Maced AI vs Superagent by i10X

Maced AI and Superagent by i10X are both coding assistants tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

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.

Superagent by i10X

Superagent hooks into GitHub CI/CD and runs on every PR, nightly build, or release without requiring new tooling. The agents triage incoming findings automatically, surfacing real exploit paths and discarding noise — so security teams stop drowning in slop reports. Every fix arrives as a pull request, keeping your team in the loop before anything merges. The free tier covers public repositories; private repos and agent security sit behind a paid-only custom arrangement. Teams without GitHub-centric workflows, or those needing integrations beyond GitHub, will hit a hard wall fast.

Attribute	Maced AI	Superagent by i10X
Pricing	Paid	Paid
Price	$249/mo	—
Free trial	No	No
Open source	No	No
Has API	Yes	No
Self-hosted option	Yes	No
Platforms	Web-based SaaS; on-premises and air-gapped deployment available	GitHub, CI/CD
Pros	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.	Agent-driven exploit-path chaining instead of flat finding lists, which means your security team reviews real attack scenarios rather than spending days manually deciding which CVEs matter. Every fix ships as a GitHub pull request your team approves before it merges, so automated remediation never bypasses your review process or introduces unreviewed changes. Automated triage that filters noise from real exploit paths, so engineers stop context-switching out of feature work to manually sort scanner output. Zero-tooling CI/CD integration via GitHub app — runs on PRs, nightly, or at release without standing up new infrastructure, so adoption doesn't require a platform team sprint. Full vulnerability finding, patching, contributor trust scoring, supply-chain protection, and report deduplication available at no cost for public repositories, so open-source maintainers get a production-grade security loop without a budget line.
Cons	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.	Private repository coverage is a paid-only feature with no self-serve tier — teams with private repos must negotiate a custom contract before they can run a single scan, which blocks evaluation for any org that cannot get commercial approval before proving value. The entire integration surface is GitHub. Teams running pipelines on GitLab, Bitbucket, or internal VCS will find no supported path forward — and this is the condition under which those teams switch to a scanner with provider-agnostic CI hooks instead. No API is available, which means security findings cannot be pulled into internal dashboards, ticketing systems, or SIEM tooling without building a workaround on top of GitHub webhook events — at which point teams are maintaining glue code the tool was supposed to eliminate. Agent coverage explicitly includes AI agents alongside code, but the vendor page does not describe how agent scanning works in technical detail, so teams with complex agent architectures cannot assess fit without a direct sales conversation.

Bottom line

Only Maced AI exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Maced AI and Superagent by i10X?

Maced AI is Paid, while Superagent by i10X is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Maced AI better than Superagent by i10X?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.