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Free · Open source
AI security researchers
AI coding agents delete files, call expensive APIs, and exfiltrate data — not because they're malicious, but because nothing stopped them. SigmaShake sits between the agent and the action, enforcing rules before the damage lands.
$5/mo · Free to download only; an active subscription is required to use any value surface; there is no free tier of the product · Checked Jul 1, 2026
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.
Bottom line: Pick SigmaShake when you need deterministic, offline guardrails wired into Claude Code or Cursor and you cannot afford the latency or cost of a model-based policy check — but plan around the fact that no API means you cannot embed these checks programmatically into a custom agent runtime without reaching for the CLI or MCP server layer.
For teams that must prove what their AI agents are allowed to do
When procurement asks
View full pricing on sigmashake.com →
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SigmaShake places a rule-enforcement layer between an AI coding agent and the actions it wants to take — file writes, shell commands, API calls, outbound requests. When an agent attempts a tool call, SigmaShake evaluates it against a compiled rule set and returns Allow, Deny, or Ask. Ask is the key differentiator: instead of a blunt block, the action is held in a visual approval queue where a developer or team lead reviews it before execution continues. The vendor describes integration via Claude Code’s PreToolUse hook and an MCP server for Cursor, Codex, VS Code Copilot, and Gemini CLI.
The evaluation engine is deterministic and runs locally — no LLM forward pass, no network round-trip. The vendor states the engine resolves in approximately 85 ms and publishes a benchmark called SHAKEDOWN, which replayed 324 attack tasks across 9 agent harnesses. SigmaShake’s own submission scored 100 on that corpus; competitor rows were modeled from public docs rather than direct measurement, which is a methodological detail worth noting when weighing the comparison.
The tool fits teams who have already adopted an AI coding agent and now need an audit trail, a cost-containment layer, or a way to enforce policy without rewriting their agent’s prompt. It does not fit teams building custom agent runtimes who need a programmable SDK — there is no API surface for embedding checks inside your own orchestration code. Teams in that situation end up wrapping the CLI, which works but adds a process-boundary to every call.
Installation splits into a desktop app (Windows, macOS, Linux) and a CLI binary. The desktop app exposes a visual approval queue, system tray status, and a live dashboard. Both paths run the same underlying binary, so rules and audit logs are consistent regardless of which surface a team member uses. Fleet management for teams is a paid-only feature.
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