​

TL;DR Summary

Krkn is a modern, distributed, self-contained, streaming-first cracking orchestration system designed for cloud, containers, segmented networks, and long-term cracking intelligence.

Hashtopolis is a traditional centralized cracking management platform designed around shared storage and classic server-agent models.

Both are excellent tools — they simply optimize for very different deployment philosophies and very different operational goals.

​

Part 1 — High-Level Explanation

​

What is the core difference?

Krkn is a modern, cloud-native distributed cracking platform designed around:

• Self-contained jobs
• Pull-based workers
• High-performance networking
• Minimal infrastructure assumptions
• Persistent encrypted hash intelligence and historical result reuse
• Automation-first control plane with webhooks and APIs

Hashtopolis is a traditional server-based cracking management system designed around:

• Central file storage
• Agents that download tasks and files
• A classic web application architecture
• Ephemeral task execution without long-term intelligence memory

---

​

The User Interface

​

Krkn

• CLI-driven, API-driven system
• The CLI is:
  • Just a client to the control plane
  • Scriptable
  • Automatable
  • CI/CD friendly
• Humans are optional
• Designed to be:
  • Embedded into pipelines
  • Driven by schedulers
  • Triggered by other systems
  • Used headless

​

Hashtopolis

• UI-driven system
• The web interface is:
  • The primary control plane
  • The primary workflow engine
  • The primary integration surface
• Automation is secondary
• Humans are in the loop by default

​

How work is sent to workers

​

Krkn

• Workers (Tentacles) connect to a controller (Krkns).
• When ready, they ask for work.
• They receive everything needed to execute the job in one package:
  • Hashes
  • Wordlists
  • Rules
  • Masks
• No shared filesystem is required.
• Before any job runs, hashes are checked against the encrypted intelligence store and previously cracked results are reused automatically.

​

Hashtopolis

• The server tells agents what to do.
• Agents then download files separately from a central file store.
• The job references files by ID or path.
• Previously cracked data is not treated as a first-class, reusable intelligence source.

---

​

Persistent Hash Intelligence (Major Architectural Difference)

​

Krkn

• Maintains a system-local, encrypted key-value database of:
  • Hashes
  • Cracked passwords
  • Metadata
• Encryption key:
  • Is system-specific
  • Rotates daily
• This allows:
  • Instant re-query of previously cracked hashes
  • Deduplication across jobs
  • Historical cracking reuse
  • Long-term cracking intelligence accumulation
• Jobs automatically benefit from everything the system has ever cracked before.

​

Hashtopolis

• Oriented around:
  • Task execution
  • File-based results
• No first-class, encrypted, system-wide cracking intelligence database
• Historical results are not treated as a core optimization primitive.

---

​

Access Control & Multi-Tenancy

​

Krkn

• Built-in user ACL system:
  • Controls access to jobs, results, datasets, and system functions
  • Designed for multi-user, multi-role environments
• Enables:
  • Operator roles
  • Read-only auditors
  • Automation accounts
  • Segmented access to cracking infrastructure

​

Hashtopolis

• Has mature user and permission management
• Tightly coupled to the PHP web application model

---

​

Real-Time Automation & Webhooks

​

Krkn

• Provides webhook support for:
  • Job start
  • Job completion
  • Chunk completion
  • New crack events
  • Error conditions
• Enables:
  • Real-time dashboards
  • SIEM/SOAR integration
  • Slack/Discord alerts
  • Automated follow-on actions (password resets, ticketing, reporting, etc)
• Designed to act as part of a larger automated security pipeline, not just a cracking box.

​

Hashtopolis

• Primarily UI-driven
• Limited external automation hooks
• Oriented toward human-driven workflows

---

​

Why this matters

​

Krkn advantages

• Works extremely well in:
  • Containers
  • Cloud environments
  • VPN / NAT / segmented networks
• No shared storage required
• Simpler deployment model for distributed workers
• Better performance over unreliable networks
• Workers are autonomous and self-scheduling
• Builds long-term cracking intelligence over time
• Integrates cleanly into automated security workflows

​

Hashtopolis advantages

• Mature and battle-tested
• Full-featured web UI
• Centralized file storage saves bandwidth
• Easier for non-developers to customize agents
• Strong multi-user and permission model

---

​

Networking model

• Krkn is capable of using QUIC and HTTP/2:
  • Faster startup
  • Better multiplexing
  • Better performance on high-latency or restricted networks
• Hashtopolis uses traditional HTTP(S) over TCP

---

​

In short

Krkn is optimized for modern, distributed, containerized environments and long-term cracking intelligence accumulation.
Hashtopolis is optimized for classic server + agents + shared storage environments.

