Axtary vs SigmaShake

Axtary and SigmaShake 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.

Axtary

Axtary sits beside the agent and evaluates each tool call against deterministic policy before the underlying provider is called. Routine actions — ones that clear the policy rules — pass automatically. Higher-risk actions pause for a human to review the normalized payload, and the approval is cryptographically tied to that specific hash. If anything changes after sign-off, the adapter catches the mismatch and blocks execution. Every attempt, pass, and rejection lands in a verifiable ledger. The self-hosted path keeps provider credentials local, which matters for teams that cannot route credentials through a third-party service.

SigmaShake

SigmaShake intercepts tool calls from agents running in Claude Code, Cursor, VS Code Copilot, and Gemini CLI, evaluating each action against a rule set before it executes. The vendor states decisions resolve in roughly 85 ms using deterministic native evaluation — no model inference, no GPU, no token spend. Rules follow an Allow/Ask/Deny pattern, where Ask routes the action to a human approval queue rather than blunting everything with a hard block. The desktop app installs in about 30 seconds with no admin rights; the CLI drops into any shell or CI hook chain. Self-hosting is supported, which means the guardrail layer stays offline and never sends your code or commands to a third-party model.

Attribute	Axtary	SigmaShake
Pricing	Paid	Paid
Price	—	$5/mo
Free trial	30 days	No
Open source	No	No
Has API	No	No
Self-hosted option	Yes	Yes
Platforms	—	Windows 10+, macOS 14+, Linux (Ubuntu 22.04+ / Fedora 38+ / Pop!_OS)
Pros	Payload hash binding ties every human approval to the exact diff or message reviewed, so a payload altered after sign-off is rejected at the adapter before the provider is called — eliminating the attack surface where approval covers a summary rather than the literal content. Deterministic policy evaluation on routine actions means low-risk tool calls clear automatically, so human reviewers only see the calls that actually warrant attention rather than approving every agent action manually. Self-hosted policy enforcement keeps provider credentials local, so teams under data-residency or credential-exposure constraints can run authorization checks without routing sensitive tokens through a third-party service. A verifiable ledger records every decision, pass, execution result, and trace reference, so teams facing a post-incident audit have a timestamped, tamper-evident record of what the agent was authorized to do and what actually ran. ActionPass artifacts carry normalized action records — actor, intent, resource, constraints, and policy version — structured for consumption across SDKs and MCP wrappers, so teams can integrate authorization evidence into existing tooling without custom log parsing.	Deterministic local evaluation at roughly 85 ms per check, so you avoid the latency and per-token cost of routing every agent action through a model-based policy guard. Ask mode holds a risky action in a human approval queue rather than blocking it outright, which means your agent keeps moving on safe tasks while you review the one call that needs a second look. PreToolUse hook integration for Claude Code and MCP server integration for Cursor, Codex, and VS Code Copilot, so the guardrail wires into agents your team is already running without a custom shim. Self-hosted deployment with no model inference, so your code, file paths, and shell commands never leave the machine — critical for teams with data-handling obligations. Per-user install with no admin or UAC rights required, which means individual developers can adopt it without waiting for IT to sign off on an organization-wide rollout.
Cons	The hash-binding guarantee only holds for connectors that implement the adapter-side verification step. Teams whose agents call tools outside the documented connector set — anything not in the GitHub, Slack, Linear, AWS/GCP, MCP, or document-search list — must write and maintain their own adapter verification before Axtary's core security property applies to those calls. Axtary enforces policy on proposed actions; it does not generate, plan, or sequence agent tasks. Teams that need an authorization layer bundled with agent orchestration — where the same system routes tasks and enforces rules — will hit this ceiling immediately and look at platforms that combine both concerns. The product is in access-request stage with a small documented connector surface, which means teams with production timelines that cannot absorb an integration build or a waitlist delay will default to a more established policy enforcement tool rather than waiting for connector coverage to expand.	No API is exposed, so teams building custom agent runtimes or embedding safety checks inside their own orchestration code cannot call SigmaShake programmatically — they wrap the CLI binary, which introduces a process boundary and complicates error handling at scale. The SHAKEDOWN benchmark that positions SigmaShake as the top-ranked guardrail was authored by SigmaShake, and competitor scores were modeled from public docs rather than measured runs; teams doing their own evaluation should run independent tests before treating the benchmark as a neutral comparison. Fleet management and team-level policy enforcement are paid-only features, which means a free-tier team cannot centrally audit what rules individual developers are running — a gap that matters the moment more than one engineer is using an AI coding agent on shared infrastructure. Windows support is the primary release target based on page emphasis and download prominence; macOS and Linux builds are listed but community reports on edge cases outside Windows are sparse, so teams running heterogeneous developer environments should validate on non-Windows machines before committing.

Bottom line

Axtary and SigmaShake are closely matched on pricing model, openness, and API availability — pick by feature set and platform support in the table above.

Frequently asked questions

What is the difference between Axtary and SigmaShake?

Axtary is Paid, while SigmaShake is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Axtary better than SigmaShake?

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.