Becoming a Millionaire, 0.000150 BTC at a Time

Becoming a Millionaire, 0.000150 BTC at a Time

How we discovered a critical issue in Solana’s stable swap implementation. A story about arbitrage and rounding.

We discovered a critical rounding issue in the Solana Program Library’s implementation of stable swap, spl-token-swap. Similar to Neodyme’s spl-token-lending exploit, we were able to extract a single token per instruction. This exceeds the value of the 5000 lamport transaction fee on BTC stable swaps, allowing an attacker to profitably drain funds.

Such BTC stable swaps had over 74 million in combined value. The total value of stable swaps impacted exceed 700 million.

We would also like to thank the Saber team for their fast triage and remediation.

Rounding bugs are an increasingly common vulnerability class, enabled by low transaction costs

Discovery

Parth, one of our researchers, was implementing a graph search for our arbitrage bot to calculate the price of any token relative to SOL.

After a while, he noticed something weird..

so either my graph search is wrong or its possible to get a ton of money out of nothing

KwnjUuZ :              0 9vMJfxu ->              1 EPjFWdd
KwnjUuZ :              1 EPjFWdd ->              2 9vMJfxu
KwnjUuZ :              2 9vMJfxu ->              3 EPjFWdd
HU1tejU :              3 EPjFWdd ->            625 PRT88Rk
24ZbKS3 :            625 PRT88Rk ->              7 EPjFWdd
3oRPcFa :              7 EPjFWdd ->              6 BQcdHdA

Somehow, we were getting tokens from nothing?

After taking a look at the pairs on which this was occuring, we quickly realized that only stable swap pairs were impacted.

KwnjUuZhTMTSGAaavkLEmSyfobY16JNH4poL9oeeEvE
HU1tejUtt7AZYrC9SAuqCW9MpuSqsdoedHSb1XUKjUPN
24ZbKS36rkPv14Tdx8qv4NRyqatTaJ5KgJrT1LxBKn5d
3oRPcFaRHvv9pPR6nRasigVDkm3k9kTjdfjxUpgLV5Pq

This seemed suspicious. Perhaps it had something to do with the stable swap math?

It was also weird how we could only ever get at most one extra token. As usual, the best way to answer such questions is to read the code. We dived into the stable swap Solana implementation to look for a possible root cause.

    // Solve for y by approximating: y**2 + b*y = c
    let mut y = d_val;
    for _ in 0..ITERATIONS {
        let (y_new, _) = (checked_u8_power(&y, 2)?.checked_add(c)?)
            .checked_ceil_div(checked_u8_mul(&y, 2)?.checked_add(b)?.checked_sub(d_val)?)?;
        if y_new == y {
            break;
        } else {
            y = y_new;
        }
    }

approximate. Looks suspicious.. Perhaps we really did find a bug in the Solana Program Library?

With this promising find in mind, we decided to throw together a quick proof of concept. To do this, we attempted to swap very small amounts of tokens back and forth between sBTC and renBTC.

// from sbtc to renbtc
for i in 0 .. 50u8 {
    // create swap transaction
    let mut swap_instruction = swap(
        &spl_token::id(),
        &swap_pubkey,
        &swap_authority_pubkey,
        &test_account_signer.pubkey(),
        &sbtc_user_account,
        &sbtc_reserve,
        &renbtc_reserve,
        &renbtc_user_account,
        &admin_fee_account_sbtc_to_ren,
        1,
        2
    ).unwrap();

    // nonce
    swap_instruction.data.append(&mut vec![i, extranonce]);

    let mut instructions = vec![];

    instructions.push(swap_instruction);

    env.execute_as_transaction(&instructions, &vec![&test_account_signer]);
}

It works!

holy shit yea, this is big

Exploitability

Off-by-one bugs are much easier to exploit on Solana compared to other chains, enabled by the relatively low fees on Solana.

A single swap on Ethereum can cost dozens of dollars, but on Solana packing hundreds of swap instructions into a single transaction costs the same flat rate of 5000 lamports (at least prior to the 1.9 per transaction size compute limit update).

This transaction cost discrepancy can trip up developers who transitioned from Ethereum to Solana. For example, the developers who wrote tests for the Solana Program Library implementation of stable swap assumed the impact of an off by one error would be negligible.

As we mentioned previously, due to the rounding error, each swap allowed an attacker to steal a single token. It’s important to keep in mind that this represents a single token per instruction. Transactions on Solana can also contain multiple instructions.

With an onchain program, we are able to fit over 50 swap instructions per transaction. Each transaction can be run around 3 times before exceeding the per-instruction compute limit cap. Thus, we can pack around 150 invocations per transaction.

Some quick napkin math confirms that this is indeed profitable. At a price of $41440 per Bitcoin, we are able to steal around 6 cents per transaction.

\[10^{-8}\text{ BTC} * \$41,400/\text{BTC} * 150 \text{ swaps} = \$0.0621\]

At 200 transactions per second, we can extract just over a million dollars per day.

We’re well on our way to becoming a millionaire!

Patch

Now that we had a proof-of-concept going, it was time to contact the relevant teams.

By grepping through Solana logs for the swap instruction log, we were able to identify many potential spl-token-swap forks.

solana logs -um | grep 'Instruction: Swap' -B1

With some Google dorking, we were able to identify many of these programs.

