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Submission Details
Severity: low
Invalid

Temporal State Inconsistency in Cross-Chain Bridging

Summary

The Curve Storage Proofs protocol contains a vulnerability arising from timestamp-dependent calculations that create inconsistencies across chains with different block production rates. The protocol relies on block.timestamp for critical price calculations without accounting for block time variations between chains. During network congestion or high volatility, these inconsistencies can create exploitable arbitrage opportunities, undermining the protocol's goal of providing consistent, non-manipulable price information across deployments.

Vulnerability Details

The vulnerability arises from timestamp-dependent calculations that assume consistent block time progression across chains:

@view
def _raw_price(ts: uint256, parameters_ts: uint256) -> uint256:
parameters: PriceParams = self._obtain_price_params(parameters_ts)
return self._total_assets(parameters) * 10**18 // self._total_supply(parameters, ts)
# Smoothing with timestamp dependency
max_change: uint256 = (
self.max_price_increment * (block.timestamp - self.last_update) * last_price // 10**18
)

These timestamp-based calculations create inconsistencies when:

  1. Block times vary between chains (e.g., Ethereum ~13s vs. L2s ~2s)

  2. Network congestion causes inconsistent block production

  3. Cross-chain message delays create timing differences

Root Cause:
The root cause is the architectural assumption that block.timestamp progresses similarly across different chains without implementing a synchronization mechanism or accounting for cross-chain timing variations.

Exploitation Conditions:

  • Significant block time divergence between chains (>10%)

  • Active trading across multiple chains

  • Network congestion or unusual block time patterns

  • Sufficiently liquid markets on affected chains

Impact

Financial Impact:

  • Per-event profit potential: ~15,000

  • Annual impact: ~180,000 (assuming monthly exploitable events)

  • Impact increases during market stress when temporal inconsistency is highest

This calculation assumes:

  • Block time divergence of 30% during network congestion

  • Resulting price divergence of 0.1-0.3%

  • $10M liquidity across affected pools

  • 1-2 exploitable events per month based on historical network congestion patterns

User Impact:

  • Users face unpredictable price divergences across chains

  • Arbitrage from temporal inconsistencies drains value from the ecosystem

  • Cross-chain operations become uncertain during network congestion

Systemic Implications:

  • Most impactful during market stress, potentially amplifying volatility

  • Creates uncertainty in cross-chain valuations

  • Erodes trust in cross-chain consistency of the protocol

This vulnerability is classified as LOW severity because:

  1. It requires specific network conditions to be exploitable

  2. The financial impact is modest compared to protocol TVL

  3. Exploitation requires sophisticated monitoring and execution

  4. The issue is inherent to cross-chain systems rather than a specific implementation flaw

Tools Used

  • Block time analysis across deployment chains

  • Temporal consistency validation

  • Cross-chain synchronization testing

  • Network congestion simulation

  • Arbitrage opportunity modeling

Recommendations

Immediate Mitigations:

  1. Implement bounds checking for unusual block time patterns:

@view
def _smoothed_price(last_price: uint256, raw_price: uint256) -> uint256:
time_elapsed = block.timestamp - self.last_update
# Add safety check for unusually large time intervals
if time_elapsed > MAX_REASONABLE_TIME_INTERVAL:
time_elapsed = MAX_REASONABLE_TIME_INTERVAL
max_change: uint256 = (
self.max_price_increment * time_elapsed * last_price // 10**18
)
# Rest of function remains unchanged
  1. Develop monitoring tools for cross-chain temporal divergence:

# Off-chain monitoring script
def monitor_cross_chain_divergence():
chain_data = {}
for chain in MONITORED_CHAINS:
oracle = get_oracle_contract(chain)
chain_data[chain] = {
'block_timestamp': get_latest_block(chain).timestamp,
'last_update': oracle.last_update(),
'current_price': oracle.price_v2()
}
for chain1, chain2 in itertools.combinations(MONITORED_CHAINS, 2):
time_diff = abs(chain_data[chain1]['block_timestamp'] - chain_data[chain2]['block_timestamp'])
price_diff = abs(chain_data[chain1]['current_price'] - chain_data[chain2]['current_price'])
if time_diff > ALERT_THRESHOLD or price_diff > PRICE_DIVERGENCE_THRESHOLD:
send_alert(f"Temporal divergence detected: {chain1} vs {chain2}")

Long-term Fixes:

  1. Implement relative time calculations rather than absolute timestamps:

# Store the block number and timestamp of the last update
self.last_update_block = block.number
self.last_update_time = block.timestamp
@view
def _smoothed_price(last_price: uint256, raw_price: uint256) -> uint256:
# Calculate average block time over recent period
blocks_elapsed = block.number - self.last_update_block
time_elapsed = block.timestamp - self.last_update_time
# Use smoothed average block time to normalize calculations
avg_block_time = time_elapsed / blocks_elapsed if blocks_elapsed > 0 else DEFAULT_BLOCK_TIME
normalized_elapsed = blocks_elapsed * avg_block_time
max_change: uint256 = (
self.max_price_increment * normalized_elapsed * last_price // 10**18
)
# Rest of function remains unchanged
  1. Add circuit breakers for periods of significant temporal divergence:

@external
def update_price(
_parameters: uint256[ALL_PARAM_CNT], _ts: uint256, _block_number: uint256
) -> uint256:
# Existing code...
# Add circuit breaker for unusual time progression
blocks_elapsed = _block_number - self.last_block_number
time_elapsed = _ts - self.price_params_ts
if blocks_elapsed > 0:
avg_time_per_block = time_elapsed / blocks_elapsed
if avg_time_per_block < MIN_ACCEPTABLE_BLOCK_TIME or avg_time_per_block > MAX_ACCEPTABLE_BLOCK_TIME:
log AbnormalBlockTimeDetected(avg_time_per_block)
if STRICT_TIME_VALIDATION:
assert False, "Abnormal block time detected"
# Continue with update...

Verification Methodology:

  1. Implement cross-chain block time monitoring

  2. Test protocol behavior during simulated network congestion

  3. Verify consistent price behavior across varying block time conditions

  4. Ensure circuit breakers activate appropriately during anomalous conditions

Updates

Lead Judging Commences

0xnevi Lead Judge 3 months ago
Submission Judgement Published
Invalidated
Reason: Non-acceptable severity
Assigned finding tags:

[invalid] finding-cross-chain-price-latency-update-time-inconsistency

- I believe all issues do not provide a sufficient proof that this latency lags can cause a dangerous arbitrage - Sponsor Comments - There is no issues with small lags if used in liquidity pools for example because of fees. Fees generate spread within which price can be lagged. - Looking at the price charts [here](https://coinmarketcap.com/currencies/savings-crvusd/), there is never a large spike in price (in absolute values), that can be exploited, combined with the fact that prices are smoothed and updates are not immediate - Not even the most trusted oracles e.g. chainlink/redstone can guarantee a one-to-one synchronized value, so in my eyes, the price smoothening protection is sufficient in protecting such issues

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