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Autter vs Maced AI

Bottom line

Autter has a free plan plus paid upgrades, while Maced AI is paid. Autter is open source and Maced AI is not. You can run Maced AI on your own machine or server; Autter is hosted by the vendor.

Which one should you try?

Autter

Freemium

Best for GitHub-based development teams

Visit Autter See full review

Maced AI

Paid

Best for Engineering teams seeking continuous automated security validation

Visit Maced AI See full review

Pricing, capabilities and platforms side by side. Prices are as of the "Pricing checked" date in the table.

Autter

Autter

Autter sits in your GitHub PR workflow and does more than read the diff — the vendor describes an agentic review loop that executes code, runs scanners, and follows logic paths across files. It pulls context from a codegraph, linked Jira or Linear issues, MCP servers, and web queries, so reviews reflect your actual architecture rather than generic lint rules. Rules are defined in plain English, and the tool learns from how your team reviews over time. The agentic layer adds depth, but it also adds latency — teams with tight merge windows will feel the difference versus a static analyzer that returns in seconds.

Maced AI

Maced AI

Maced deploys AI agents that crawl, fuzz, and attempt exploitation across your web apps, APIs, source code, and cloud infrastructure — then deliver audit-grade reports with proof-of-exploit payloads and merge-ready fix PRs. Every finding is auto-validated before it surfaces, which means triage queues shrink instead of growing. The continuous monitoring model means your attack surface is tested on every deploy, not just once a quarter. The ceiling shows up when your environment demands the kind of adversarial creativity a seasoned human tester brings to a novel business-logic flaw — agents that follow a structured probe loop will miss what only lateral thinking finds. Teams with that requirement use Maced for baseline and point a human at what the agents flag as high-severity.

AttributeAutterMaced AI
PricingFreemiumPaid
Price$39/mo$249/mo
Pricing checkedJul 1, 2026Jun 11, 2026
Free trialNot statedNot stated
Open sourceYesNo
Has APIYesYes
Self-hosted optionNoYes
PlatformsGitHub, Jira, Linear, Slack, GitLab, VS CodeWeb-based SaaS; on-premises and air-gapped deployment available
Pros
  • Agentic review loop that executes code and traces logic paths across files, so edge cases that pass a human read — the kind that surface two weeks after merge — get flagged before they do.
  • Plain-English rule definition with no regex or YAML, which means your coding standards actually get enforced consistently instead of living in a wiki nobody reads before opening a PR.
  • Codegraph-based dependency analysis pulls in impact across the full codebase, so a change that looks isolated in the diff but breaks a downstream service gets caught at review time, not at deployment.
  • External context from Jira, Linear, and web queries is woven into the review, which means the feedback reflects the ticket's intent and current library behavior rather than what the code looks like in isolation.
  • Learns from how your team reviews over time, so institutional knowledge — the patterns your seniors catch by instinct — gets encoded and applied consistently across every PR, not just the ones they personally review.
  • Auto-validation with proof-of-exploit payloads for every finding, so your team stops spending sprint time manually reproducing scanner noise before deciding whether to act.
  • Merge-ready fix PRs generated and retested automatically, which means remediation moves from 'ticket in backlog' to 'reviewed and merged' without a separate engineering investigation cycle.
  • Continuous scanning triggered on every deploy rather than quarterly, so a misconfiguration introduced in Tuesday's PR is caught before it reaches production — not six weeks later in an audit.
  • SOC 2 and ISO 27001 audit-ready report output, so compliance documentation is a byproduct of your normal security workflow rather than a separate manual engagement you schedule and budget for.
  • Self-hosted deployment option, so teams operating in air-gapped or strict data-residency environments can run the platform without routing source code or infrastructure details through a third-party cloud.
Cons
  • The agentic loop runs code, calls tools, and reasons across multiple context sources — that takes time. Teams running more than a handful of PRs per hour will find review feedback arriving after engineers have already context-switched, which defeats the purpose of pre-merge review.
  • GitHub is the only supported platform based on the vendor page. Teams on GitLab or Bitbucket cannot use this tool, and migrating version control to fit a code review tool is not a trade most engineering leads make — those teams go to a competitor with broader VCS support.
  • No self-hosting option exists per available documentation. Organizations with data-residency policies or air-gapped environments are blocked from using the tool regardless of how well the feature set fits.
  • Agents follow a structured crawl-fuzz-exploit loop, which means multi-step business-logic attacks that require contextual judgment — an attacker who knows your domain and chains three unrelated weak points — fall outside what the platform reliably discovers. Teams whose threat model centers on that class of vulnerability still require a human penetration tester; Maced becomes a first-pass filter, not a full engagement replacement.
  • The platform is paid-only with no free tier beyond an initial scan, so teams evaluating at scale against a large or complex environment cannot fully assess fit before committing to a subscription — at which point switching cost is real if the agents' coverage does not match the environment's actual attack surface.
  • White-box testing requires handing over source code access, and for teams at organizations where that creates legal, contractual, or procurement friction, onboarding stalls at the approval stage rather than the technical one — a problem self-hosting solves only if your ops team has bandwidth to stand up and maintain the infrastructure.

Made up your mind?

Autter

Freemium

Best for GitHub-based development teams

Visit Autter See full review

Maced AI

Paid

Best for Engineering teams seeking continuous automated security validation

Visit Maced AI See full review

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Specs come from each tool's own site and docs (how we test). AIDiveForge is editorially independent.

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