---

​

Part 2 — Technical Deep Dive

​

1. Architecture & Technology Stack

​

Krkn

• Go-based microservices
• gRPC + Protocol Buffers
• QUIC/HTTP2 transport
• SQLite using sqlc for type-safe queries (user & job database)
• Custom encrypted key-value database for hash intelligence storage
  • System-specific key
  • Daily key rotation
• Strongly typed, compile-time validated APIs

​

Hashtopolis

• PHP monolith
• MySQL
• REST/HTTP with JSON
• Python agents

​

2. Work Distribution Model

​

Krkn

• Custom system: Orchestra
• Pull-based model:
  • Workers (“Instruments”) register with the Conductor
  • Workers open streaming gRPC connections
  • Workers request work when ready
• Natural load balancing

​

Hashtopolis

• Push/poll model
• Server assigns tasks
• Agents poll HTTP endpoints for work

​

3. Communication Protocol

​

Krkn

• gRPC + Protocol Buffers
• QUIC/HTTP2 transport
• Streaming RPCs
• Supports large, chunked payloads:
  • Wordlists
  • Rules
  • Hashlists

​

Hashtopolis

• REST API over HTTP(S)
• JSON messages
• Files transferred via separate download endpoints
• Agents reference files by ID/path

​

4. Job Distribution Philosophy

​

Krkn

• Batching system
• Jobs are grouped into batches
• Each batch contains:
  • Hashes
  • Wordlists
  • Rules
  • Masks
• Entire attack payload is self-contained

​

Hashtopolis

• Task-based model
• Jobs reference centrally stored files
• Agents must fetch required files separately

​

5. Worker Architecture

​

Krkn

• Go-based workers called Tentacles
• Execute hashcat directly using shared object files
• Embedded file handling

​

Hashtopolis

• Python-based agents
• More flexible for ad-hoc customization

​

6. Data Embedding Strategy

​

Krkn

• File contents embedded directly into job payloads:
  • Hashes
  • Wordlists
  • Rules
  • Masks
• Delivered as byte arrays over gRPC streams

​

Hashtopolis

• Files stored centrally
• Agents download files separately

​

7. Network Transport

​

Krkn

• QUIC (UDP-based)/HTTP2
• Multiplexed streams
• Better performance on:
  • High latency
  • NAT
  • VPN
  • Firewalled environments

​

Hashtopolis

• TCP-based HTTP(S)

​

8. Database Design

​

Krkn

• SQLite for:
  • Users
  • Jobs
  • Scheduling
  • ACLs
• Custom encrypted key-value store for:
  • Hashes
  • Cracked passwords
  • Historical result indexing
• SQLC-generated type-safe queries

​

Hashtopolis

• MySQL
• Traditional ORM / query approach

​

9. Scalability Model

​

Krkn

• Streaming chunked transfer
• Pull-based scheduling
• Workers request work when idle
• Natural horizontal scaling

​

Hashtopolis

• Central file repository
• Separate download phase
• More I/O coordination required

​

10. Observability & Automation

​

Krkn

• Structured logging via Zap
• Orchestra heartbeat and metrics system
• Webhook-based event streaming
• Automation-first integration design

​

Hashtopolis

• Traditional PHP logging and status views

​

Key Advantages of Krkn

• Type safety (Protocol Buffers, SQLC)
• Higher performance (QUIC + gRPC)
• Self-contained jobs (no shared filesystem)
• Modern concurrency (Go goroutines)
• Pull-based load balancing
• Cloud/container friendly
• Better for segmented and restricted networks
• Persistent encrypted cracking intelligence
• Automatic re-use of historical results
• Webhook-driven automation and integration
• Fine-grained ACL system

---

​

Key Advantages of Hashtopolis

• Mature, battle-tested ecosystem
• Full web UI
• Centralized file storage reduces payload size
• Python agents easier to customize
• Strong multi-user and permission model

---

​

Final Positioning

Krkn is not just a distributed cracking scheduler.
It is a cracking intelligence platform that accumulates knowledge over time, integrates into automated security workflows, and is built for modern infrastructure.

Hashtopolis is an excellent task execution and management system for traditional environments.

They solve related but fundamentally different problems.