Ad
Inputs (2)
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
39.20
Output transaction:
Settlement height:
Value:
0.474903957 ERG
Outputs (3)
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
30.80
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent in transaction:
Settlement height:
Value:
0.473803957 ERG
Tokens:
Transaction Details
Status: Confirmed
Size: 2.7 KB
Received time: 4/11/2025 05:16:46 PM
Included in blocks: 1,501,369
Confirmations: 263,548
Total coins transferred: 0.475903957 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000398 ERG
Raw Transaction Data
{
  "id": "8a8fdb56e72ed75a8bcb65010fd41e7872c33d316aefa391bae06d9bad320116",
  "blockId": "f3959c88f58eb9949c444b6264f9858bec7c0d8337aab9d145dc27a79fee855a",
  "inclusionHeight": 1501369,
  "timestamp": 1744391806225,
  "index": 33,
  "globalIndex": 8825826,
  "numConfirmations": 263548,
  "inputs": [
    {
      "boxId": "ec88802ed2070fd7235149192bd707b01a567f61463ad196ac6732ef56f2b00d",
      "value": 1000000,
      "index": 0,
      "spendingProof": "26cf6b0c2823e9406e6d87a8896e190b27aadffe03d98a9d4d4c8add3810a0f9c20faf30785a8b229957303ec6b434ac16114601cc677237",
      "outputBlockId": "cfbd373596a1b55ed6d5762434316ffcb30de3c4a2be5ce8c97c68185ec8c36a",
      "outputTransactionId": "4f3298343a20be84d88c6eccf5d70b1cf70905eb8d9e61b9c8badbfdab3742de",
      "outputIndex": 0,
      "outputGlobalIndex": 47072467,
      "outputCreatedAt": 1490758,
      "outputSettledAt": 1490761,
      "ergoTree": "0008cd0223ed5cd24df45bca18a8d049e5df2c857b1c87c136daf771278afb474721afd6",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(23ed5c,dc9b6d,...)))}",
      "address": "9entE87Q7trqHzUk99FKnTRxA8nFe4as8k1k3QY1aMEgP2M2rEa",
      "assets": [
        {
          "tokenId": "03faf2cb329f2e90d6d23b58d91bbb6c046aa143261cc21f52fbe2824bfcbf04",
          "index": 0,
          "amount": 3920,
          "name": "SigUSD",
          "decimals": 2,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    },
    {
      "boxId": "d73858150ac3ac1a945d27f0d624585af28bf62cf9179dcba9af42e23ffbf1ac",
      "value": 474903957,
      "index": 1,
      "spendingProof": "38b904a7732add0e49c1eab00186b96adbe10bdc079f50b330ce3be664c96e5642bbda806e38a61e250fb0427327349becb4f4acd49ec65b",
      "outputBlockId": "a82176212b50daef50ea9922032bea46dce9561b8ded2f264d251e827e116f53",
      "outputTransactionId": "6436213dccd8d197a6d40410437e84102b7e210fd259e69e7de4d5b5db8f426e",
      "outputIndex": 1,
      "outputGlobalIndex": 47057145,
      "outputCreatedAt": 1490079,
      "outputSettledAt": 1490082,
      "ergoTree": "0008cd0223ed5cd24df45bca18a8d049e5df2c857b1c87c136daf771278afb474721afd6",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(23ed5c,dc9b6d,...)))}",
      "address": "9entE87Q7trqHzUk99FKnTRxA8nFe4as8k1k3QY1aMEgP2M2rEa",
      "assets": [],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "05a517",
          "sigmaType": "SLong",
          "renderedValue": "-1491"
        },
        "R5": {
          "serializedValue": "05a9d6f3c403",
          "sigmaType": "SLong",
          "renderedValue": "-474903957"
        }
      }
    }
  ],
  "dataInputs": [],
  "outputs": [
    {
      "boxId": "45d1933d7a8daebc52cf5af054d8ccc176e03615ec8c6428a3284950acc97014",
      "transactionId": "8a8fdb56e72ed75a8bcb65010fd41e7872c33d316aefa391bae06d9bad320116",
      "blockId": "f3959c88f58eb9949c444b6264f9858bec7c0d8337aab9d145dc27a79fee855a",
      "value": 1000000,
      "index": 0,
      "globalIndex": 47304913,
