LLM threat modeling
Systematic threat identification, risk assessment, and control mapping for enterprise AI deployments — aligned with the OWASP Top 10 for LLM Applications framework.
Why LLMs need threat modeling
LLMs introduce a fundamentally different threat surface than traditional applications. They process natural language inputs without strict input validation, making them vulnerable to semantic attacks. Traditional AppSec threat models (STRIDE, DREAD) don't capture AI-specific risks like prompt injection, data exfiltration through conversation, and model manipulation.
OWASP Top 10 for LLMs — PromptWall coverage
| ID | Threat | Risk | PromptWall Control |
|---|---|---|---|
| LLM01 | Prompt Injection | Critical | Multi-layer detection with ML classifiers, pattern matching, and semantic analysis |
| LLM02 | Insecure Output Handling | High | Output content filtering and sanitization before rendering to users |
| LLM03 | Training Data Poisoning | High | RAG pipeline security and input validation for fine-tuning workflows |
| LLM06 | Sensitive Information Disclosure | Critical | PII masking, document leak detection, and credential scanning |
| LLM07 | Insecure Plugin Design | Medium | Guardrail enforcement and action validation for AI agent tools |
| LLM09 | Overreliance | Medium | Human oversight policies and confidence thresholds |
Threat modeling methodology
- Identify AI assets — Map all AI tools, models, providers, and data flows in your organization.
- Classify data sensitivity — Determine what data types flow through each AI interaction (PII, credentials, IP, internal docs).
- Map OWASP threats — For each AI application, assess which OWASP LLM threats apply based on architecture and usage patterns.
- Assess risk — Score each threat by likelihood and business impact. Use AI risk management frameworks.
- Map controls — For each high-risk threat, identify the detection and enforcement controls needed.
- Verify and iterate — Regular red teaming validates that controls are effective against evolving threats.
Mitigate LLM threats
Deploy PromptWall controls mapped to OWASP Top 10 for LLMs.
Frequently asked questions
What is the OWASP Top 10 for LLMs?+
The OWASP Top 10 for Large Language Model Applications is a framework identifying the ten most critical security risks in LLM deployments. It covers prompt injection, insecure output handling, training data poisoning, model denial of service, supply chain vulnerabilities, and more.
How often should I update my LLM threat model?+
Review quarterly at minimum. Update whenever: new AI tools are adopted, new use cases are deployed, the threat landscape changes (e.g., new attack techniques), or regulatory requirements evolve. Continuous monitoring through PromptWall provides real-time threat intelligence.
Do I need a separate threat model for each AI application?+
Each application has unique risks based on its data sensitivity, user base, and AI provider. A shared base threat model (covering common LLM risks) should be customized per application. Focus customization on data classification, access controls, and business impact.