How to install Kuiper on Windows or macOS?

Kuiper is optimized for Ubuntu 18.04 LTS with Docker, so installation on Windows or macOS may require using virtual machines or container workarounds, with no official support documented. Check community forums for potential guides.

Kuiper vs Autopsy for digital forensics?

Kuiper is better for team-based, server-side forensics with rule automation and collaboration, while Autopsy is a standalone desktop tool suited for individual analysts. Kuiper scales better for large cases but has a steeper setup curve.

How to add a custom parser to Kuiper?

Follow the wiki guide to write a Python parser script and integrate it into the parsers directory. This allows Kuiper to handle new file types, extending its analysis capabilities without modifying the core platform.

Can Kuiper handle live system forensics or network logs?

Kuiper focuses on parsing collected artifacts from tools like Hoarder or KAPE, not live forensics. For network logs, you might need custom parsers or pre-processing, as it's designed for post-collection analysis.

What are the scaling options for Kuiper in large investigations?

Scaling involves increasing CPU cores for parsing concurrency and using multiple Elasticsearch nodes for better performance, as suggested in the README. However, it requires manual cluster setup and resource management.

Is Kuiper suitable for law enforcement or enterprise use?

Yes, its collaborative features and rule automation make it good for teams in law enforcement or enterprises, but the open-source, self-hosted nature means you need in-house infrastructure and security compliance checks.

Kuiper — Digital Forensics Platform

What is Kuiper?

Kuiper is a digital forensics investigation platform that parses, searches, and visualizes collected evidence to aid in forensic analysis. It centralizes evidence processing on a server, enabling team collaboration through tagging and timeline features, and allows for rule-based automation to detect malicious activities. The platform is designed to handle large amounts of data and streamline investigation workflows.

Target Audience

Digital forensics analysts, incident response teams, and cybersecurity professionals who need to process, analyze, and collaborate on forensic evidence from multiple machines or cases.

Value Proposition

Developers choose Kuiper for its centralized, collaborative approach to digital forensics, which reduces hardware requirements for individual analysts and improves consistency through trusted parsers. Its ability to automate detection with custom rules and support custom parsers makes it a flexible and scalable solution for investigation teams.

Digital Forensics Investigation Platform

Use Cases

Best For

Centralizing forensic evidence processing and analysis for team-based investigations
Automating detection of malicious activities with custom rules across multiple cases
Collaborating on forensic timelines and tagging suspicious artifacts with team members
Parsing and analyzing bulk evidence collected from tools like Hoarder or KAPE
Handling large-scale digital forensics cases with numerous machines and artifacts
Extending forensic analysis capabilities by adding custom parsers for unsupported file formats

Not Ideal For

Individual analysts handling small-scale, single-machine forensics where lightweight desktop tools are sufficient
Organizations lacking DevOps expertise to manage and troubleshoot the multi-container Docker deployment
Investigations requiring rapid deployment or ad-hoc analysis without time for complex platform setup and configuration

Pros & Cons

Pros

Centralized Server Processing

Processes evidence on the server-side, reducing the need for powerful individual analyst machines and centralizing data storage, as highlighted in the README's optimization section.

Team Collaboration Features

Provides a web interface for tagging artifacts and viewing timelines, enabling multiple analysts to work on the same case simultaneously, which speeds up investigations.

Rule-Based Alert Automation

Allows creating detection rules that trigger alerts across past, current, and future cases, automating repetitive tasks like spotting suspicious PowerShell commands.

Extensible Parser Support

Supports adding custom parsers for unsupported file types via a documented process, making the platform adaptable to new evidence formats without core changes.

Cons

Complex Docker-Based Deployment

Requires running seven Docker containers with dependencies like Elasticsearch and NFS, and the installation process has known issues needing manual troubleshooting, such as adjusting vm.max_map_count.

Limited API Functionality

The built-in API is described as limited in the README, with only a few features available via a separate repo, which may hinder integration with other tools or automation workflows.

High Resource Requirements

Recommends 64GB RAM and multiple CPU cores for optimal performance, making it resource-intensive for smaller teams or environments, as noted in the hardware requirements.

What is Kuiper?

Target Audience

Digital forensics analysts, incident response teams, and cybersecurity professionals who need to process, analyze, and collaborate on forensic evidence from multiple machines or cases.

Value Proposition

Use Cases

Best For

Centralizing forensic evidence processing and analysis for team-based investigations
Automating detection of malicious activities with custom rules across multiple cases
Collaborating on forensic timelines and tagging suspicious artifacts with team members
Parsing and analyzing bulk evidence collected from tools like Hoarder or KAPE
Handling large-scale digital forensics cases with numerous machines and artifacts
Extending forensic analysis capabilities by adding custom parsers for unsupported file formats

Not Ideal For

Individual analysts handling small-scale, single-machine forensics where lightweight desktop tools are sufficient
Organizations lacking DevOps expertise to manage and troubleshoot the multi-container Docker deployment
Investigations requiring rapid deployment or ad-hoc analysis without time for complex platform setup and configuration

Pros & Cons

Pros

Centralized Server Processing

Processes evidence on the server-side, reducing the need for powerful individual analyst machines and centralizing data storage, as highlighted in the README's optimization section.

Team Collaboration Features

Provides a web interface for tagging artifacts and viewing timelines, enabling multiple analysts to work on the same case simultaneously, which speeds up investigations.

Rule-Based Alert Automation

Allows creating detection rules that trigger alerts across past, current, and future cases, automating repetitive tasks like spotting suspicious PowerShell commands.

Extensible Parser Support

Supports adding custom parsers for unsupported file types via a documented process, making the platform adaptable to new evidence formats without core changes.

Cons

Complex Docker-Based Deployment

Limited API Functionality

The built-in API is described as limited in the README, with only a few features available via a separate repo, which may hinder integration with other tools or automation workflows.

High Resource Requirements

Recommends 64GB RAM and multiple CPU cores for optimal performance, making it resource-intensive for smaller teams or environments, as noted in the hardware requirements.

Kuiper

What is Kuiper?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?

Kuiper

What is Kuiper?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?