      "creationHeight": 1501367,
      "settlementHeight": 1501369,
      "ergoTree": "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",
      "ergoTreeConstants": "0: Coll(48,-116,21,-33,-8,-92,-81,-69,-46,-102,-104,-5,-53,46,28,-114,-1,101,42,-60,70,-120,67,17,-32,76,-120,-14,76,67,-54,113)\n1: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n2: Coll(31,-42,-32,50,-24,71,108,74,-91,76,24,-63,-93,8,-36,-24,57,64,-24,-12,-94,-113,87,100,64,81,62,-41,50,106,-44,-119)\n3: Coll(-8,109,-40,-16,-93,-101,-91,-112,50,-122,91,40,67,64,29,70,1,-48,26,110,119,-116,74,-4,-83,-121,-109,40,-49,-77,19,-100,-101,126,-88,-71,-85,-85,125,46,96,-91,-39,44,107,25,57,-81,26,124,19,-104,90,-108,46,-19,-108,-29,-36,90,-81,55,-68,-125)",
      "ergoTreeScript": "{\n  val func1 = {(tuple1: (Coll[Box], Coll[Byte])) => tuple1._1.filter({(box3: Box) => blake2b256(box3.propositionBytes) == tuple1._2 }) }\n  val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n    tuple2._1.filter({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n  }\n  val coll3 = Coll[Byte]()\n  val opt4 = getVar[Coll[Byte]](1.toByte)\n  val func5 = {(coll5: Coll[Box]) => coll5.fold(0L, {(tuple7: (Long, Box)) => tuple7._1 + tuple7._2.value }) }\n  val coll6 = placeholder[Coll[Byte]](3)\n  val coll7 = coll6.slice(32, 64)\n  val coll8 = placeholder[Coll[Byte]](0)\n  val func9 = {(box9: Box) => box9.R4[AvlTree].get }\n  val coll10 = placeholder[Coll[Byte]](2)\n  val func11 = {(tuple11: (Coll[Box], Coll[Byte])) => tuple11._1.flatMap({(box13: Box) => box13.tokens }).fold(0L, {(tuple13: (Long, (Coll[Byte], Long))) =>\n        val tuple15 = tuple13._2\n        tuple13._1 + if (tuple15._1 == tuple11._2) { tuple15._2 } else { 0L }\n      }) }\n  val func12 = {(opt12: Option[Coll[Byte]]) => opt12.get.slice(1, 33) }\n  val coll13 = Coll[Byte](\n    91.toByte, -49.toByte, -15.toByte, 2.toByte, 37.toByte, 67.toByte, 102.toByte, 120.toByte, 12.toByte, -43.toByte, 25.toByte, 18.toByte, 87.toByte, 5.toByte, 10.toByte, 110.toByte, -45.toByte, 58.toByte, -59.toByte, -47.toByte, 46.toByte, -17.toByte, 14.toByte, 48.toByte, 65.toByte, 57.toByte, -19.toByte, 93.toByte, -104.toByte, 31.toByte, 75.toByte, -6.toByte\n  )\n  val b14 = getVar[Byte](0.toByte).get\n  val func15 = {(box15: Box) => box15.tokens(1) }\n  val i16 = INPUTS.indexOf(SELF, 0)\n  val func17 = {(l17: Long) =>\n    if (l17 < 128L) { 1 } else {\n      if (l17 < 16384L) { 2 } else {\n        if (l17 < 2097152L) { 3 } else {\n          if (l17 < 268435456L) { 4 } else {\n            if (l17 < 34359738368L) { 5 } else {\n              if (l17 < 4398046511104L) { 6 } else { if (l17 < 562949953421312L) { 7 } else { if (l17 < 72057594037927936L) { 8 } else { 9 } } }\n            }\n          }\n        }\n      }\n    }\n  }\n  sigmaProp(anyOf(Coll[Boolean]({(b18: Byte) => if ((b18 == 3.toByte) || (b18 == 4.toByte)) {(\n            val coll20 = blake2b256(SELF.propositionBytes)\n            val box21 = func1((OUTPUTS, coll20))(0)\n            val coll22 = CONTEXT.dataInputs\n            val box23 = func2((coll22, placeholder[Coll[Byte]](1)))(0)\n            val coll24 = opt4.getOrElse(coll3)\n            val coll25 = func1((INPUTS, coll20))\n            val l26 = func5(coll25)\n            val box27 = func2((OUTPUTS, coll7))(0)\n            val coll28 = func9(func2((coll22, coll8))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-119.toByte, 46.toByte, 111.toByte, 71.toByte, -95.toByte, 13.toByte, 92.toByte, -112.toByte, -72.toByte, 122.toByte, -44.toByte, -122.toByte, 