Is Wasabi Safe?
Risk Grade: C (45/100)
Wasabi is rated as elevated risk — multiple novel mechanisms and notable interaction risks.
Elevated risk — novel application of leveraged derivatives to highly volatile long-tail assets, with LP vaults exposed to extreme directional risk.
Wasabi is a leverage trading protocol enabling long and short positions on long-tail crypto assets including memecoins and NFTs, using physically-settled perpetual contracts backed by ETH-ERC20 LP vaults. With $18M TVL, its C+ grade reflects the novel application of leveraged derivatives to highly volatile assets, creating risks that exceed typical perp DEX exposure.
TVL
$15M
Mechanisms
5
Interactions
4
Value Grade
D
Key Risks for Wasabi Users
Wasabi enables leveraged trading on memecoins and NFTs — assets that can lose 90%+ of their value in hours. LP deposits act as counterparty and can lose value when traders profit.
The protocol uses physical settlement, meaning actual tokens must be held. For illiquid memecoins, this can create issues when large positions need to be closed.
An insurance fund exists to cover extreme losses, but memecoin crashes can create losses that exceed the fund's reserves.
Top Risk Factors
- •Asset-backed perps on long-tail assets — Wasabi enables leveraged trading on memecoins and NFTs, assets with extreme volatility and thin liquidity.
- •LP vault as counterparty — ETH-ERC20 LP vaults act as counterparty to all trades. In trending markets for volatile assets, LPs can face significant losses.
- •Insurance fund adequacy — may be insufficient for tail-risk events common in memecoin and NFT markets.
- •Physically-settled perps complexity — requires holding actual assets, creating inventory management risk.
Risk Score Breakdown
Wasabi's highest risk area is Vitality Risk (8/10). Here's how each dimension contributes to the overall 45/100 score:
Read the Full Wasabi Risk Report
This protocol has 2 collapse scenarios. 2 high-severity interaction risks identified. See the full mechanism classification, interaction matrix, and deep-dive recommendations.
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