Codebase-aware PR review
Hacktron reviews pull requests with full codebase context rather than only reading the diff. The site says it indexes repositories and call graphs so findings reflect how code actually behaves.
Hacktron AI is an AI code review and application security tool that finds exploitable vulnerabilities in pull requests and code changes.
Hacktron is an AI code review and application security product that looks for exploitable vulnerabilities in pull requests and related code changes. The site positions it as a teammate for security rather than a general-purpose reviewer, with the stated goal of helping teams fix what actually matters before code ships.
Its PR review workflow is built around repository context, inline findings, and feedback loops. Hacktron says it indexes repositories and call graphs, posts comments in GitHub and GitLab, and learns from triage notes and project-specific rules so the output better matches each codebase’s threat model.
Hacktron reviews pull requests with full codebase context rather than only reading the diff. The site says it indexes repositories and call graphs so findings reflect how code actually behaves.
The product focuses on exploitable vulnerabilities instead of general code quality commentary. It is presented as a security reviewer that surfaces issues such as broken access control, injection, SSRF, XSS, and supply-chain risk.
Hacktron posts inline findings in GitHub and GitLab, with comments attached to the vulnerable lines. That keeps the review tied to the code that introduced the risk.
The product learns from triage comments and project rules. Teams can use `.hacktron/rules.md` to describe trusted sources, auth patterns, ignored paths, and other app-specific conventions.
When a fix lands in a later commit, Hacktron can recognize the remediation and close the stale finding automatically. This reduces backlog cleanup after the issue is already resolved.
The site also presents a dependency scanning flow under “Scan dependencies,” suggesting a package review mode for dependency-related risk.
Teams that want security review on every PR can connect a repository and have Hacktron post findings directly in the pull request, keeping review work close to the code change.
Security teams that spend time filtering low-value alerts can use Hacktron’s exploitability-focused output to prioritize issues that appear likely to matter in practice.
Engineering teams with custom authentication, routing, or access-control patterns can document those conventions in `.hacktron/rules.md` so the reviewer reflects project-specific context.
Teams that want less manual backlog cleanup can rely on remediation detection, which closes findings after a fix commit is merged.
Organizations reviewing dependencies as well as application code can use the package-scanning flow referenced on the site to inspect dependency risk alongside code review.
Hacktron is positioned as an AI code review and security review product. Its PR Review workflow says it installs as a GitHub App, reviews pull requests with codebase context, and posts findings inline in GitHub and GitLab.
The source material supports use on web, mobile, backend, API, CLI, and native codebases. The PR Review page specifically emphasizes pull-request security review, while the package page indicates a dependency scanning flow.
Hacktron posts findings with enough context to reproduce and fix the issue, can deliver AI fix prompts in PR comments, and recognizes remediation commits so fixed issues can be closed automatically.
The public pages do not list a full integration catalog, but they do mention GitHub, GitLab, Bitbucket, Slack, Linear, and custom integrations for enterprise plans.
The pricing page shows a 14-day free trial with no credit card required, a Pro plan, and an Enterprise plan with custom pricing.