51.toByte, 85.toByte, -50.toByte, -83.toByte, 0.toByte, -61.toByte, -30.toByte, -104.toByte, 50.toByte, 23.toByte, -18.toByte, 21.toByte, 83.toByte, 50.toByte, 83.toByte, -51.toByte, -102.toByte, 96.toByte, 37.toByte, -62.toByte), Coll[Byte](79.toByte, -40.toByte, -80.toByte, -42.toByte, -39.toByte, -126.toByte, 66.toByte, 114.toByte, 111.toByte, 87.toByte, -77.toByte, -33.toByte, -90.toByte, -122.toByte, 18.toByte, 103.toByte, -110.toByte, -72.toByte, -27.toByte, 5.toByte, 110.toByte, 29.toByte, 81.toByte, -74.toByte, -23.toByte, 13.toByte, 104.toByte, -128.toByte, -49.toByte, 45.toByte, -51.toByte, -59.toByte), Coll[Byte](-80.toByte, -71.toByte, 7.toByte, -85.toByte, -81.toByte, -83.toByte, -115.toByte, -1.toByte, -50.toByte, 47.toByte, -97.toByte, 29.toByte, -6.toByte, 21.toByte, 53.toByte, -64.toByte, 34.toByte, -35.toByte, -96.toByte, 83.toByte, 102.toByte, -12.toByte, -5.toByte, -46.toByte, 127.toByte, 88.toByte, 29.toByte, 19.toByte, 47.toByte, 75.toByte, 35.toByte, -10.toByte), Coll[Byte](-72.toByte, -61.toByte, 44.toByte, 11.toByte, -98.toByte, 66.toByte, -52.toByte, -122.toByte, -48.toByte, 48.toByte, -78.toByte, 97.toByte, -114.toByte, 90.toByte, 6.toByte, -64.toByte, -46.toByte, -21.toByte, 43.toByte, -96.toByte, 100.toByte, 31.toByte, 9.toByte, 6.toByte, -123.toByte, -71.toByte, -123.toByte, -19.toByte, -85.toByte, 16.toByte, -107.toByte, 111.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll3))\n            val coll29 = {(opt29: Option[Coll[Byte]]) => opt29.get.slice(6, 38) }(coll28(3))\n            val l30 = byteArrayToLong(coll28(2).get.slice(1, 9))\n            val l31 = func11((coll25, coll10))\n            val coll32 = Coll[Box](box21)\n            val l33 = func11((coll32, coll10))\n            val l34 = func11((coll25, coll29))\n            val l35 = func11((coll32, coll29))\n            val bool36 = box21.tokens.filter({(tuple36: (Coll[Byte], Long)) =>\n                val coll38 = tuple36._1\n                (coll38 != coll10) && (coll38 != coll29)\n              }).forall({(tuple36: (Coll[Byte], Long)) => tuple36._2 >= func11((coll25, tuple36._1)) })\n            val bool37 = coll25.flatMap({(box37: Box) => box37.tokens }).forall({(tuple37: (Coll[Byte], Long)) =>\n                val coll39 = tuple37._1\n                (coll39 == coll10) || box21.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == coll39 })\n              })\n            anyOf(Coll[Boolean]({(b38: Byte) => if (b38 == 3.toByte) {(\n                    val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](34.toByte, 94.toByte, 63.toByte, -59.toByte, -47.toByte, -119.toByte, -11.toByte, 71.toByte, -39.toByte, -58.toByte, 38.toByte, -66.toByte, -67.toByte, -58.toByte, 113.toByte, 57.toByte, -117.toByte, 108.toByte, 0.toByte, 124.toByte, 120.toByte, 61.toByte, -60.toByte, 127.toByte, -112.toByte, 63.toByte, 36.toByte, -65.toByte, 127.toByte, 52.toByte, -124.toByte, 121.toByte), Coll[Byte](-68.toByte, 74.toByte, 90.toByte, -71.toByte, -28.toByte, 90.toByte, -73.toByte, 75.toByte, 121.toByte, -6.toByte, -20.toByte, -65.toByte, 103.toByte, 73.toByte, 108.toByte, -62.toByte, -65.toByte, -116.toByte, 43.toByte, 14.toByte, 85.toByte, -37.toByte, -24.toByte, -84.toByte, -49.toByte, -61.toByte, -99.toByte, 20.toByte, -119.toByte, 17.toByte, 116.toByte, -112.toByte), Coll[Byte](118.toByte, 124.toByte, -86.toByte, -128.toByte, -71.toByte, -114.toByte, 73.toByte, 106.toByte, -40.toByte, -87.toByte, -10.toByte, -119.toByte, -60.toByte, 65.toByte, 10.toByte, -28.toByte, 