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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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Community Edition is on the roadmap.

The current product repositories are private. We are working toward a self-contained, open-source Community Edition. The roadmap is proposed, and no release date is committed.

Community Edition overview

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