WARGAME — STRATEGIC SCENARIO

Reputation & Narrative Attack: Tesla

Document Classification: CONFIDENTIAL — Client Deliverable
Product Tier: F3 — Strategic Intelligence (W04 Wargaming Engine)
Report ID: WG-2026-08-REPU-001
Date: August 25, 2026
Target: Tesla (gleif_entity)
Engine: WorldDuplicate 1000-branch Monte Carlo v3.1.0

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EXECUTIVE SUMMARY

Tesla faces a Reputation & Narrative Attack scenario with a baseline Forreast Score of 50/100. A 500-branch Monte Carlo simulation converges to a mean of 54.9 (σ 14.9), with P(critical) = 4.4% and P(high) = 34.2%.

Convergence analysis (Gelman-Rubin R-hat = 1.000 across 4 chains) confirms the distribution is CONVERGED — stable. 5th-percentile tail risk: 29.5. System phase: fluctuation (near equilibrium — moderate fluctuation).

Red/Blue/Green adversarial debate verdict: CONTINGENCY REQUIRED (net risk 63.0). Consensus: CONTINGENCY REQUIRED. Net risk after Red-Blue-Green debate: 63.0. Red impact (16.2) vs Blue mitigation (8.1) → Red dominates. Green observes.

Data basis: 2 real signals from the live intelligence stream (avg severity 0.56), sources: Ahmia, searxng.

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SCENARIO PARAMETERS

Parameter	Value	Source
Scenario	Reputation & Narrative Attack	Forreast scenario library
Branches	500	WorldDuplicate Monte Carlo
Base score	50/100	Forreast Score (live)
Volatility	14.7pt	signal-derived
Signal shock	5.6pt	live signals
P(critical)	4.4%	Monte Carlo
Tail risk (P5)	29.5	Monte Carlo
R-hat	1.000 (converged)	4-chain Gelman-Rubin
Elapsed	0.333s	engine timing

Factor scores (from real signal mix where present):

Factor	Score (0-100)
social_velocity	83.0
response_capacity	81.0
leadership_credibility	65.0
media_sentiment	40.3

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MONTE CARLO DISTRIBUTION

Statistic	Value
Mean	54.88
Median	54.75
Std	14.93
Min / Max	10.7 / 97.7
P5 / P25 / P75 / P95	29.5 / 45.2 / 64.8 / 79.8
P(critical ≥81)	4.4%
P(high ≥61)	34.2%
P(significant ≥41)	81.8%
Tail risk (P5)	29.5

Convergence: R-hat = 1.0000 across 4 chains × 200 branches. CONVERGED — results are stable.

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RED / BLUE / GREEN ADVERSARIAL DEBATE

Red Team (Adversary)

Attack vector: scandal_injection (exploits `media_sentiment`, impact 16.2pt)

Red Team assesses that Tesla's 'media_sentiment' factor (score: 54) is the critical vulnerability. Attack vector: scandal_injection. Projected impact: 16.2 point degradation. Monte Carlo shows P(critical) = 4.4%, tail risk at 5th percentile = 29.5. Recommend aggressive exploitation of this axis.

Blue Team (Client Defense)

Intervention: leadership_change (mitigation 8.1pt)

Blue Team counters: apply 'leadership_change' (effect: -0.15) to harden 'media_sentiment'. Projected mitigation: 8.1 points. Defense capability: pr_counter. Post-intervention Monte Carlo mean shifts from 54.9 to est. 39.9. Recommend immediate pre-positioning.

Green Team (Neutral / Exogenous)

Exogenous event: media_fact_check (intervention probability 31%)

Green Team evaluates: exogenous event 'media_fact_check' has 31% probability of materializing. No immediate green intervention. Balance assessment: 54.9 mean with 14.9 std. System near equilibrium.

Move-by-Move (3 turns)

Turn	Red action	Blue response	Green reaction	ΔScore
1	disinformation_campaign	transparency_drive	media_fact_check	+4.1
2	disinformation_campaign	pr_counter	public_opinion_shift	-2.9
3	disinformation_campaign	pr_counter	regulator_inquiry	+3.5

Consensus: CONTINGENCY REQUIRED

Consensus: CONTINGENCY REQUIRED. Net risk after Red-Blue-Green debate: 63.0. Red impact (16.2) vs Blue mitigation (8.1) → Red dominates. Green observes.

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SENSITIVITY ANALYSIS (TORNADO)

Variable	Swing (pts)	Low → High
base_score	38.9	30 → 70 (35.9 → 74.7)
signal_shock	9.7	0.6000000000000005 → 10.600000000000001 (50.9 → 60.6)
volatility	1.9	22.080000000000002 → 11.040000000000001 (54.8 → 56.7)

Most sensitive variable: base_score (swing: 38.9 points). Model stability: UNSTABLE — high parameter sensitivity.

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SYSTEM DYNAMICS (STOCK/FLOW)

Final risk: 29.3 (initial 50) over 100 steps

Signals detected: 9 | Interventions applied: 9

Detection efficiency: 9.0% | Intervention efficiency: 100.0%

Equilibrium risk: 37.9

System dynamics: risk decreased from 50 to 29.3 over 100 steps. Detection rate: 9.0%. Intervention rate: 100.0%.

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ABNORMALITY DETECTION & BALANCE

Abnormality: Simulation diverges from reality by 4.9 points (0.3σ). Normal — model aligns with reality.

Balance: near equilibrium — moderate fluctuation (phase: fluctuation)

Meadows leverage points:

Leverage point	Level	Effect
Constants and parameters	12	Adjust signal thresholds and alert sensitivity.
Feedback loop delays	9	Reduce time between signal detection and response.
Structure of material flows	5	Redesign information flow between INT disciplines.
Rules of the system	3	Change authority levels and escalation triggers.
Goal of the system	1	Reframe from 'monitoring' to 'anticipatory positioning'.

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AGENT-BASED CASCADE (ABM)

- Agents: 50	Mean health: 0.148 (σ 0.156)
- Cascade events: 44	Target agent health: 0.002

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6-DIMENSION RISK SCORECARD

Dimension	Score (1-5)	Rationale
Exposure	4	Simulation std 14.9pt across 500 branches
Velocity	4	Reputation & Narrative Attack propagates in days-to-weeks
Severity	3	P(critical) 4.4%
Confidence	2	2 real signals underpinning the run
Reversibility	3	Interventions (scenario library) can reduce net risk
Contagion	3	P(high) 34.2% — cascade risk via ABM: 44 events
Composite Risk	19/30 — HIGH	Mean 54.9, σ 14.9, P(crit) 4.4%

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RECOMMENDED ACTIONS

Intervention ladder (by impact):

- `leadership_change` — effect -0.15 on factor scores - `transparency_report` — effect -0.12 on factor scores - `pr_counter_campaign` — effect -0.10 on factor scores - `do_nothing` — effect +0.00 on factor scores

Blue Team priority: deploy `leadership_change` with 8.1pt expected mitigation.

Model driver: `base_score` dominates outcomes (swing 38.9pt) — monitor it first.

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FALSIFICATION CONDITIONS

If the observed Forreast Score of Tesla stays within 1σ of the simulated mean (54.9 ± 14.9) for 90 days, the model's predictive value is confirmed.

If R-hat exceeds 1.1 on the next run, the branch count (500) must be increased.

If real signal volume drops to zero and the run falls back to name-hash factors, the report is a hypothesis, not an evidence-based assessment — re-run after signal recovery.

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Generated by Forreast Intelligence — WorldDuplicate 1000-branch wargaming engine. Montis Sapientia, Fluminis Vis.