized scenario rows from the supplied workbook. Every row is fictional, every numerical estimate is source-authored and non-calibrated, and every consequence path is illustrative rather than predictive.

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FICTIONAL SCENARIO — NOT HISTORICAL, NOT A FORECAST The provenance of this block requires editorial review.
Confidence
Source-bounded scenario register
Sources
1
Independent corroboration
0
Date range
2027–2036
Review
Exact workbook bytes preserved; scenario assumptions, baselines, and estimates require claim-specific review
How to read this register

FICTIONAL SCENARIO — NOT HISTORICAL, NOT A FORECAST. Probability fields are source-authored analytical estimates, not calibrated forecasts and not additive. Consequence scores are comparison aids, not expected casualties, financial losses, or site rankings. Coordinates are broad centroids, not target locations.

Scenario rows
3,000
Scenario tracks
300
Years
2027–2036
Rows per year
300
Baseline source URLs
19

FICTIONAL SCENARIO — NOT HISTORICAL, NOT A FORECAST

2029-S122Track W003Q2 2029

Iran nuclear threshold or safeguards crisis — 2029 outlook

Nuclear proliferation / safeguards crisis · Tehran and Persian Gulf region

Nuclear / WMD · Moderate 15.3% source estimate · magnitude 5/5 · priority 5/5

FICTIONAL SCENARIO — NOT HISTORICAL, NOT A FORECAST

2029-S259Track CH007Q3–Q4 2029

Large earthquake strikes a major urban fault zone — 2029 outlook

Earthquake / urban catastrophe · Istanbul or a comparable high-exposure metropolitan fault zone

Climate / health · Low 9.3% source estimate · magnitude 5/5 · priority 3/5
FICTIONAL SCENARIO — NOT HISTORICAL, NOT A FORECAST The provenance of this block requires editorial review.
Confidence
Moderate-high
Sources
1
Independent corroboration
0
Date range
Q2 2029
Review
Scenario premise, probability, and consequences require claim-specific review

FICTIONAL SCENARIO — NOT HISTORICAL, NOT A FORECAST

SOURCE ROW 615 · TRACK CE068

Frontier AI models and compute clusters: Supply-chain compromise propagates across vendors — 2029 outlook

In 2029, the modeled trigger or precursor is: Against a background of rapid capability gains, concentrated expertise and strategic competition over general-purpose AI, a trusted update, component or managed service is found to have distributed unauthorized access across many organizations. The affected environment is model weights, training data, safety evaluations, agentic tools and high-end compute. The compromise exploits concentration and trust relationships rather than a single target, producing simultaneous investigations across countries and sectors. The scenario matters because compromise can accelerate rival programs, enable scalable abuse or undermine confidence in critical AI deployments. Near-term exposure remains high because legacy systems, concentrated cloud services and accelerated AI adoption are outpacing defensive modernization. The annual probability is an approximate analytical estimate of 31.9% (Elevated), with consequence magnitude 5/5. This row is a plausible, overlapping scenario—not a prediction.

Stable scenario ID
2029-S014
Track ID
CE068
Illustrative window
Q2 2029
Category
Cyber / espionage
Impact scope
Global
Outcome direction
Adverse
Broad geography
San Francisco Bay Area and major AI-compute hubs · United States / China / European Union / Global
Coordinate precision
Technology-cluster centroid; not a data-center coordinate
Confidence label
Moderate-high
Operational use
Not allowed by this educational transformation

SOURCE-AUTHORED ANALYTICAL ESTIMATE — NOT CALIBRATED OR ADDITIVE

Annual estimate
31.9%
Band
Elevated
Magnitude
5/5
Weighted score
31.9/100
Planning priority
5/5

Workbook formula: probability ÷ 100 × magnitude × 20. It is a comparison aid only. Scenario probabilities overlap and must not be summed.

Scenario premise

Against a background of rapid capability gains, concentrated expertise and strategic competition over general-purpose AI, a trusted update, component or managed service is found to have distributed unauthorized access across many organizations.

