UniLend Redeem Underlying Missing Health Factor Check Exploit

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UniLend Logo/Homepage

UniLend is a decentralized finance (DeFi) platform enabling permissionless lending and borrowing for any ERC20 token, along with features like isolated dual-asset pools, on-chain governance, and the Lamaa AI platform for building blockchain-integrated AI agents. However, a recent exploit occurred due to a flaw in the health factor check within the "redeemUnderlying" function, where the health factor was checked before collateral transfer, allowing hackers to manipulate balances and withdraw assets without adequate collateral. This led to a $198k loss after a hacker exploited the miscalculation by depositing USDC, borrowing stETH, and withdrawing the funds. The vulnerability stemmed from inflated token balances due to unremoved LP positions and improper health factor calculations. Although UniLend acknowledged the attack and offered a 20% bounty, the outcome and whether affected assets were made whole remain unclear.

About UniLend Finance

UniLend is a decentralized finance (DeFi) platform aiming to democratize blockchain, AI, and DeFi by offering permissionless lending and borrowing functionalities for any ERC20 token. It features isolated dual-asset pools, flexible lending options, and on-chain governance for token holders to manage key parameters. UniLend also introduces Lamaa AI, a platform that enables users to build and launch modular AI agents with blockchain capabilities. Additionally, Numa Network offers a solution to simplify transaction execution and cross-chain intents, addressing issues like gas fees and scheduling. UniLend focuses on empowering its community through governance, allowing users to propose and vote on protocol changes.

The Reality

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What Happened

The Unilend smart contract was exploited due to a flawed health factor check in the "redeemUnderlying" function, which allowed the withdrawal of 60.672854887643676587 stETH.

Key Event Timeline - UniLend Redeem Underlying Missing Health Factor Check Exploit

Date	Event	Description
January 12th, 2025 4:19:59 AM MST	Ethereum Exploit Transaction	The exploit transaction on Ethereum which is able to remove 60.672854887643676587 stETH.
January 12th, 2025 8:54:00 PM MST	SlowMist Analysis Posted	SlowMist posts
January 13th, 2025 7:04:00 AM MST	UniLend Tweets Notice	UniLend makes a post publicly acknowledging the vulnerability and effects. According to their post, the impact represents only $200k out of the $4.7m in TVL (total value locked) for their protocol. They are "working on a resolution for affected users".
January 13th, 2025 11:16:00 AM MST	Tikkala Research Analysis Posted	Tikkala Research shares an initial analysis of the damage, and subsequently the cause, of the significant loss in the UniLend platform.

Technical Details

The Unilend exploit occurred due to a flawed health factor check in the "redeemUnderlying" function, where the health factor was calculated before collateral transfer, allowing a hacker to manipulate the system and withdraw assets without proper collateral.

According to Nick L Franklin, the Unilend Pool exploit that led to a $200k loss was caused by a flaw in the health factor check in the "redeemUnderlying" function of the smart contract. The issue stemmed from the sequence of operations: LP tokens were first burned, and then the health factor was checked. However, the health factor was evaluated before the collateral tokens were transferred to the user, leading to an inaccurate balance calculation.

When the health factor was checked, the system relied on the current token balance in the pool contract, which included untransferred tokens. As these tokens were not yet transferred when calculating the user’s token balance, it resulted in an inflated balance. This miscalculation was particularly problematic in pools with large liquidity, as the “userBalanceOfToken” function returned a higher "lendBalance" with a small lending share, making it appear that the user had more collateral than they actually did.

A hacker exploited this vulnerability by depositing a massive amount of USDC (60 million) into the lending pool, borrowing stETH, and then withdrawing all the USDC. This allowed the hacker to effectively gain 60 stETH for free, bypassing the intended collateral requirements. The health factor check should have occurred after the token transfer, and to prevent such issues, it was recommended that the "getShareByValue" function use divUp instead of div to avoid rounding errors and ensure more accurate calculations.

In summary, the exploit took advantage of a timing flaw in the health factor check and inaccurate token balance calculations during withdrawal. These issues allowed the hacker to manipulate the system, withdrawing assets without providing adequate collateral.

Tikkala Research: "The root cause is the shares inflation, After burn the LPposition, @UniLend_Finance forgot to remove the underlying tokens which should reduce the token0.balanceOf(address(this)). When it start to count the HealthFactor of the position, it still uses the old balance and allows users to get more collateral (_lendBalance0) than they deposited."

Total Amount Lost

Amount of loss: $ 197,600 (60.672854887643676587 stETH)

The total amount lost has been estimated at $198,000 USD.

Immediate Reactions

The exploit was picked up by multiple blockchain analysts including SlowMist, Tikkala Research, and Nick L Franklin.

"On January 13, 2025, the SlowMist MistEye security monitoring system detected an attack on UniLend, resulting in a loss of ~$197K."

Ultimate Outcome

While UniLend publicly acknowledged the attack and claimed to be working with affected users, it was unclear what outcome occurred, if any.

UniLend Finance offered a 20% bounty. It does not appear that the attacker took them up on the offer.

Total Amount Recovered

It is unclear if affected user assets were recovered.

There do not appear to have been any funds recovered in this case.

Ongoing Developments

What parts of this case are still remaining to be concluded?

Individual Prevention Policies

No specific policies for individual prevention have yet been identified in this case.

For the full list of how to protect your funds as an individual, check our Prevention Policies for Individuals guide.

Platform Prevention Policies

Policies for platforms to take to prevent this situation have not yet been selected in this case.

For the full list of how to protect your funds as a financial service, check our Prevention Policies for Platforms guide.

Regulatory Prevention Policies

No specific regulatory policies have yet been identified in this case.

For the full list of regulatory policies that can prevent loss, check our Prevention Policies for Regulators guide.