Accelerated Innovation

Ensuring You Have the Threat Modeling Capabilities to Win

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Ensuring You Have the Threat Modeling Capabilities to Win

Description

Threat Modeling helps organizations systematically identify, assess, and mitigate potential security threats to GenAI systems across their lifecycle. This capability focuses on embedding structured, proactive risk analysis into development workflows-before vulnerabilities can be exploited.

Why it's Important

GenAI systems introduce novel threat vectors that traditional security reviews often overlook. From data leakage via prompts to adversarial manipulation of training data, these risks can be difficult to detect without deliberate and structured analysis. Threat Modeling ensures that teams proactively surface risks early-before solutions go live-and that mitigations are baked into design, not retrofitted after deployment. By institutionalizing Threat Modeling, organizations can avoid high-impact security failures, reduce costly rework, and build trust with users and stakeholders.

Why it's Challenging @ Scale

  • Rapidly evolving threat landscape: New GenAI-specific vulnerabilities emerge constantly, making it difficult to maintain current, actionable threat models.
  • Lack of GenAI-specific frameworks: Traditional threat modeling tools are often too generic to capture the unique risks introduced by LLMs and dynamic model behaviors.
  • Limited team expertise in AI threats: Most development and security teams lack experience with GenAI-specific attack vectors, increasing the risk of gaps or false assumptions.
  • Siloed development and security workflows: Without tight integration, threat modeling often becomes an afterthought instead of a proactive, embedded practice.
  • Difficulty scaling across teams and use cases: Creating reusable templates and processes that work across diverse models, tools, and use cases can be challenging.

Complexity

High: Maturing Threat Modeling capabilities requires cross-functional coordination, specialized expertise in GenAI security risks, and well-integrated processes across the development lifecycle.

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Taking Action

Though most organizations begin their GenAI journey with significant knowledge gaps, there are targeted actions that can be taken to accelerate the process. Select your group’s current maturity, based on your assessment results, and act today.