83.toByte, 50.toByte, 127.toByte, 15.toByte, -107.toByte, -23.toByte, 80.toByte, -124.toByte, -64.toByte, -82.toByte, 32.toByte, 99.toByte, 80.toByte, 121.toByte, 59.toByte, 119.toByte), coll13), coll24)\n                    val l41 = byteArrayToLong(coll40(0).get.slice(1, 9)) * {(box41: Box) => box41.R5[Coll[Long]].get(2) }(box27) + 1L\n                    val bool42 = coll10 == coll29\n                    allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(3).get.slice(1, 9)), l33 >= l31 - l41 + byteArrayToLong(coll40(1).get.slice(1, 9)) + if (bool42) { l30 } else { 0L }, if (bool42) { true } else { l35 >= l34 - l30 }, bool36, bool37, func11((Coll[Box](OUTPUTS.filter({(box43: Box) => blake2b256(box43.propositionBytes) == coll40(2).get.slice(1, 33) })(0)), coll10)) >= l41, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(1))))\n                  )} else { false } }(b14), {(b38: Byte) => if (b38 == 4.toByte) {(\n                    val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](-20.toByte, -14.toByte, -48.toByte, 75.toByte, -82.toByte, 72.toByte, -96.toByte, 10.toByte, -118.toByte, 110.toByte, 73.toByte, -64.toByte, 86.toByte, 114.toByte, 99.toByte, -55.toByte, -11.toByte, -46.toByte, 63.toByte, 38.toByte, -56.toByte, 35.toByte, 88.toByte, -95.toByte, 118.toByte, -85.toByte, -47.toByte, -16.toByte, 33.toByte, -40.toByte, -79.toByte, 48.toByte), coll13), coll24)\n                    allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(1).get.slice(1, 9)), l33 >= l31 - byteArrayToLong(coll40(0).get.slice(1, 9)), if (coll10 == coll29) { true } else { l35 >= l34 }, bool36, bool37, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(0)), func15(box27)._2 == func15(func2((INPUTS, coll7))(0))._2))\n                  )} else { false } }(b14)))\n          )} else { false } }(b14), {(b18: Byte) => if (b18 == 9.toByte) { func9(func2((CONTEXT.dataInputs, coll8))(0)).getMany(Coll[Coll[Byte]](blake2b256(Coll[Byte](105.toByte, 109.toByte, 46.toByte, 112.toByte, 97.toByte, 105.toByte, 100.toByte, 101.toByte, 105.toByte, 97.toByte, 46.toByte, 99.toByte, 111.toByte, 110.toByte, 116.toByte, 114.toByte, 97.toByte, 99.toByte, 116.toByte, 115.toByte, 46.toByte, 97.toByte, 99.toByte, 116.toByte, 105.toByte, 111.toByte, 110.toByte, 46.toByte).append(func2((INPUTS, coll6.slice(0, 32)))(0).propositionBytes))), opt4.get)(0).isDefined } else { false } }(b14), {(b18: Byte) => if (b18 == 10.toByte) {(\n            val coll20 = blake2b256(SELF.propositionBytes)\n            val coll21 = func1((INPUTS, coll20))\n            val coll22 = func1((OUTPUTS, coll20))\n            val l23 = func5(coll21)\n            allOf(Coll[Boolean](coll21.size >= 5, coll22.size == 1, coll22(0).tokens.forall({(tuple24: (Coll[Byte], Long)) => func11((coll21, tuple24._1)) == tuple24._2 }), l23 - func5(coll22) <= 2000000L, l23 >= 2000000L))\n          )} else { false } }(b14), {(b18: Byte) => if (b18 == 7.toByte) { {(tuple20: (Coll[Byte], Box)) => if (i16 >= OUTPUTS.size) { false } else {(\n                val box22 = OUTPUTS(i16)\n                val l23 = box22.value\n                val l24 = SELF.value\n                val coll25 = box22.propositionBytes\n                val coll26 = SELF.bytesWithoutRef\n                val coll27 = SELF.propositionBytes\n                val i28 = SELF.creationInfo._1\n                val coll29 = box22.bytesWithoutRef\n                val i30 = box22.creationInfo._1\n                allOf(Coll[Boolean](l23 >= l24 - 