Your Threat Surface Index (TSI) is a single number that captures how likely you are to attract trouble and how much damage it can do.
It blends three factors:
These combine into one score:
You do not need to love math. The key idea is simple:
“The risk of being who you are.”
Measures how much adversarial pressure you face.
Factors we look at:
Input source: A structured Hostility survey and threat research.
👉 [Take the Hostility Index survey]
“The risk of how you live and work online.”
Measures behavioral exposure.
What we look at:
Input source: A detailed Privacy Practices survey.
Where to start:
👉 [Start a Privacy Practices assessment]
PPI is treated as a brake in the math:
We normalize your PPI score, then apply
f(PPI) = 1 / (1 + PPI_norm)
Better practices lower PPI_norm, so f(PPI) gets closer to 1.
Risky behavior pushes PPI_norm up and drags f(PPI) down, which lowers your TSI.
In plain terms: good habits are rewarded. Bad habits stop you from ever being “low risk,” even if no one hates you.
“The risk of what leaks and what can be used against you.”
Measures your public digital footprint.
What we look at:
Input source: ObscureIQ Footprint Audit.
Where to start:
👉 [Schedule a Footprint Audit]
FI is treated as an amplifier:
We normalize FI and apply
g(FI) = 1 + FI_norm
Cleaner footprint keeps g(FI) close to 1.
Large exposed footprint pushes g(FI) above 1 and multiplies your risk upward.
Your final TSI score blends all three:
TSI = (HI ÷ 10) × f(PPI) × g(FI)
Typical ranges:
Often celebrities in controversy, executives in hot litigation, or principals with recent threats.
You receive:
Scale: 0 to 159 points.
We divide HI by 10 to set your baseline risk factor.
Example: HI 92 → 9.2 baseline.
We collect your raw PPI survey score.
Normalize it relative to our client population.
Compute f(PPI) = 1 / (1 + PPI_norm).
If you are disciplined with privacy, f(PPI) stays closer to 1.
Sloppy practices pull f(PPI) down and stop your TSI from ever being low.
We compute your raw FI from the audit.
Normalize it across our client base.
Compute g(FI) = 1 + FI_norm.
A smaller footprint keeps g(FI) near 1.
Large exposed footprint pushes g(FI) above 1 and magnifies your TSI.
Multiply the three factors:
Example:
HI = 96 → 9.6
f(PPI) = 0.8
g(FI) = 1.4
TSI = 9.6 × 0.8 × 1.4 ≈ 10.7 (Moderate–High)
Hostility captures who you are and why anyone would target you.
PPI rewards habits you can control.
FI captures what is already out there and weaponizable.
The final TSI balances intrinsic risk, lifestyle choices and data exposure into one index that can move over time as we improve your posture.
Client: Sample Executive
Date: [Month] [Day], [Year]
Hostility Index Score
Drivers of Hostility
Role sensitivity
Public-facing CEO of a controversial company.
Regular media exposure.
Recent media spikes
Two negative news cycles in the last 90 days.
Active social media campaigns criticizing company decisions.
Litigation and regulatory activity
Named party in an ongoing civil lawsuit.
Under current regulatory scrutiny.
Extremist or fringe chatter
Low but nonzero mentions on fringe forums.
One historical threat report from three years ago.
Category Breakdown
(0 = none, 5 = extreme)
Interpretation
This client sits in a sustained high-hostility band.
Risk is driven more by public role and controversy than by direct threats.
Short term volatility is expected around key events and news cycles.
Prescribed Actions to Lower HI
Together those three steps generate your Threat Surface Index and the remediation roadmap that follows.