flipside

    Faucet Rate-Limit Bugs Address
    aPrioriFaucet Rate-Limit Bugs Address
    Updated 2025-03-05
    WITH address_transactions AS (
    -- 获取所有符合条件的交易
    SELECT
    TO_ADDRESS,
    TX_HASH,
    BLOCK_TIMESTAMP,
    -- 按地址和时间排序
    ROW_NUMBER() OVER (PARTITION BY TO_ADDRESS ORDER BY BLOCK_TIMESTAMP) AS tx_seq
    FROM monad.testnet.fact_transactions
    WHERE FROM_ADDRESS = LOWER('0xD7a24d1F1435CD314E86736E139f8431D4498D4e')
    AND TX_SUCCEEDED
    AND BLOCK_TIMESTAMP >= '2025-02-19 14:00:00'
    ),
    transaction_pairs AS (
    -- 计算每个地址相邻交易之间的时间间隔，并获取前一笔交易的信息
    SELECT
    a.TO_ADDRESS,
    a.TX_HASH AS current_tx_hash,
    a.BLOCK_TIMESTAMP AS current_tx_time,
    a.tx_seq AS current_tx_seq,
    LAG(a.TX_HASH) OVER (PARTITION BY a.TO_ADDRESS ORDER BY a.BLOCK_TIMESTAMP) AS previous_tx_hash,
    LAG(a.BLOCK_TIMESTAMP) OVER (PARTITION BY a.TO_ADDRESS ORDER BY a.BLOCK_TIMESTAMP) AS previous_tx_time,
    LAG(a.tx_seq) OVER (PARTITION BY a.TO_ADDRESS ORDER BY a.BLOCK_TIMESTAMP) AS previous_tx_seq,
    -- 计算与前一笔交易的时间差
    DATEDIFF(SECOND, LAG(a.BLOCK_TIMESTAMP) OVER (PARTITION BY a.TO_ADDRESS ORDER BY a.BLOCK_TIMESTAMP), a.BLOCK_TIMESTAMP) AS time_gap_seconds,
    DATEDIFF(HOUR, LAG(a.BLOCK_TIMESTAMP) OVER (PARTITION BY a.TO_ADDRESS ORDER BY a.BLOCK_TIMESTAMP), a.BLOCK_TIMESTAMP) AS time_gap_hours,
    DATEDIFF(DAY, LAG(a.BLOCK_TIMESTAMP) OVER (PARTITION BY a.TO_ADDRESS ORDER BY a.BLOCK_TIMESTAMP), a.BLOCK_TIMESTAMP) AS time_gap_days
    FROM
    address_transactions a
    )

    select
    wallet
    ,count(distinct current_tx_hash) as Rate_Limit_Bugs_tx_count
    ,min(current_tx_time) as bug_min_block_time
    ,max(current_tx_time) as bug_max_block_time
    Last run: 14 days ago
    WALLET
    RATE_LIMIT_BUGS_TX_COUNT
    BUG_MIN_BLOCK_TIME
    BUG_MAX_BLOCK_TIME
    1
    		0x2309d19042398056ed5868c839b0237427d72e92272025-02-28 07:55:19.0002025-03-03 19:13:28.000
    2
    		0xa844653fe0bcc430affb4bb254b4b5e1f4caf82c202025-02-27 17:21:00.0002025-02-28 09:40:22.000
    3
    		0x638b0ac85541f459d9f6e71199c6ef41bdee5de4142025-02-28 09:50:27.0002025-03-02 04:32:30.000
    4
    		0x42a3c37512489365df1c25bc2ce902676a382cbb142025-03-01 03:12:21.0002025-03-01 19:44:22.000
    5
    		0x7887727a4cf1566b06e6c3c63ac88760feb22727122025-02-28 10:27:44.0002025-02-28 10:40:39.000
    6
    		0xb6580c5a160e5df534305bc200cf2937ce95f238122025-03-01 18:40:29.0002025-03-01 19:37:22.000
    7
    		0xa4e7d0ff4ad2fa57c45742922fb49f27e8c71288122025-03-01 16:29:11.0002025-03-01 16:41:00.000
    8
    		0x96cc2d7340409d5fc3a1f24cd95e5d5f7fd5729e122025-02-28 09:38:48.0002025-03-01 15:29:00.000
    9
    		0x4c4d58ac784ce3bcb5d8f1794517a1b8d17f0355112025-02-28 08:14:40.0002025-03-02 03:04:29.000
    10
    		0x38642af4460101ad6c8d8feb6ffdddff8c3af603102025-02-28 08:14:31.0002025-03-02 03:04:35.000
    11
    		0x7f4a995accc627b0c73d985999e524e18601796c102025-03-01 16:02:56.0002025-03-01 16:40:50.000
    12
    		0xd240a9de14e78e9bd709ddca51f3a0063a96780d102025-02-28 07:47:57.0002025-02-28 08:03:47.000
    13
    		0xbe6e7cd412bce1929a79f2643f09e98860642b7e102025-02-28 07:58:47.0002025-02-28 10:14:02.000
    14
    		0x5309ce86a0e616830c2d69d0a051e86d74fee651102025-03-01 18:59:48.0002025-03-01 19:18:03.000
    15
    		0x463aac736cc2b64a0839e66bb575131bc1715544102025-02-28 07:29:44.0002025-03-01 20:33:15.000
    16
    		0x3c85e0b9d0126ad3c8835dadfd3e8f8c5f91414492025-02-27 20:01:45.0002025-03-02 01:32:44.000
    17
    		0x9c600d6eb117a92b4ef402c8dcff371914d851db92025-02-28 10:32:10.0002025-03-01 19:40:03.000
    18
    		0xaa8ff39efb40a7a626fe16c561e860d3f11fd33292025-03-01 19:57:03.0002025-03-03 13:02:34.000
    19
    		0x701a1570395843eac780020176ba6f8d264e9aff92025-02-28 07:37:09.0002025-03-01 17:05:05.000
    20
    		0x1237351e07214a751e56cdf0412c2ca42cf5976692025-02-28 07:10:18.0002025-03-01 22:37:43.000
    ...
    2161
    213KB
    8s