Apache Maka vs Darkmoon: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Apache Maka and Darkmoon — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Apache Maka
The Apache Software Foundation
Apache-licensed local-first agent workspace that runs tools in a sandbox and records every model message and tool call as a recoverable execution log.
Key features
- Append-Only Execution Record: Model messages, tool calls, tool results, permission decisions, and turn termination events are written down durably, so the transcript is evidence rather than a disposable chat buffer.
- Context Trimming Without Data Loss: Old tool output can be omitted from the next prompt to shorten context while the full saved history remains intact and inspectable.
- Single Runtime Host: Desktop, terminal, and evaluation all execute through one runtime, so behavior does not diverge between how you develop and how you benchmark.
- Sandboxed Tool Boundary: Built-in Read, Write, Edit, Bash, Glob, and Grep tools run under a sandbox; anything leaving that boundary requires approval, and Computer Use and catalog skills are opt-in.
- Crash Recovery and Resume: Runs can be aborted, failures are classified, and an interrupted turn can optionally be resumed rather than restarted from scratch.
- Session Branching and Search: The desktop workspace supports creating, archiving, searching, renaming, retrying, regenerating, and branching sessions from any turn.
- Bring Your Own Model: Connect a cloud API, a locally hosted model, or a compatible gateway, with streaming output, thinking, usage reporting, and clearer provider errors.
- Declarative Evaluation Harness: maka eval expands multi-arm experiments into task by repetition by subject cells with immutable per-cell attempts and a result kernel covering score, normalized usage, attributable cost, duration, and failure reason.
- Local-First Storage: Sessions, settings, artifacts, and run records stay on the machine by default, with local memory and optional web search when configured.
Best for
- Auditable Agent Runs: Keeping a defensible record of exactly what an agent did and which permissions were granted during a task.
- Long Coding Sessions: Working through a multi-turn refactor with branching and resume instead of losing state when a turn fails.
- Agent Benchmarking: Running reproducible multi-arm experiments comparing models, prompts, or external agent subjects on the same task set.
- Air-Gapped or Regulated Work: Running an agent workspace where sessions and artifacts must remain on local infrastructure.
- Cost and Usage Analysis: Attributing token usage, cost, and duration per experiment cell to decide which model configuration to ship.
- Terminal Workflows: Driving an agent from the current project directory or scripting a single non-interactive turn from CI or a shell.
- Open-Source Agent Research: Building on a permissively licensed runtime whose execution semantics and architecture are fully documented.
Darkmoon
Darkmoon Project
Open-source autonomous penetration testing platform with 18 AI agents, 80+ integrated tools, live dashboard and publication-ready reports.
Key features
- Multi-Agent Orchestration: Coordinates 18 specialized AI agents that perform distinct pentesting tasks (reconnaissance, exploitation, post-exploitation) to run distributed, autonomous assessments.
- Extensive Tool Integration: Integrates 80+ security tools into a unified workflow, allowing automatic use of scanners, exploitation frameworks, and enumeration utilities without manual tool chaining.
- Live Dashboard Monitoring: Provides a real-time dashboard to observe agent activities, progress, findings, and task status, enabling live oversight and interaction during engagements.
- Evidence Collection & Reproducibility: Captures verifiable evidence (logs, screenshots, commands) for each finding and produces reproducible artifacts that support validation and remediation.
- Publication-Ready Reporting: Automatically generates structured, professional reports summarizing vulnerabilities, impact, steps to reproduce, and remediation guidance suitable for stakeholders.
- Extensibility & Open Source: Distributed under GPLv3 with modular architecture to add custom agents, integrate additional tools, or adapt workflows for specific environments.
- Autonomous Workflow Automation: Chains reconnaissance, exploitation, and validation steps without continuous human intervention to scale routine testing and free analysts for higher-value tasks.
- Autonomous attack orchestration across multiple stages
- 18 specialized agents for different testing tasks
- 80+ integrated security tools
- Live dashboard for monitoring runs
- Publication-ready, evidentiary reports
- Open-source codebase (GPLv3)
- Autonomous multi-agent penetration testing with 18 specialized AI agents
- Integration with 80+ security tools for scanning, exploitation, and analysis
- Live dashboard for real-time monitoring of test progress and agent activity
- Publication-ready, evidence-backed reports for findings and remediation
- Open-source distribution under GPLv3 enabling self-hosting and auditability
- Automated evidence collection and validation of exploits
- Extensible workflows and tool integrations for customizable testing
Best for
- Automated Red Teaming: Run continuous or scheduled autonomous red-team style assessments across an environment to uncover attack paths and validate defenses with minimal human supervision.
- Vulnerability Discovery at Scale: Perform large-scale reconnaissance and automated scanning across many targets using integrated tools to surface emerging vulnerabilities quickly.
- Compliance & Audit Reporting: Generate detailed, reproducible reports for compliance audits that include evidence and remediation steps to demonstrate security posture improvements.
- Security Research & Tooling Integration: Rapidly prototype and evaluate new exploitation techniques by integrating custom tools and agents into Darkmoon’s orchestration framework.
- Continuous Security Testing: Integrate into CI/CD or periodic security workflows to automatically re-assess applications and infrastructure after changes or deployments.
- Incident Reproduction & Forensics: Reproduce exploitation steps and collect verifiable evidence to support incident investigations and post-incident analysis.
- Automated red team / penetration testing
- Continuous security assessments in CI/CD
- Security research and tool evaluation
- Generating evidence-backed reports for compliance
- Integrating multiple pentest tools into automated workflows
- Automated internal and external vulnerability assessments
- Autonomous red-team style engagements and continuous security testing
- Evidence-backed reporting for compliance and remediation tracking
- Proof-of-concept exploit validation and penetration test automation
- Self-hosted security testing pipelines for DevSecOps teams