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SQUIRRELOPS

Deception & Attribution Platform

Make attackers reveal themselves.

Deploy intelligent decoys across your network, your endpoints, and your customer-facing AI. When threats interact with them, you learn who, what, and where.

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AI Deception · v1.0.5

Turn an LLM jailbreak attempt into a labeled threat signal.

Squirrelops sits in front of your customer-facing language model. When someone tries to jailbreak it, exfiltrate secrets, or prompt-inject your agent, we route them into a high-fidelity decoy and capture exactly what they tried, what tooling they used, and what they were after.

Your real model stays clean. Your security team gets a feed of labeled attacker behavior.

66/67
Attack turns captured
0
False positives on benign traffic
116
Tracked credentials / campaign

Internal adversarial campaign, v1.0.4 (2026-05-12). Methodology: see the AI page.

Products

Three lines, one platform.

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Built in the open.

SquirrelOps is source-available under PolyForm Noncommercial. Explore the core platform, the ClownPeanuts adaptive deception framework, and the PingTing monitoring toolkit on GitHub.

Explore the Community

Pilot engagement

Run an evaluation pilot.

We work with security teams that have a defined LLM attack surface and an internal red-team or pen-test capability. A 4-to-6-week engagement with a signed profile bundle scoped to your model and use cases.

Request a pilot