Named actor classes

state intelligence services; AI laboratories; cloud providers; insiders; criminal groups; regulators

Warning indicators

similar anomalies across unrelated organizations; emergency vendor advisories; certificate revocations; unusual update behavior; sudden procurement holds

Indicators are planning prompts, not proof that the scenario is occurring and not a monitoring or targeting instruction.

Key uncertainties

how far the compromise propagated, whether dormant access remains and whether a state, criminal group or insider is responsible

ILLUSTRATIVE CONSEQUENCE PATH — NOT A PREDICTION

Conditional consequence sequence

  1. 0–30 days

    If this scenario occurs in 2029: Organizations disconnect affected products, delay operations and compete for scarce forensic and replacement capacity. Sector-level effects include model access is suspended, credentials are rotated and regulators demand evidence about the scope of exposure.

  2. 1–3 years

    During 2030–2032: Governments mandate software bills of materials, stronger supplier assurance and coordinated disclosure while affected vendors lose market access. Over one to three years, labs adopt classified-style compartmentation, stronger compute monitoring and international controls on high-risk capabilities.

  3. 4–10 years

    Across 2033–2039: Supply chains become more transparent but also more regionalized, with governments treating key digital components as strategic goods. Over four to ten years, frontier AI development consolidates among a smaller number of highly regulated firms and states, with persistent espionage pressure.

Baseline source — not endorsement of this scenario or estimate

OECD AI Policy Observatory; used for AI incidents, governance and frontier-model risk framing.

Open the workbook’s baseline source

BASELINE START POINT ONLY

Track evidence review remains open

Review ID
SER-CE068
Review state
READY FOR CLAIM-SPECIFIC REVIEW
Premise verification
NOT REVIEWED
Probability calibration
NOT PERFORMED
Independent origins
0
Assignment state
OPEN_UNASSIGNED

A source relationship records where review can begin. It does not verify this fictional premise, calibrate the annual estimates, validate the consequence path, or grant operational authority.

Open the claim-specific review docket

ASSUMPTION IS NOT FACT

Track assumptions and retirement remain open

Assumption ID
SAR-CE068
Premise review
NOT REVIEWED
Indicator review
NOT REVIEWED
Retirement state
NOT EVALUATED

The sidecar exposes dependencies, disconfirming questions, alternative explanations, false-alarm risks, consequence interruptions, and retirement triggers. It does not predict, monitor, or retire this track.

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Safety and use boundary

High-level defensive cyber/counterintelligence scenario; no exploit, persistence, evasion or targeting instructions are included. This site adds no tactical target data, exploit steps, evasion methods, weapon construction, casualty optimization, or authorization for real-world action.

SOURCE-AUTHORED ANALYTICAL ESTIMATE — NOT CALIBRATED OR ADDITIVE

Ten-year track: CE068

The workbook annualizes the same scenario family once per year so readers can compare how its assumptions and numerical estimates change. This is not a time-series forecast.

Source-authored annualized rows for track CE068
YearScenario IDProbabilityBandMagnitudeWeighted scorePriorityConfidence
2027 2027-S022 26.9% Moderate 5/5 26.9 5/5 Moderate-high
2028 2028-S019 28.3% Moderate 5/5 28.3 5/5 Moderate-high
2029 2029-S014 31.9% Elevated 5/5 31.9 5/5 Moderate-high
2030 2030-S014 31.6% Elevated 5/5 31.6 5/5 Moderate-high
2031 2031-S016 32.7% Elevated 5/5 32.7 5/5 Moderate-high
2032 2032-S014 35.3% Elevated 5/5 35.3 5/5 Moderate-high
2033 2033-S012 37.5% Elevated 5/5 37.5 5/5 Moderate-high
2034 2034-S014 39.1% Elevated 5/5 39.1 5/5 Moderate-high
2035 2035-S015 40.6% Elevated 5/5 40.6 5/5 Moderate-high
2036 2036-S014 40.7% Elevated 5/5 40.7 5/5 Moderate-high

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Scenario-register literacy

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