Cyber Risk Forecasts & Track Record

1. Observe What changed? →

2. Understand Why does it matter? →

3. Track How does risk evolve? →

4. Predict What happens next? →

5. Decide What to do? →

6. Verify What happened? →

7. Remember Persistent memory

Predictive Accountability

Probabilities, Not Certainties: Hermes publishes falsifiable threat predictions with explicit deadlines. Every prediction is adjudicated by third-party resolution oracles (CISA KEV, honeypot telemetry, advisory releases) and scored via the Brier Score ($BS$) to penalize overconfidence and hindsight bias.

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🎯 Active & Historical Forecast Record

Explore current probabilistic forecasts, verify ground-truth resolutions, and audit our empirical calibration score:

HERMES FORECAST — FALSIFIABLE PREDICTIONS & ORACLES

RELEASE 2.0 • BRIER SCORE & CALIBRATION

Probabilistic forecasting engine for cyber risk and vulnerability weaponization. Every forecast has a fixed temporal horizon and a deterministic external resolution oracle (CISA KEV, GreyNoise, public weaponized PoC). Reliability is objectively audited against hindsight bias via the Brier score.

Mean Brier Score (BS)

0.1043

58% vs random baseline (0.25)

Resolution Track Record

5 / 13

4 TRUE 1 FALSE

Active In-Flight Forecasts

8

Horizons 14 to 60 days

Calibration Tier

HIGH

BS ≤ 0.15 (High calibration)

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Reliability Diagram & Empirical Calibration (Deciles)

PRINCIPLE P10: NO FAKE PRECISION

A well-calibrated forecast matches predicted probability with empirical realization frequency. The deliberate inclusion of failed forecasts (e.g. CVE-2025-3248) prevents hindsight cherry-picking and confirms epistemic integrity (Principle P5).

Probability Range	Forecast Count	Mean Forecast	Empirical Outcome	Calibration Delta	Visual Balance
0.00 - 0.20	0 (0 resolved)	—	Pending	—
0.20 - 0.40	0 (0 resolved)	—	Pending	—
0.40 - 0.60	0 (0 resolved)	—	Pending	—
0.60 - 0.80	7 (2 resolved)	73%	50%	+0.23
0.80 - 1.00	6 (3 resolved)	87%	100%	-0.13

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Counterfactual 'What-If' Resolution Simulator

Simulate how active predictions would alter the global Brier Score in real-time

Simulated BS: 0.1043 Reset

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All (13) Active Forecasts (8) Resolved Oracles (5)

All Domains 🤖 Agentic AI 🏢 Enterprise 📦 Supply Chain & Cloud

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1. How Accurate Has Hermes Been?

A prediction engine is only as credible as its audited track record. Hermes measures prediction accuracy using the Brier Score:

BS = (1 / N) * SUM_{t=1}^N (f_t - o_t)^2

Where f_t in [0, 1] is the forecasted probability and o_t in {0, 1} is the actual ground-truth outcome. A score of 0.00 represents perfect clairvoyance, while random guessing yields 0.25.

Current Mean Brier Score

0.1043 across verified historical cases, demonstrating superior calibration over unweighted heuristics.

Skill Score vs Random

+58.3% improvement in predictive discrimination compared to uncalibrated baselines.

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2. Forecast Architecture Principles

1. Immutable Records: Once registered, a forecast ID (FC-YYYY-XXX) cannot be edited, deleted, or backdated.
2. Deterministic Resolution: Outcomes are determined solely by verifiable public telemetry, never subjective consensus.
3. No Retrospective Claims: Hermes clearly separates forward predictions made before an event from retrospective re-simulations.