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ASL V6 vs Declaw

ASL V6 and Declaw 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.

Declaw

Declaw

Each agent execution runs inside a hardware-isolated microVM with a warm-pool restore measured in milliseconds. Outbound traffic passes through a per-sandbox proxy the agent cannot bypass, enforced at both L3/L4 and L7 — so if your allowlist says api.openai.com only, evil.com gets blocked and logged automatically. The credential vault injects secrets at the proxy layer, meaning API keys never enter the VM itself. Where Declaw shows its limits: there is no self-hosted option, so teams in air-gapped environments or with data-residency requirements that preclude third-party cloud infrastructure hit a hard wall. Those teams look at building their own Firecracker wrapper.

AttributeASL V6Declaw
PricingFreePaid
Free trialNoNo
Open sourceYesNo
Has APINoYes
Self-hosted optionYesNo
PlatformsLinux, macOS, Windows (with Docker)
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.
  • All security primitives — network policy, PII redaction, credential vault, and audit log — share the same execution context inside one SDK, so there are no integration gaps between vendors where an injection or exfiltration can slip through unlogged.
  • Credentials are injected at the egress proxy rather than passed into the VM, which means a compromised agent process cannot read the raw API key even if it tries.
  • L7 domain and SNI filtering with wildcard and regex matching lets you define exactly which external endpoints an agent is allowed to reach, so a prompt injection that tries to POST to an attacker-controlled domain is blocked and audited rather than silently succeeding.
  • Snapshot and pause/resume support lets you freeze idle agents and stop paying for compute mid-task, which matters for long-running workflows where billing otherwise accumulates during wait states.
  • Drop-in compatibility with OpenAI, Anthropic, LangChain, and CrewAI means existing agent code runs inside the sandbox without a rewrite, so the migration cost is measured in configuration rather than refactoring.
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.
  • There is no self-hosted deployment option — every agent execution and its outbound traffic passes through Declaw's cloud infrastructure. Teams with data-residency requirements or compliance mandates that prohibit third-party traffic inspection hit this wall immediately; those teams typically end up building a custom Firecracker wrapper with open-source guardrails libraries rather than adopting Declaw.
  • The audit log and guardrail features are only as useful as the policies you define upfront — the docs describe allowlist-based network control, meaning any allowed domain your agent abuses (for example, an attacker using a permitted API as an exfiltration relay) passes through without detection. Teams handling adversarial inputs at scale need to layer additional behavioral monitoring on top, adding back some of the complexity Declaw was meant to eliminate.
Bottom line

ASL V6 is free while Declaw is paid; ASL V6 is open source; only Declaw 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 Declaw?

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

Is ASL V6 better than Declaw?

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 Declaw: which should I pick?

Pick ASL V6 if its pricing model, openness, or platform fit matches your constraints; pick Declaw 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.