MAESTRO

Glossary

Version: 1.0.0

Terms

Term Definition
Agent An autonomous software entity that uses an LLM/foundation model to make decisions and take actions toward a goal
Agentic AI AI systems with autonomous decision-making, tool use, and goal-directed behavior
Agentic Risk Factor One of four properties unique to agentic AI that amplify threats: Non-Determinism, Autonomy, Identity Management, and Agent-to-Agent Communication
Attack Complexity A modifier in risk scoring that measures how difficult an attack is to execute. Ranges from Low (easily repeatable) to High (requires specialized conditions). Derived from CVSS methodology.
Attack Surface The total set of points where an attacker can attempt to enter or extract data from a system. In agentic AI, the attack surface includes model inputs, tool interfaces, MCP connections, inter-agent channels, and human interaction points.
Attack Vector The path or method an attacker uses to reach and exploit a vulnerability. Common vectors for agentic systems include network (remote), adjacent (same infrastructure), local (same host), and physical access. Derived from CVSS methodology.
Blindspot Vector (BV) A threat category identified through supplemental MAESTRO analysis that is underrepresented in existing taxonomies (BV-1 through BV-12)
Circuit Breaker A control pattern that automatically halts agent operations when predefined thresholds are exceeded (e.g., cost limits, error rates, action counts)
Confused Deputy A security pattern where an agent with high privileges is tricked into acting on behalf of a lower-privilege entity
Context Window The maximum amount of text (tokens) an LLM can process in a single inference call, including system prompt, conversation history, and retrieved context
Corrective Control A security control that restores the system to a known-good state after a threat has been realized (e.g., rollback, incident response)
Cross-Layer Threat A threat that emerges from the interaction of multiple MAESTRO layers, not visible in single-layer analysis
Defense in Depth A security strategy employing multiple layered controls so that if one layer fails, subsequent layers provide protection
Detective Control A security control that identifies and alerts on threats during or after occurrence (e.g., anomaly detection, log monitoring)
Deterrent Control A security control that discourages threat actors through visibility of security measures (e.g., published monitoring capabilities, red team exercises)
Embedding A numerical vector representation of text, used by RAG pipelines to measure semantic similarity between queries and documents
Embedding Drift Gradual change in the semantic meaning of vector embeddings over time, caused by updates to the embedding model, changes in the document corpus, or adversarial manipulation. Can cause RAG systems to return incorrect or misleading results.
Extended Threat Scenario A threat identified via MAESTRO analysis that goes beyond the base ASI T1-T15 taxonomy (T16-T47)
Fine-Tuning The process of further training a foundation model on domain-specific data to specialize its behavior
Foundation Model A large-scale pretrained model (e.g., LLM) that serves as the base intelligence for an agent
Guardrail A runtime constraint that limits agent behavior, such as input/output filters, content classifiers, or action blocklists
HITL Human-in-the-Loop – a human reviewer who oversees and approves agent actions
Layer (MAESTRO) One of the 7 architectural layers in the MAESTRO framework used for structured threat analysis
MAS Multi-Agent System – multiple autonomous agents coordinating to achieve shared or distributed goals
MCP Model Context Protocol – an open standard for connecting AI assistants with external data sources and tools
MCP Host The application (e.g., AI-powered IDE, desktop app) that initiates MCP connections
MCP Client A protocol client within the host, maintaining 1:1 connections with MCP servers
MCP Server A lightweight program exposing specific capabilities (tools, resources, prompts) via MCP
Mitigation A control or countermeasure that reduces the likelihood or impact of a threat
MVTM Minimum Viable Threat Model – the bare minimum analysis for a useful threat model, covering business context, layer mapping, top threats, trust boundaries, and key mitigations
Non-Determinism The property of agentic AI systems producing different outputs for identical inputs, arising from LLM stochasticity, variable retrieval results, and changing agent state
Policy-as-Code Encoding security and compliance policies in machine-executable format (e.g., OPA Rego, AWS SCPs) for automated enforcement
Preventive Control A security control that stops threats before they occur (e.g., input validation, access controls, sandboxing)
Prompt Injection An attack where adversarial instructions are inserted into an LLM’s input to override its intended behavior or system prompt
RAG Retrieval-Augmented Generation – a pattern where external context is retrieved and provided to an LLM before it generates a response
Residual Risk The risk remaining after mitigations have been applied
Rubber-Stamping When HITL reviewers approve agent actions without meaningful review due to volume or automation bias
Service Account A non-human identity (credentials, API keys, tokens) used by an agent or service to authenticate to other systems. Service account management is a critical concern at L4 (Deployment Infrastructure) and L6 (Security & Compliance).
Supply Chain Attack Compromise of a system through its dependencies, including third-party models, libraries, MCP servers, plugins, or data sources
System Prompt The initial instructions provided to an LLM that define its role, constraints, and behavior boundaries for a given application
Tenant Isolation Controls ensuring that data and operations belonging to one user or organization are separated from those of others in a shared system
Trust Boundary A boundary between zones of different trust levels where security controls must be enforced
Trust Zone A region of the system where components share a common trust level
Vector Database A specialized database optimized for storing and querying high-dimensional vector embeddings. Used in RAG pipelines (L2 - Data Operations) to find semantically similar documents. Examples include Pinecone, Weaviate, Chroma, and pgvector.
Vertical Layer A MAESTRO layer that spans all other layers rather than sitting at a single level in the stack. L6 (Security & Compliance) is the primary vertical layer, as authentication, authorization, and compliance controls must be enforced at every other layer.

Acronyms

Acronym Expansion
A2A Agent-to-Agent — Google’s open protocol for inter-agent communication, enabling agents to discover capabilities and exchange messages across different frameworks
ABAC Attribute-Based Access Control
ASI Agentic Security Initiative (OWASP)
ATLAS Adversarial Threat Landscape for AI Systems (MITRE)
ATT&CK Adversarial Tactics, Techniques, and Common Knowledge (MITRE)
BV Blindspot Vector
CCPA California Consumer Privacy Act
CSA Cloud Security Alliance
CVSS Common Vulnerability Scoring System
CWE Common Weakness Enumeration (MITRE)
DREAD Damage, Reproducibility, Exploitability, Affected Users, Discoverability (risk model)
FedRAMP Federal Risk and Authorization Management Program (US)
GDPR General Data Protection Regulation (EU)
HIPAA Health Insurance Portability and Accountability Act (US)
IAM Identity and Access Management
LLM Large Language Model
MAESTRO Multi-Agent Environment, Security, Threat, Risk, and Outcome
MVTM Minimum Viable Threat Model
NIST AI RMF National Institute of Standards and Technology AI Risk Management Framework
OWASP Open Worldwide Application Security Project
PCI-DSS Payment Card Industry Data Security Standard
RBAC Role-Based Access Control
RCE Remote Code Execution
SBOM Software Bill of Materials
SCP Service Control Policy
SOX Sarbanes-Oxley Act
STRIDE Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege
TOCTOU Time-of-Check to Time-of-Use
WAF Web Application Firewall

Attribution: OWASP GenAI Security Project - Multi-Agentic System Threat Modelling Guide. Licensed under CC BY-SA 4.0.