Security and cryptography
Non-LLM vulnerability scanning, a self-playing cyber range, encrypted-at-rest stores, and licensing backed by proof-of-work.
Unslop
Find and fix known bugs. No model in the loop.
Live Static analysis and vulnerability scanning
Unslop is a modular, encrypted knowledge base of code bugs and vulnerabilities paired with a non-LLM detector. It ingests dozens of open-source vulnerability datasets into one sealed, source-blind store, then scans whole codebases in seconds by matching against it.
What it does
Scans are deterministic: the same code produces the same findings, every run, with zero model calls and no code leaving the machine. Output is SARIF, so it drops into existing CI and code-scanning dashboards.
It also auto-fixes, either by swapping a matched chunk for the known-good code or by applying a registered safe rewrite. Because the match is exact rather than inferred, a fix is a substitution rather than a suggestion.
Who it is for
Engineering teams that need reproducible vulnerability scanning in CI without sending source code to a model provider.
What it costs
Free scanning tier; paid plans for larger codebases and private dataset hosting.
Terminology
Words this page uses in a specific sense.
- Non-LLM detector
- A matcher that finds known-vulnerable code by comparison against a dataset, with no language model in the analysis path. Deterministic and offline.
- Source-blind store
- The vulnerability knowledge base is encrypted and content-addressed, so it can be distributed without shipping the original vulnerable source it was derived from.
- SARIF
- Static Analysis Results Interchange Format — the OASIS standard JSON format that GitHub code scanning and most IDEs consume.
Facts
| Field | Value |
|---|---|
| Name | Unslop |
| Status | Live |
| Category | Static analysis and vulnerability scanning |
| Platforms | Web, Windows, Linux, macOS |
| Pricing | Free scanning tier; paid plans for larger codebases and private dataset hosting. |
| Source | Closed source |
| Publisher | Cognitive Industries |
| Published from | Brisbane, Queensland, Australia |
Capabilities behind it
How it compares
Unslop vs LLM-based code scanners
Both find problems in a codebase. They fail in opposite directions, so the choice is about which failure you can live with.
Sources
Where this page states a standard, an obligation or a research result, this is what it is drawn from. All external, all checkable.
- ONNX Runtime — the inference engine behind the vision stack
- Keystroke dynamics research overview — Computers & Security — the basis for HumanIO timing models
- Fitts, P. M. (1954), The information capacity of the human motor system — the motor-control law behind cursor submovements
Related
Last reviewed · Site changelog