1SoLTvbiicqXZ3MJmnTL2WYXKLYpuxwHpa4yYrVQaMZ  - "1 SOL"
9W959DqEETiGZocYWCQPaJ6sBmUzgfxXfqGeTEdp3aQP - Orca Swap Program v2
SCHAtsf8mbjyjiv4LkhLKutTf6JnZAbdJKFkXQNMFHZ  - "Sencha Swap"
SSwapUtytfBdBn1b9NUGG6foMVPtcWgpRU32HToDUZr  - "Saros Swap"
SSwpkEEcbUqx4vtoEByFjSkhKdCT862DNVb52nZg1UZ  - Saber Stable Swap Program
SSwpMgqNDsyV7mAgN9ady4bDVu5ySjmmXejXvy2vLt1  - Step Finance Swap Program
SwaPpA9LAaLfeLi3a68M4DjnLqgtticKg6CnyNwgAC8  - Swap Program

Now it was time to contact these teams.

Of these protocols, Saber was the only one which had BTC stable swaps, which would make exploitation immediately profitable. Luckily, they were also the most responsive, triaging and patching the vulnerability in just over one day.

After some discussion, they decided to port a patch from Curve.fi, subtracting one from the output amount.

-        let dy = swap_destination_amount.checked_sub(y)?;
+        // https://github.com/curvefi/curve-contract/blob/b0bbf77f8f93c9c5f4e415bce9cd71f0cdee960e/contracts/pool-templates/base/SwapTemplateBase.vy#L466
+        let dy = swap_destination_amount.checked_sub(y)?.checked_sub(1)?;

For reference, here is the Curve.fi implementation.

    dy: uint256 = xp[j] - y - 1  # -1 just in case there were some rounding errors
    dy_fee: uint256 = dy * self.fee / FEE_DENOMINATOR

We originally thought this was an additional patch that didn’t get ported over to Solana. However, it turns out this code was actually included in the original commit, not as an additional security patch.

commit 0fd801df7488d89f0e2fc81e760942d7858b01d6
Author: Ben Hauser <ben@hauser.id>
Date:   Mon Aug 31 02:35:30 2020 +0300

    feat: add base pool without lending

The commit adding stable swaps to SPL was made a few months later, meaning there was some disconnect when porting the code. Either the rounding was thought to be unnecesary, or it was simply forgotten.

commit d62ddd2b94d5d2daaa97460b165d288610a87623
Author: Yuriy Savchenko <yuriy.savchenko@gmail.com>
Date:   Tue Nov 17 15:13:18 2020 +0200

    Added stable curve invariant to the token swap smart contract (#838)

    * Added stable curve invariant to the token swap smart contract

    * Fixed formatting

    * Added missing stable curve constraints

    * Symbol renames to make math clearer

    * Small refactoring according to PR comments, fixes for JS tests

After contacting some other swap projects which were unaffected, we decided to notify the Solana team in order to get a patch upstreamed to the Solana Program Library.

While few projects deploy the swap program from the Solana Program Library, the SPL program is meant as a reference implementation, and many exchanges fork their own code off of it.

@joncinque helped triage this patch. We also asked him for his thoughts on a more complete solution.

Honestly, the idea of just subtracting 1 from the output will cover almost all situations correctly, so it’s a good quick solution. I’ll take a look to see if we can solve this for all situations through a correct application of checked_ceil_div, as with the constant product curve.

After some thought, he helped introduce a PR which ceilings the computation in compute_new_destination_amount to correctly round within the stable curve math library.

     // Solve for y by approximating: y**2 + b*y = c
     let mut y_prev: U256;
     let mut y = d_val;
     for _ in 0..ITERATIONS {
-        y_prev = y;
-        y = (checked_u8_power(&y, 2)?.checked_add(c)?)
-            .checked_div(checked_u8_mul(&y, 2)?.checked_add(b)?.checked_sub(d_val)?)?;
-        if y == y_prev {
+        let (y_new, _) = (checked_u8_power(&y, 2)?.checked_add(c)?)
+            .checked_ceil_div(checked_u8_mul(&y, 2)?.checked_add(b)?.checked_sub(d_val)?)?;
+        if y_new == y {
             break;
+        } else {
+            y = y_new;
         }

Closing Thoughts

This is a good example of how messing around and interacting with the ecosystem can lead to unexpected bugs. We found this, not as a result of active security research, but as part of our work in MEV and trading.

Another interesting takeaway is that fuzzing can give a false sense of security. Prior to our report, Saber had already deployed comprehensive fuzzers for their swap implementation. A researcher looking at code coverage alone might come to the incorrect conclusion that such extensively fuzzed code couldn’t possibly have a vulnerability.

One can see parallels to traditional security, as with Google Project Zero’s port-mortem of the NSS overflow.

A heavily fuzzed method had a trivial buffer overflow due to an arbitrary size limit on the input data. Implict assumptions can often undermine security.

Especially with regard to onchain programs, it’s important to consider what actually is a “vulnerability”. Getting tokens from nothing is a more obvious example, but more subtle bugs can arise with increasingly complex defi interactions. Economic invariants are much harder to detect than say, memory corruption.

A comprehensive evaluation of smart contracts relies on a deep understanding of economic implications within the Solana ecosystem.


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