Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for developers and security teams who want a practical open-source scanner for AI-generated code, plus a clearer verification loop than a one-pass lint or static rule bundle.
Who should use it
Who should skip it
Skip openhackai/OpenHack if the source link, documentation, or setup requirements do not align with your current workflow or stack.
About this signal
openhackai/OpenHack is tracked by RepoRadar as a tool in the Security Tools section. It was first seen on 2026-06-26 and last updated on 2026-06-26. The current verdict is 'try now' with a Gold tier and moderate setup difficulty. The standout signals for openhackai/OpenHack are workflow potential (9.1) and open-source/build quality (8.4), while setup ease (6.4) trails — that balance shapes where it fits best. This page summarizes the evidence RepoRadar has captured from captured source metadata. The score, tier, risk label, and verdict on this page are never influenced by sponsorship, ads, or tips — they reflect only the usefulness, popularity, novelty, momentum, maturity, and evidence signals described in the RepoRadar methodology.
How this item is evaluated
RepoRadar assigned openhackai/OpenHack a composite score of 8.0 out of 10, placing it in the Gold tier. This score combines weighted sub-signals: usefulness (35%), novelty (18%), momentum (14%), maturity (10%), open-source/build quality (7%), evidence quality (6%), workflow potential (6%), and setup ease (4%). Popularity is tracked separately at 91.0 and never affects the composite score or tier. The risk label of 'conditional' reflects inherent user-impacting hazards, not generic novelty. Items with no risk flag may still require normal code review before production use.
Putting this into practice? Read How to evaluate an AI tool before you adopt it for the checklist behind this score.
Risk explanation
Default setup uses an OpenHack account token for hosted inference, so confirm what project context leaves the machine before scanning sensitive codebases; Sandbox and browser verification depend on a working Docker environment, which adds extra operational surface beyond a pure code scanner; Treat findings as triage input rather than auto-merge truth because exploit validation and severity still need human review.