SigmaShake
Runtime guardrails that block dangerous AI agent commands deterministically in about 85ms, with full audit
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sigmashake.comAbout SigmaShake
SigmaShake puts deterministic guardrails around AI coding agents at runtime. Rather than asking the model nicely, it intercepts the tool calls an agent tries to make and evaluates them against rules you control, so a shell command targeting a production path is denied before it executes. The evaluation is native and deterministic — no model inference, no GPU, no token cost — which the company measures at roughly 85 ms per decision, with denials landing in under 2 ms in their demo. Everything the agent does is written to a local audit log, and paid accounts can sync a signed, tamper-evident copy to the cloud for security review. The distinguishing move is that they published the benchmark rather than just claiming the result: SHAKEDOWN is an open agent-containment benchmark scoring containment multiplied by one minus the false-block rate, run over 324 attack tasks across 9 agent harnesses, with a corpus of 3,855 malicious and 1,894 benign tasks. SigmaShake reports 100 on it at 100% of attacks blocked with a 0% false-block rate, against modelled scores of 49.5 for a sandbox runtime, 21.1 for a policy kernel, 19.3 for a skill-based guardrail and 18.1 for a prompt guard. It ships as a desktop app for Windows, macOS and Linux plus a VS Code extension, an MCP server and a rules hub, and supports Claude Code, Cursor, Gemini CLI, VS Code and Codex.
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Key Features
SigmaShake Pros & Cons
✅ Pros
- +$5/month flat is unusually cheap for a security control
- +Publishing the benchmark and corpus makes the containment claim checkable
- +No inference in the decision path means no added latency or token spend
⚠️ Cons
- −No usable free tier — the download is free but the product is not
- −Competitor scores on SHAKEDOWN are modelled from public docs, not run by the vendors
- −Per-user install means no central team deployment below Enterprise
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