2000000L, blake2b256(coll25) == func12(func9(tuple20._2).getMany(Coll[Coll[Byte]](tuple20._1), opt4.getOrElse(coll3))(0)), coll26.slice(func17(l24) + coll27.size + func17(i28.toLong), coll26.size) == coll29.slice(func17(l23) + coll25.size + func17(i30.toLong), coll29.size), anyOf(Coll[Boolean](i30 - i28 >= 504000, coll27 != coll25))))\n              )} }((Coll[Byte](-57.toByte, -59.toByte, 55.toByte, -26.toByte, -58.toByte, 53.toByte, -109.toByte, 14.toByte, -53.toByte, 74.toByte, -50.toByte, -107.toByte, -91.toByte, 73.toByte, 38.toByte, -77.toByte, -85.toByte, 119.toByte, 105.toByte, -115.toByte, -97.toByte, 73.toByte, 34.toByte, -16.toByte, -79.toByte, -59.toByte, -114.toByte, -88.toByte, 113.toByte, 86.toByte, 72.toByte, 59.toByte), func2((CONTEXT.dataInputs, coll8))(0))) } else { false } }(b14))))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "03faf2cb329f2e90d6d23b58d91bbb6c046aa143261cc21f52fbe2824bfcbf04",
          "index": 0,
          "amount": 3080,
          "name": "SigUSD",
          "decimals": 2,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "db58395e3545578ab0148a294618b457e53db0d832fda2da1104b9cf883cd5e5",
      "mainChain": true
    },
    {
      "boxId": "61ce79cf08de83304c47bb0b68c9c91162a91a6445c96bfce147adf5f522bcab",
      "transactionId": "8a8fdb56e72ed75a8bcb65010fd41e7872c33d316aefa391bae06d9bad320116",
      "blockId": "f3959c88f58eb9949c444b6264f9858bec7c0d8337aab9d145dc27a79fee855a",
      "value": 1100000,
      "index": 1,
      "globalIndex": 47304914,
      "creationHeight": 1501367,
      "settlementHeight": 1501369,
      "ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
      "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(16,2,4,-96,11,8,-51,2,121,-66,102,126,-7,-36,-69,-84,85,-96,98,-107,-50,-121,11,7,2,-101,-4,-37,45,-50,40,-39,89,-14,-127,91,22,-8,23,-104,-22,2,-47,-110,-93,-102,-116,-57,-89,1,115,0,115,1)\n3: Coll(1)\n4: 1",
      "ergoTreeScript": "{sigmaProp(\n  allOf(\n    Coll[Boolean](\n      HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n        placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n      ), OUTPUTS.size == placeholder[Int](4)\n    )\n  )\n)}",
      "address": "2iHkR7CWvD1R4j1yZg5bkeDRQavjAaVPeTDFGGLZduHyfWMuYpmhHocX8GJoaieTx78FntzJbCBVL6rf96ocJoZdmWBL2fci7NqWgAirppPQmZ7fN9V6z13Ay6brPriBKYqLp1bT2Fk4FkFLCfdPpe",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "f6ac0ab28e42054005f641dc820bada9bd2ca02b62b20583a6e38cc61df97606",
      "mainChain": true
    },
    {
      "boxId": "dcebd8f0233b9197790cbe63f824d15308c401d8ca0a18a6233c67140a21e8c1",
      "transactionId": "8a8fdb56e72ed75a8bcb65010fd41e7872c33d316aefa391bae06d9bad320116",
      "blockId": "f3959c88f58eb9949c444b6264f9858bec7c0d8337aab9d145dc27a79fee855a",
      "value": 473803957,
      "index": 2,
      "globalIndex": 47304915,
      "creationHeight": 1501367,
      "settlementHeight": 1501369,
      "ergoTree": "0008cd0223ed5cd24df45bca18a8d049e5df2c857b1c87c136daf771278afb474721afd6",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(23ed5c,dc9b6d,...)))}",
      "address": "9entE87Q7trqHzUk99FKnTRxA8nFe4as8k1k3QY1aMEgP2M2rEa",
      "assets": [
        {
          "tokenId": "03faf2cb329f2e90d6d23b58d91bbb6c046aa143261cc21f52fbe2824bfcbf04",
          "index": 0,
          "amount": 840,
          "name": "SigUSD",
          "decimals": 2,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "8d7b898a751dc06d231e2a44967705cb528fe734bdec0b03c43757f082c7d56d",
      "mainChain": true
    }
  ],
  "size": 2766,
  "isUnconfirmed": false
}