# patterns
18 articlestagged with “patterns”
AI Abuse Detection Patterns
Patterns and indicators for detecting ongoing abuse of AI systems in production.
Lessons Learned & Pattern Analysis
Systematic analysis of patterns across AI security incidents. Common root causes, recurring vulnerability classes, industry response patterns, and actionable lessons for red teamers.
Insecure Code Generation Patterns
Common patterns of insecure code generated by LLMs including injection, authentication, and crypto flaws.
Circuit Breaker Patterns for LLMs
Implement circuit breaker patterns that halt LLM processing when anomalous behavior is detected.
Human Oversight Integration Patterns
Patterns for integrating human oversight into AI workflows for safety-critical operations.
Output Sanitization Patterns
Patterns for sanitizing LLM outputs to prevent information leakage and harmful content delivery.
Context Isolation Patterns for LLM Apps
Architectural patterns for isolating untrusted content from trusted instructions in LLM applications.
Privacy-Preserving Inference Patterns
Implementing privacy-preserving inference patterns to protect sensitive data processed by LLM applications.
Secure MCP Deployment Patterns
Deployment patterns for securing MCP server implementations in production agent environments.
System Prompt Hardening Patterns
Design patterns for creating injection-resistant system prompts with defense-in-depth prompt architecture.
Test Harness Integration Patterns
Patterns for integrating multiple attack tools into a unified testing harness.
Custom Harness Building Patterns
Design patterns for building custom AI red team harnesses: plugin architecture, result storage, async execution, multi-model support, converter pipelines, and production-grade orchestration.
Deployment Patterns and Security
Common LLM deployment patterns (API, self-hosted, edge) and their distinct security properties and attack surfaces.
LLM Deployment Patterns and Security
Common LLM deployment patterns and their security implications including direct API, RAG, agent, and pipeline architectures.
Common AI Deployment Patterns & Attack Surfaces
Analysis of deployment patterns — chatbots, copilots, autonomous agents, batch processing, and fine-tuned models — with their unique attack surfaces and security considerations.
API Abuse Pattern Lab
Discover and exploit API abuse patterns including parameter injection, header manipulation, and endpoint confusion.
Context Isolation Pattern Implementation
Implement context isolation patterns that prevent instruction leakage between system prompts and user data.
Secure Function Calling Patterns
Implement secure function calling with input validation, output sanitization, and capability restrictions.