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ASL V6 vs Gateplex

ASL V6 and Gateplex are both guardrails & safety 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.

ASL V6

ASL V6

ASL V6 combines AST-based static analysis with Docker-isolated runtime verification to find and confirm exploitable vulnerabilities in AI agent frameworks before they ship. The dual-layer approach means a finding isn't just flagged — it's verified in a sandboxed execution environment, which cuts the false-positive rate that burns security team time. It runs entirely offline with no external API calls, so sensitive proprietary code never leaves your machine. The ceiling appears quickly on non-Python codebases and on teams that need ticketing integrations or cloud-native CI pipelines baked in rather than assembled by hand.

Gateplex

Gateplex

Gateplex is governance middleware: it does not run your agents, it watches them. The vendor describes it as a policy enforcement layer that intercepts agent actions — API calls, approvals, data sends — checks them against defined rules, and blocks or flags violations before execution completes. That distinction matters for regulated environments where post-hoc logging is not enough. The free tier covers three agents and a capped intercept volume per month, which fits a proof-of-concept but runs short the moment a second team deploys. Beyond that ceiling, teams move to a paid tier or hit a wall.

AttributeASL V6Gateplex
PricingFreePaid
Price$199/month
Free trialNoNo
Open sourceYesNo
Has APINoYes
Self-hosted optionYesNo
PlatformsLinux, macOS, Windows (with Docker)Cloud-based middleware; integrates with agent frameworks on any platform running OpenAI, Anthropic, LangChain, CrewAI, AutoGen, Vertex AI, or AWS Bedrock
Pros
  • AST static analysis paired with Docker runtime verification confirms exploitability before surfacing a finding, so your team spends time fixing real vulnerabilities rather than triaging false positives.
  • 100% local execution with no external API calls, which means auditing proprietary or pre-release AI code without the legal and compliance risk of sending source to a third-party service.
  • Remediation patch generation alongside confirmed findings, so developers receive an actionable fix rather than a vulnerability description they have to decode into a code change.
  • MIT license with self-hosted deployment, so security teams can run it inside air-gapped environments or modify detection rules to match their specific AI framework stack without vendor approval.
  • Detection rules derived from confirmed, disclosed CVEs in production AI systems (AutoGPT, FlowiseAI), which means the tool targets attack patterns that have already caused real damage rather than theoretical edge cases.
  • Real-time action interception before execution completes, which means a procurement agent cannot approve an out-of-policy spend and then get flagged about it afterward — the action is stopped in the moment.
  • PII detection at the intercept layer, so customer data does not reach a third-party API before a policy check has cleared it — without this, a misconfigured agent integration becomes a data leak that logging discovers too late.
  • Duplicate transaction detection for financial agents, which prevents a refund or payment from issuing twice due to a retry loop or race condition — the kind of error that is trivial to miss and expensive to reverse.
  • Audit trail output formatted for legal and compliance review rather than raw telemetry, so the evidence package a regulator or procurement committee requests does not require a data engineering sprint to produce.
  • API access to the enforcement layer, which means policy rules can be managed programmatically and integrated into existing deployment pipelines rather than configured only through a UI.
Cons
  • Coverage is scoped entirely to Python — teams auditing AI systems with Node.js tool-calling layers, Go-based infrastructure, or polyglot agent frameworks get no static or dynamic analysis for the non-Python surface, and there is no documented path to extend language support without forking the project.
  • Docker is a hard runtime dependency for the dynamic verification layer; teams in environments where Docker is restricted by policy (common in enterprise security tooling reviews) lose the exploit-confirmation step entirely and fall back to static-only output, which is where false positives return.
  • There is no native integration with vulnerability management platforms, ticketing systems, or SIEM pipelines — teams that need findings routed into Jira, Defect Dojo, or Splunk build that plumbing themselves, and when the integration maintenance cost grows, teams with existing platform investments switch to commercial SAST tools that ship those connectors out of the box.
  • No self-hosted deployment option is documented — every agent action routed through Gateplex passes through vendor infrastructure. Teams with data residency requirements, air-gapped environments, or legal restrictions on externalizing sensitive financial or health data have no workaround: this is a hard architectural incompatibility, not a configuration problem, and those teams evaluate on-premises alternatives instead.
  • The free tier caps at three agents and a fixed intercept volume per month. A team piloting with two agents clears that ceiling the moment a third team onboards or production traffic spikes — at which point the choice is a paid tier commitment or a freeze on agent expansion, and the evaluation timeline compresses.
  • Gateplex enforces policy on agent actions but does not itself define what your agents should do — teams that want policy logic tightly coupled to agent orchestration (branching based on what a prior step returned, approval gates wired into the agent graph) end up maintaining Gateplex as a separate enforcement layer alongside their orchestration framework, which is two systems to debug when something breaks.
Bottom line

ASL V6 is free while Gateplex is paid; ASL V6 is open source; only Gateplex exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between ASL V6 and Gateplex?

ASL V6 is Free and open source, while Gateplex is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is ASL V6 better than Gateplex?

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.

ASL V6 vs Gateplex: which should I pick?

Pick ASL V6 if its pricing model, openness, or platform fit matches your constraints; pick Gateplex otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.