prodaft/cradle is an open-source web application that gives Cyber Threat Intelligence analysts a shared workspace for collaborative note-taking, relationship mapping, and report generation during authorized investigations.
| Tool | prodaft/cradle — batteries-included collaborative threat intelligence platform for CTI analysts |
| Category | Threat intelligence management and collaboration platform (JavaScript/Django) |
| Primary Use | Team-based threat analysis: shared investigations, entity relationship visualization, and exportable intelligence reports |
| Safe Use | Intended for authorized CTI teams, incident responders, and security researchers analyzing threat data in controlled, sanctioned environments |
| Telemetry Note | Purely defensive analyst tooling; it touches no third-party systems, so its use leaves no trace on external infrastructure — defenders simply benefit from its structured intelligence output |
CRADLE, published at prodaft/cradle, positions itself as "batteries included collaborative threat intelligence," and that tagline is an accurate summary of what the repository delivers. It is an open-source web application aimed squarely at Cyber Threat Intelligence (CTI) analysts who need more than a pile of markdown notes and a whiteboard. The platform streamlines threat analysis workflows through three complementary pillars: collaborative note-taking, visual relationship mapping, and report generation, all wrapped in a modular architecture the developers explicitly designed to be extensible. With 344 stars, an MIT license, an active CI pipeline, and backing from the PRODAFT CATALYST team, it reads as a serious attempt to commoditize the internal tooling that mature CTI shops usually build themselves.
The technical stack is conventional in the best sense, which matters for a tool a team must trust with investigation data. The backend is a Django-based API and data processing layer living in backend/, while the frontend in ui/ is an Electron/React application — an interesting choice that means the same interface can run as a desktop client or in a browser. Persistence is handled by PostgreSQL, and the whole stack is orchestrated through Docker configurations in docker/, with documentation and the project website (cradle.sh) in docs/. This monorepo layout keeps each component independently documented, so a team evaluating CRADLE can audit or extend one layer without reverse-engineering the others.
The feature set, per the README, is organized around four key capabilities. Collaborative investigation provides a shared workspace for team-based threat analysis, which addresses the real pain point of CTI work: analysts duplicating effort because findings live in personal notes. Entity relationship visualization offers a graphical representation of connections between threat actors and artifacts — the graph view that turns scattered indicators into an actionable model of adversary behavior. Report generation produces exportable intelligence reports in multiple formats, closing the loop from raw analysis to deliverable. Finally, the modular architecture is called out explicitly as a design goal for future enhancements, signaling that extension points were planned rather than bolted on.
Getting a first look is deliberately frictionless. The README offers a demo path that spins up the full stack with docker compose -f docker-compose.demo.yml up -d, after which CRADLE is reachable at http://localhost:8000 with demo credentials admin:admin. A production-leaning installation follows the same pattern: clone the repository, run docker compose -f docker/docker-compose.demo.yml up -d, and access the application at http://localhost:3000. Prerequisites are minimal — Docker 20.10+, Docker Compose 2.0+, and Git — and component-specific READMEs in backend/ and ui/ cover advanced setup for teams that want to run pieces outside the containerized path.
Two details in the quickstart deserve an operator's attention. First, the demo credentials admin:admin are clearly for local evaluation only; anyone exposing the demo compose stack beyond localhost is asking for trouble, and the README's localhost-oriented framing should be respected. Second, the demo compose file and the installation instructions reference slightly different paths (docker-compose.demo.yml at the repo root versus docker/docker-compose.demo.yml) and ports (8000 versus 3000), a minor documentation inconsistency worth reconciling before deployment — the kind of small drift that tells you the project is young and iterating.
The visualization capability is arguably CRADLE's core differentiator, and its topic tags — data-visualization, cti, threat-intelligence, incident-response — reinforce that. Relationship graphs in CTI serve as the shared mental model between analysts: which infrastructure connects to which actor, which artifacts cluster into a campaign. By making that graph a first-class, collaboratively editable artifact rather than an export from a separate drawing tool, CRADLE reduces the gap between analysis and documentation. The README does not enumerate supported entity types or data models, so a thorough evaluation would start in the backend/ documentation to see how entities and relationships are actually represented and whether they can be imported from existing formats.
Report generation is the other half of the workflow equation. Raw analytical depth is worthless to stakeholders if it cannot be packaged, and the README promises exportable intelligence reports in multiple formats without specifying which ones. That ambiguity is acceptable at this stage of the project, but it is the first question a prospective adopter should ask: whether the outputs fit existing stakeholder expectations or require post-processing. In an authorized engagement or internal investigation context, report generation also creates the audit trail — a durable record of what the team concluded and when.
The provenance of the project is unusually well documented for an open-source security tool. CRADLE is developed by PRODAFT in collaboration with students from TU Delft, with six named contributors — Tudor Măgirescu, Călin-Marian Diacicov, Daniel Popovici, Matei Grigore, Razvan Dinu, and Yigit Colakoglu — plus contact channels through the CATALYST Threat Intelligence Team (catalyst.prodaft.com). PRODAFT is a known name in threat intelligence, which lends credibility to the tool's fitness for real analyst workflows rather than a toy academic exercise, while the academic collaboration explains the clean documentation structure and conventional engineering choices.
From a defensive perspective, CRADLE is purely a force multiplier — it is not an attack tool and touches no third-party systems. Its telemetry footprint on the outside world is zero; the interesting observability question is internal, namely what logging the Django backend exposes for auditing analyst actions inside the shared workspace. The README does not address audit logging, so teams with compliance requirements should verify that capability in the backend layer before making CRADLE the system of record for sensitive investigations.
Where CRADLE fits in the broader landscape is worth stating plainly: it competes with heavyweight platforms like MISP and OpenCTI while offering a lighter, opinionated path geared toward collaborative investigation and report writing rather than large-scale feed ingestion. Teams already committed to a threat intelligence platform may use CRADLE as an investigation-side workspace, feeding curated conclusions upward. The automation and collaborative topic tags suggest the developers see programmatic integration as part of the roadmap, and the modular architecture claim gives that some weight.
For an authorized security team evaluating CRADLE today, the sensible path is exactly what the README prescribes: run the demo compose stack locally, load a sample investigation, and stress the two features that determine day-to-day value — the relationship graph's usability and the report exporter's output quality. Contributions follow a standard fork-and-branch workflow (git checkout -b feature/..., pull request), and the MIT license imposes no friction on internal deployment or customization. As an educational and operational matter, CRADLE represents a well-documented, defensively oriented open-source entry in the CTI tooling space, and its trajectory will depend on how quickly the promised modularity attracts community extensions.
prodaft/cradle.Educational analysis for authorized security professionals. Use only in controlled, authorized environments.
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