What Is ScanDrix And How Does It Work?

ScanDrix is an autonomous AI-powered code review and AST security scanning platform built for modern engineering teams. It integrates into your Git providers (GitHub, GitLab, Bitbucket, Azure Repos) to automatically review pull requests, detect vulnerabilities, suggest code fixes, and enforce custom Drixy rules.

How Does ScanDrix Differ From Traditional Linters Like SonarQube?

Traditional linters analyze files in isolation using rigid regex or pattern rules, resulting in high false-positive rates and zero understanding of code intent. ScanDrix performs deep Abstract Syntax Tree (AST) analysis combined with multi-model AI reasoning, understanding whole-codebase context, taint flows, and architectural boundaries.

What Are Drixy Rules And How Do I Configure Them?

Drixy rules are customizable code review and security policies. You can define rules globally across your organization, per repository, or choose from a library of community best practices. You can also run 'Dry Run' previews to test rule modifications against real historical PRs before enforcing them.

Which Git Providers And CI/CD Tools Does ScanDrix Support?

ScanDrix supports GitHub, GitLab, Bitbucket, Azure Repos, and Forgejo out of the box. It also provides a CLI and team API keys for local developer workflows, pre-commit hooks, and custom CI/CD runners.

Does ScanDrix Train On Our Private Source Code?

No. ScanDrix never uses customer source code to train AI models. All code diffs are processed in ephemeral, isolated environments with strict zero-data-retention guarantees. For enterprise deployments, ScanDrix supports Bring Your Own Key (BYOK) and self-hosted on-premise installations.

How Fast Are ScanDrix Code Reviews On New Pull Requests?

ScanDrix is built for sub-minute reviews: an async worker architecture picks up webhook events without blocking CI pipelines. That is a design goal, not a measured guarantee — live service state is on the status page.

Can ScanDrix Suggest Inline Code Fixes?

Yes. When ScanDrix detects bugs, security vulnerabilities, or rule violations, it generates precise inline diff suggestions directly in the pull request review comments that developers can apply with a single click.

Can We Deploy ScanDrix On-Premise Or In Our Own VPC?

Yes. Enterprise customers can deploy ScanDrix in their own AWS, GCP, or Azure VPC, or in fully air-gapped on-premise environments with support for internal LLM endpoints (vLLM, Ollama) and enterprise SSO.

Security-First Review Pipeline

Configure Drixy rules for OWASP risks, secret detection, and secure coding patterns as merge gates.

A ready-to-adopt rule set that makes critical security findings block merges while keeping lower severities advisory.

1. Enable the security baseline

From Rules → Library, activate:

Rule ID	Severity	Blocks
`sec-001` enforce-parameterized-sql	critical	✓
`sec-002` no-hardcoded-secrets	critical	✓
`arch-001` tenant-isolation-guard	critical	✓
injection/eval patterns	critical	✓
missing outbound timeouts	warning	✗

yaml

version: 1
project: "payments-service"
rules:
  - rule: "enforce-parameterized-sql"
    severity: "critical"
  - rule: "no-hardcoded-secrets"
    severity: "critical"
  - rule: "tenant-isolation-guard"
    severity: "critical"
  - rule: "outbound-timeout"
    severity: "warning"
ignore_paths:
  - "**/*_test.go"
  - "testdata/**"

2. Set merge policies

Settings → Merge Policies: block on critical, comment on warning, advisory for info. This gives security a hard gate without parking refactors.

3. Dry Run before enforcing

Run scandrix rules dry-run --since 30d and review the would-be findings. Expect an initial spike on legacy code — narrow matches or triage with suppressions (/scandrix ignore <rule> --reason "<ticket>") rather than turning the rule off.

4. Evidence for auditors

Audit log — every suppression carries author, reason, timestamp.
Export — audit CSV for SOC 2 / ISO review periods.
CI proof — required status check shows the policy set version active on each merge.

5. Keep it alive

Quarterly, review the rule feedback report: rules with high rejected-suggestion rates get tuned; rules with zero hits over 90 days get questioned. The pipeline only stays trusted while the signal stays clean.

PreviousScanDrix for Monorepos NextOnboarding a New Team