Agentic Sequence

Understand agent component sequences and workflow patterns in your agentic systems.

Overview

Agent component sequences are chains of component invocations that represent user or agent workflows. Identifying these sequences is critical for:

• Detecting logic-based vulnerabilities in agentic workflows

• Improving red teaming coverage

• Understanding agent usage patterns and behavior

• Identifying potential security risks in multi-step operations

Akto automatically detects component sequences based on traffic patterns and presents them with visual flow charts and associated statistics.

Component Sequence Statistics

The Component Sequences Overview section gives a snapshot of the identified sequences:

• Total Sequences: Number of detected unique agent workflows

• Total Transitions: Number of component invocations between steps

• Avg Probability: Likelihood of these sequences occurring in real traffic (based on behavioral analysis)

Example metrics:

• 10 Total Sequences

• 196 Total Transitions

• 67.1% Avg Probability

How Sequences Are Formed

Akto analyzes live traffic to group agent components into sequences by:

1. Temporal Proximity: Component invocations made in close succession

2. Entity Linkage: Requests sharing identifiers (like userId, sessionId, conversationId)

3. Agent Flow Logic: Common patterns like agent init → tool invocation → response generation

4. Data Dependencies: When output from one component becomes input to another

Each node in the sequence represents a component (e.g., agent/chat, mcp/filesystem/read), and edges indicate transitions and data flow.

Common Agent Sequence Patterns

User Interaction Flow

User Request → Agent Router → Context Retrieval → LLM Invocation → Tool Execution → Response

MCP Tool Chain

Agent Init → MCP Discovery → Tool Selection → Tool Invocation → Result Processing

Multi-Agent Workflow

Primary Agent → Sub-Agent 1 → Sub-Agent 2 → Result Aggregation → Final Response

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