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Threat Modeling Methodologies: STRIDE and PASTA — A Chaotic TA's Guide for IoT/OT

This lesson explains two practical threat-modeling methodologies—STRIDE for quick component checks and PASTA for deep, attacker-centric scenario analysis—applied to IoT/OT systems. It covers why threat modeling matters for cyber-physical systems, step-by-step usage for both methodologies, examples (PLC firmware update and connected vehicle telematics), AI-assisted tooling considerations, quick templates, and actionable closing guidance.

Content Overview

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Threat Modeling Methodologies: STRIDE and PASTA — A Chaotic TA's Guide for IoT/OT

Opening motivation

You already poked firmware, mapped OT networks, and obsessively refreshed SBOMs. Now let us stop improvising and start predicting the bad things that will happen before they do.

Lesson scope and framing

This lesson builds on our previous excursions through defense-in-depth for IoT/OT , device lifecycle and patching , and automotive/transportation concerns . We will translate that gritty, hardware-flavored knowledge into two practical threat modeling methodologies: STRIDE and PASTA . Think of STRID...

Why threat modeling matters for IoT/OT

Why threat modeling matters for IoT/OT (and why you should care) IoT and OT systems are cyber-physical: breaches can flip switches, derail trains, or brick medical devices. Patch cycles are long and provenance is messy (hello, SBOM gaps). Threat modeling forces you to be intentional about where...

STRIDE overview, usage, and PLC example

STRIDE: Fast, focused, and excellent at pointing fingers STRIDE is an acronym for six threat categories: S poofing identity T ampering with data R epudiation I nformation disclosure D enial of service E levation of privilege Why STRIDE here? Because for IoT/OT you need a taxonomy yo...

PASTA overview and connected vehicle example

PASTA: The cinematic, attacker-centric multi-act play PASTA stands for Process for Attack Simulation and Threat Analysis . It is a seven-stage methodology that centers on understanding attacker intent and modeling attack scenarios end-to-end. PASTA stages (compressed): Define objectives (busi...

STRIDE vs PASTA comparison

STRIDE vs PASTA: When to use which (table time) Dimension STRIDE PASTA Speed Fast Slow(er) Depth Shallow to moderate Deep and scenario-driven Best for Checklists, quick audits Comprehensive risk programs Output Threat list per component Attack paths, risk treatment...

AI in threat modeling: benefits and caveats

AI and threat modeling: friend or bad karaoke partner? AI can help accelerate both methods: Automate component inventory from network scans and SBOM data. Generate candidate threats from STRIDE templates for each component. Simulate attack chains in PASTA with probabilistic scoring. But w...

Templates, checklist, closing, and takeaways

Quick templates and cheats Pseudocode for a simple risk score using STRIDE outputs: for each component: for each threat in STRIDE: likelihood = estimate_likelihood(threat) impact = estimate_impact(threat) # factor in physical consequences score = likelihood * impact rank threats by score ...

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