Apeiron AI
forecast horizon active · 12–18 Sep 2026

Predict. Simulate. Prevent.

Apeiron AI is a predictive defence platform for enterprises that cannot afford to learn about an attack from the incident report. It forecasts the campaigns aimed at your estate, simulates how they would unfold, and prices the interventions that stop them.

Forecast lead time
18 days
Modelled exposure
$214M
Model confidence
91%
live forecast · PRD-4417

BlackFrost exploitation of CVE-2026-48217 in Northstar payment tier

critical

BlackFrost weaponises the SecurePay Gateway deserialization flaw against Northstar's PCI enclave within 18 days.

probability
87%14 / 7d
predicted
model drivers
Weaponised PoC velocity
31
BlackFrost targeting history (financial)
24
Northstar unpatched SecurePay 7.4.2 instances
22
Dark-web access broker listing match
13
propagation preview
Initial accessCredential harvestLateral movementCollection
the shift

Security programmes answer "what is vulnerable?". Boards are asking "what happens next, and what should we do now?"

yesterday · descriptive

The vulnerability inventory

  • A ranked list of findings, sorted by a severity score assigned to the world, not to you.
  • Effort spent on flaws no adversary can reach, while reachable ones age quietly.
  • Detection measured after the fact — the incident defines the lesson.
  • Board reporting reduced to counts: open criticals, mean time to patch.
now · predictive

The forecast and the decision

  • A named adversary, a named asset, a probability and a dated window you can plan against.
  • Priority set by reachability inside your digital twin and by exploit maturity in the wild.
  • Interventions costed before the event: probability removed, loss avoided, days to effect.
  • One narrative from raw signal to board pack, with every claim tied to its evidence.
Worked example. BlackFrost activity against Third-party software supply chain → internet-facing SecurePay Gateway moves CVE-2026-48217 from a queued finding to a 87% forecast on NS-PAY-CLUSTER-01, with $214M modelled impact and a mitigation set that removes most of it inside the window.
platform

Five layers, one causal chain

Each layer feeds the next: what the world is doing, what you are made of, how an attack would travel, what happens if it does, and what stays exposed for the next decade.

Layer 01

Global cyber intelligence

Continuous fusion of adversary infrastructure, exploit maturity, regional campaign pressure and sector telemetry into one coherent picture of the threat environment.

10 monitored regions · BlackFrost targeting score 94
Layer 02

Organisational digital twin

A live model of your estate — identity, payment tier, data vaults, controls and their real efficacy — so exposure is measured against your architecture rather than a generic benchmark.

Crown-jewel reachability, control efficacy and blast radius per node
Layer 03

Attack propagation & supply chain

Trace how an adversary moves from a third-party gateway to a card vault, including fourth-party concentration you never contracted with directly.

SecurePay Gateway → PCI Card Vault traced in 4 hops
Layer 04

Simulated futures & interventions

Run the campaign before the adversary does. Every mitigation is scored on probability reduction, loss avoided, cost and time to effect.

FROSTGATE staged run · 9 costed interventions
Layer 05

Quantum risk horizon

Inventory long-lived cryptography against cryptanalytically-relevant quantum arrival estimates, and sequence migration by data lifetime, not by hype.

9 crypto systems inventoried · harvest-now exposure modelled
credibility model

Every number states how it knows

Prediction is only useful if it is auditable. Apeiron AI labels each value in the product with its epistemic status, so an analyst can tell a measurement from a model output at a glance — and defend the difference to a regulator.

Forecasts carry a confidence band, named drivers with weights, and the underlying evidence records with observation timestamps.

observed

Observed

Directly measured — telemetry, scans, vendor disclosures, adversary infrastructure we can see. No inference applied.

inferred

Inferred

Derived from correlated observations: attribution, asset ownership, reachability and posture recalculations.

predicted

Predicted

Model output with an explicit probability, confidence band and named drivers. Always attributable to its evidence.

simulated

Simulated

Counterfactual results from scenario runs — what would happen under a chosen adversary path or intervention set.

who it is built for

Estates where the second-order effects are the real loss

Financial institutions

Payment tiers, PCI enclaves and interbank settlement paths carry regulatory clocks as well as loss exposure. Apeiron attaches both to every forecast.

8-K materiality clock attached to each critical prediction

Critical infrastructure

OT-adjacent estates need propagation modelling, not vulnerability counts. Twin-based reachability shows which flaws actually touch operations.

Cross-domain propagation from IT ingress to operational assets

Security leadership

Board-grade narrative in the same system as the analyst evidence, so the number briefed upstairs is the number the SOC is working.

One corpus, from raw signal to board pack
10
Regions modelled
5
Tracked adversaries
9
Crypto systems inventoried
9
Costed interventions

Figures describe the Northstar Financial reference deployment used throughout this environment.

The next campaign against your estate is already forming

Step into the live Northstar Financial environment and follow the BlackFrost forecast from raw signal to a costed decision.