  • Explore Key Concepts & Best Practices: Complete the Secure AI Best Practices workshop (2 hrs.) to understand foundational key concepts and explore applied best practices.
  • Introducing Secure AI Design Principles.
  • Framing Security in AI Lifecycle Context.
  • Mapping Threat Surfaces in GenAI Systems.
  • Identifying Roles and Responsibilities in Secure AI.
  • Linking Security to AI Governance Goals.
  • Define Your Action Plan: Outline concrete, prioritized steps your organization will take to implement GenAI Strategy.
  • Align on your Current State and define your Target State.
  • Create an actionable enablement plan.
  • Define target timeline and measures of success.
  • Deliver Quick Wins: Small, high-impact GenAI projects that can demonstrate tangible value in a short time frame.
  • Build a GenAI threat catalog for a known use case: Create a lightweight list of relevant threats for a pilot application to enable targeted risk analysis.
  • Pilot threat modeling with cross-functional teams: Conduct a simple workshop that brings product, security, and AI teams together to map risks for an upcoming GenAI feature.
  • Introduce a threat modeling checklist: Equip teams with a practical tool they can use to flag common GenAI risks during early solution design.
  • Complete one or more of our Deep Dive Courses: Begin exploring key concepts and best practices, including:
  • Secure AI Governance & Accountability Best Practices.
  • Secure AI Risk Management Best Practices.
  • Secure AI Security Controls Best Practices.
  • Secure AI Prompt Injection Best Practices.
  • Secure AI Sensitive Information Best Practices.
  • Secure AI Supply Chain Risks Best Practices.
  • Secure AI Model Poisoning Best Practices.
  • Secure AI Output Handling Best Practices.
  • Secure AI Excessive Agency Best Practices.
  • Secure AI System Prompt Risks Best Practices.
  • Secure AI Vectorization Risks Best Practices.
  • Secure AI Misinformation Best Practices.
  • Secure AI DDoS Prevention Best Practices.
  • Nail It Before You Scale It: Assess and optimize your solution or process before adopting it at scale
  • Assess Your Proposed Solution or Process: Validate whether your current threat modeling workflows surface meaningful GenAI-specific risks and result in concrete mitigations.
  • Define in-scope Processes and Guardrails: Identify which GenAI projects, use cases, or models require threat modeling-and the governance rules that apply.
  • Close any Data or Measurement Gaps: Ensure threat modeling activities are consistently tracked and tied to measurable outcomes like reduced vulnerabilities or faster approvals.
  • Define Your Adoption & Scaling Plan: Create a structured roadmap for how GenAI solutions will be rolled out across teams, workflows, or business units
  • Define Your Phased Implementation Plan: Prioritize rollout based on GenAI risk profile, use case complexity, and business criticality.
  • Build Awareness and Finalize Enablers: Deliver onboarding, templates, and tools to help teams adopt threat modeling practices with minimal friction.
  • Operationalize Your Comms Plan: Communicate clearly how and when threat modeling is expected, and the support available to teams.
  • Formalize Your Best Practices: Document and standardize what’s working to ensure consistent, scalable success across teams and use cases
  • Create reusable threat modeling templates: Provide teams with standardized formats for capturing threats, mitigations, and residual risk.
  • Publish threat modeling guidance by use case: Offer concrete examples that illustrate how to apply threat modeling to common GenAI scenarios.
  • Integrate threat modeling into solution design reviews: Make threat modeling a required checkpoint before GenAI systems move to build or test.
  • Accelerate Your Adoption: Intensify efforts to embed GenAI across your organization by expanding use cases, increasing user engagement, and removing adoption barriers
  • Expand threat modeling to all GenAI use cases: Ensure that both pilot and production systems undergo consistent threat review.
  • Automate threat modeling triggers and reminders: Use project data to flag when a threat model is needed and notify responsible owners.
  • Train product teams to self-model risks: Enable frontline teams to conduct lightweight modeling without security team dependency.
  • Celebrate Your Wins: Publicly acknowledge team accomplishments to build and sustain adoption momentum
  • Highlight GenAI projects that modeled and mitigated risk: Share stories of how early threat modeling averted problems downstream.
  • Reward teams with high-quality threat models: Recognize thoroughness, creativity, and practical action in threat assessments.
  • Communicate risk reduction metrics: Showcase measurable impacts of threat modeling such as fewer security escalations or faster approvals.
  • Streamline & Embed: Integrate GenAI into core workflows while eliminating friction points to make usage seamless and routine
  • Embed threat modeling into DevOps pipelines: Trigger automated prompts to complete threat reviews during early development stages.
  • Pre-fill models with common GenAI threat patterns: Use tooling to suggest likely risks based on use case type and architecture.
  • Connect threat models to risk dashboards: Provide leadership with real-time visibility into GenAI risk exposure and mitigation progress.
  • Leverage Automation: Use GenAI-powered tools and workflows to streamline repetitive tasks, enhance operational efficiency, and reduce manual effort
  • Use AI-assisted threat modeling tools: Automate initial threat identification based on system architecture and data flows.
  • Auto-tag risks with severity and ownership: Streamline triage and follow-up using rule-based logic tied to your governance system.
  • Continuously monitor model behavior for threats: Feed telemetry into threat modeling updates to reflect live system dynamics.
  • Evolve & Further Accelerate: Continuously refine GenAI strategies based on insights and outcomes, while expanding into more complex or high-impact use cases
  • Update threat catalogs based on live findings: Capture emerging GenAI threats from red teams, bug bounties, or incident response.
  • Expand to next-gen GenAI systems: Apply threat modeling practices to agents, multi-modal systems, and fine-tuned proprietary models.
  • Benchmark maturity vs. industry peers: Use external comparisons to refine your threat modeling posture and drive competitive advantage.

Key "Watchouts"

  • Treating threat modeling as a one-time task: Risks evolve quickly-especially in GenAI. Static models quickly become outdated.
  • Overloading teams with complex tooling: If tools are too technical or time-consuming, teams may skip the process entirely.
  • Failing to tailor models to GenAI use cases: Generic threat frameworks may miss AI-specific risks like model leakage or jailbreaking.
  • Omitting cross-functional input: Security teams alone often lack context on AI functionality-product and engineering must be involved.
  • Using models that don’t lead to action: Threat modeling should directly inform mitigations, not just documentation.

Targeted Benefits

  • Earlier identification of GenAI risks: Risks are uncovered during design-not after deployment-reducing rework and exposure.
  • Faster, more secure go-to-market: Structured threat analysis helps teams make security a strength, not a blocker.
  • Stronger alignment across teams: Cross-functional threat modeling builds shared understanding and better decision-making.
  • Reduced impact of security incidents: Early mitigations mean fewer disruptions and lower response costs when issues arise.
  • A reputation for secure-by-design innovation: Customers and regulators trust GenAI systems that are visibly and proactively risk-managed.

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Eddie
Accelerated Innovation

Hi, I'm Eddie 👋

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