Estimated Runtime and Cost for a Full Pentest Cycle with Shannon: Technical Benchmarks and Optimization

A complete Shannon pentest cycle typically finishes in 1–1.5 hours and costs approximately $50 USD when using Claude 4.5 Sonnet, delivering automated five-phase security analysis through orchestrated LLM agents.

The KeygraphHQ/shannon repository implements an AI-driven penetration testing framework that automates complex security assessments via the Temporal workflow engine and Anthropic’s Claude models. Understanding the estimated runtime and cost for a full pentest cycle with Shannon enables security teams to budget API expenses and infrastructure resources accurately when scaling continuous security validation.

Runtime and Cost Benchmarks for Shannon Pentesting

Shannon’s full assessment cycle is engineered to balance thorough coverage with practical resource constraints.

Wall-Clock Runtime: 1–1.5 Hours

A complete end-to-end pentest usually completes within 1–1.5 hours according to the project documentation【README line 476】. This duration encompasses five coordinated phases: Pre-Reconnaissance, Reconnaissance, Vulnerability Analysis (executed by five parallel agents), conditional Exploitation, and final Reporting.

API Cost: Approximately $50 USD per Run

The workflow consumes Anthropic’s Claude 4.5 Sonnet model, which at current pricing translates to roughly $50 per full test【README line 477】. Costs scale with model pricing updates and target application complexity, as larger attack surfaces generate additional tool output requiring LLM synthesis.

Architectural Drivers of Runtime and Cost

Shannon’s performance characteristics stem from specific implementation choices in its orchestration layer and AI integration.

Five-Phase Pipeline Execution

In src/temporal/workflows.ts, the Temporal workflow engine sequences five distinct phases, handling retries, heartbeats, and parallelism. The Vulnerability Analysis phase specifically launches five parallel agents to accelerate coverage, while the Exploitation phase executes conditionally based on discovered vulnerabilities. This structured orchestration adds predictable overhead compared to ad-hoc scripting.

Claude 4.5 Sonnet Integration

The src/ai/claude-executor.ts file wraps Claude 4.5 Sonnet calls via the Claude Agent SDK, enforcing a 10,000-turn limit per session and implementing cost-tracking hooks. By maintaining a single persistent session throughout the workflow rather than spawning multiple concurrent LLM instances, Shannon minimizes redundant context initialization overhead.

Temporal Orchestration Overhead

The src/temporal/activities.ts implementation executes external security tools (nmap, subfinder, whatweb) within isolated Docker containers. While this ensures reproducible environments, Docker startup and tool execution I/O contribute significantly to the total wall-clock time, as the LLM must wait for tool output before proceeding to analysis phases.

Optimizing Shannon Pentest Duration and Expense

Security teams can adjust runtime and cost through configuration flags and infrastructure choices.

Skipping External Scans with PIPELINE_TESTING Mode

Enable PIPELINE_TESTING=true to bypass external reconnaissance tools (nmap, subfinder, whatweb), reducing both runtime and API consumption:

# Skip external scans for faster validation cycles

PIPELINE_TESTING=true ./shannon start URL=https://target.example.com REPO=target-app

This mode executes only the internal analysis phases, shaving significant minutes off the standard 1–1.5 hour window while reducing Claude API calls.

Resource Configuration Best Practices

Configure the Docker runtime and Temporal worker pools in docker-compose.yml to prevent resource contention:

# Excerpt from docker-compose.yml for resource optimization

services:
  temporal-worker:
    deploy:
      resources:
        limits:
          cpus: '4'
          memory: 8G
    environment:
      - TEMPORAL_MAX_CONCURRENT_ACTIVITY_EXECUTIONS=10

Allocating sufficient CPU and memory prevents container throttling during parallel vulnerability analysis, ensuring the five agents complete without artificial delays.

Key Implementation Files

Understanding these source files clarifies how Shannon achieves its 1–1.5 hour runtime and $50 cost structure:

File	Role
src/temporal/workflows.ts	Defines the five-phase pipeline and parallel agent orchestration
src/ai/claude-executor.ts	Wraps Claude 4.5 Sonnet with cost tracking and turn limits
src/temporal/activities.ts	Implements tool execution (nmap, subfinder) in Docker containers
docker-compose.yml	Configures Temporal stack and resource allocation
README.md	Documents the 1–1.5 hour runtime and ~$50 cost benchmarks

Summary

• Runtime: Shannon completes full pentest cycles in 1–1.5 hours through Temporal-orchestrated parallel execution.
• Cost: Each run costs approximately $50 USD using Claude 4.5 Sonnet, with expenses scaling by target complexity.
• Architecture: Five-phase pipelines in src/temporal/workflows.ts and single-session LLM management in src/ai/claude-executor.ts optimize resource usage.
• Optimization: Enable PIPELINE_TESTING=true to skip external scans and reduce both time and API consumption.

Frequently Asked Questions

What factors can increase Shannon pentest runtime beyond 1.5 hours?

Complex target applications with extensive attack surfaces generate larger tool outputs (nmap scans, subfinder results) that require more processing time by the Claude 4.5 Sonnet model. Additionally, enabling conditional exploitation phases or increasing the TEMPORAL_MAX_CONCURRENT_ACTIVITY_EXECUTIONS beyond default limits can extend duration due to Docker resource contention.

Can I reduce the $50 cost per Shannon pentest?

You can lower costs by setting PIPELINE_TESTING=true to skip external reconnaissance tools, significantly reducing Claude API calls. Alternatively, targeting smaller application subsets or reducing the number of parallel vulnerability analysis agents (configured in src/temporal/workflows.ts) decreases token consumption, though this trades thoroughness for savings.

How does PIPELINE_TESTING mode affect the pentest cycle?

When PIPELINE_TESTING=true is exported before running ./shannon start, the workflow bypasses external network scanning tools including nmap, subfinder, and whatweb. This mode executes only internal analysis phases, typically reducing runtime by 20–30 minutes and cutting API costs proportionally while still performing vulnerability analysis against provided source code repositories.

What LLM model does Shannon use for security analysis?

Shannon utilizes Anthropic’s Claude 4.5 Sonnet model via the Claude Agent SDK, as implemented in src/ai/claude-executor.ts. The implementation maintains a single persistent session throughout the five-phase workflow with a 10,000-turn limit, optimizing context retention while controlling costs compared to spawning multiple concurrent model instances.

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