SigmaShake vs Strix

SigmaShake and Strix 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.

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.

Strix

Strix runs multi-agent Think-Plan-Act loops that scan infrastructure, attempt exploitation, and return findings backed by working PoCs — so your team reviews confirmed vulnerabilities rather than triaging noise. The vendor page describes CI/CD integration and PR-level fix suggestions, which means security gates can live inside the same pipeline where code ships. Self-hosted and air-gapped deployment options are confirmed, making it viable for teams with data residency requirements. The agentic model works well when scope is defined and targets are enumerable — cloud misconfigs, known CVE classes, API surface. Where it strains is against novel logic flaws and business-layer vulnerabilities that require context no automated agent carries.

Attribute	SigmaShake	Strix
Pricing	Paid	Paid
Price	$5/mo	—
Free trial	No	No
Open source	No	Yes
Has API	No	No
Self-hosted option	Yes	Yes
Platforms	Windows 10+, macOS 14+, Linux (Ubuntu 22.04+ / Fedora 38+ / Pop!_OS)	CLI (Docker, bash install), self-hosted, web platform
Pros	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.	Autonomous agents return findings with working proof-of-concept exploits attached, so your team skips the manual reproduction step that typically consumes days between scan and fix. Multi-agent Think-Plan-Act architecture executes attack sequences without human steering at each step, which means a single security engineer can run coverage across an infrastructure that would otherwise require a full red team. CI/CD pipeline integration with PR-level fix suggestions keeps security findings inside the developer workflow, so vulnerabilities surface at the same moment code changes ship rather than weeks later in a quarterly report. Self-hosted and air-gapped deployment is confirmed by the vendor, which means teams with data residency requirements or classified environments can run the full agent stack without sending target data to an external service. Open-source codebase allows security teams to audit exactly what the agents execute, which means you are not trusting a black-box scanner on infrastructure you cannot afford to have probed incorrectly.
Cons	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.	Agents operating within Think-Plan-Act loops depend on the target being within the enumerable attack surface the model understands — business logic vulnerabilities and multi-step application flows that require domain context produce no findings, and teams with that testing requirement add a manual penetration tester alongside the tool rather than replacing the workflow. Automated exploitation against production targets carries risk that misconfigured scope definitions translate directly into unintended impact; teams running Strix against live environments report needing explicit scope guardrails and staging-first policies before touching production, adding operational overhead the tool does not eliminate. When the primary gap is compliance-driven manual testing with a signed attestation from a human pentester, Strix's autonomous output does not satisfy the requirement regardless of finding quality — teams in those regulatory contexts switch to a managed DAST or manual pentest vendor for the compliance artifact and run Strix separately for continuous coverage.

Bottom line

Strix is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between SigmaShake and Strix?

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

Is SigmaShake better than Strix?

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.