June 2

https://commonwealth.im/layerzero/discussion/20021-sybil-clusters-about-evm-and-aptos

Sybil Clusters about evm and aptos

Danniel0x000

Published 5 days ago

56 views

Reported Addresses

First of all, I’m sorry that I can only use external files for the several files included in this thread, because if they are all posted here, the thread will be too large to be published. And I use Google Cloud Disk to share external files cuz my github account has been blocked.

Clusters: 90, evm wallets: 5406, Here they are:

EVM-wallets-csv

and aptos wallets: 5162, Here they are (I don’t know if the aptos wallet is also in this airdrop range, so I provide it as well):

Aptos-wallets-csv

Description

All addresses in this report are generated cross-chain between EVM and APTOS. For example, A of polygon cross-chain to B of Aptos, and then B of Aptos cross-chain to C of Arbitrum, then A/B/ C forms a cluster, and so on.

For all charts below, the red dots are evm wallets that may be eligible for the next airdrop, the blue dots are aptos wallets that are bridged to/from, and the black dots are evm wallets that are connected to aptos wallets but are not in the reporting list .

please note in particular that these Black spots are actually part of the sybil cluster, but they are not within the scope of this report because they may have been discovered or the indicators failed to meet the set standards

I have filtered the evm wallet reported this time in advance. The filtering rules are: 1. layerzero transactions count >=5; 2. layerzero bridge amount($) >= 20; 3. Not in the published list of 803,093.

all thess wallets is clutsters, pls look at the relationship as below:

Special reminder, some of the pictures below are very dense, please be careful if you have trypophobia.

cluster 1

cluster 2

cluster 3

cluster 4

cluster 5

cluster 6

cluster 7

cluster 8

cluster 9

cluster 10

cluster 11

cluster 12

cluster 13

cluster 14

cluster 15

cluster 16

cluster 17

cluster 18

cluster 19

cluster 20

cluster 21

cluster 22

cluster 23

cluster 24

cluster 25

cluster 26

cluster 27

cluster 28

cluster 29

cluster 30

cluster 31

cluster 32

cluster 33

cluster 34

cluster 35

cluster 36

cluster 37

cluster 38

cluster 39

cluster 40

cluster 41

cluster 42

cluster 43

cluster 44

cluster 45

cluster 46

cluster 47

cluster 48

cluster 49

cluster 50

cluster 51

cluster 52

cluster 53

cluster 54

cluster 55

cluster 56

cluster 57

cluster 58

cluster 59

cluster 60

cluster 61

cluster 62

cluster 63

cluster 64

cluster 65

cluster 66

cluster 67

cluster 68

cluster 69

cluster 70

cluster 71

cluster 72

cluster 73

cluster 74

cluster 75

cluster 76

cluster 77

cluster 78

cluster 79

cluster 80

cluster 81

cluster 82

cluster 83

cluster 84

cluster 85

cluster 86

cluster 87

cluster 88

cluster 89

cluster 90

I will provide detailed TX of the interaction between these wallets (including evm wallet and aptos wallet) below:

detail tx here, This csv file contains the following columns: cluster number, cluster size, TX hash, source address, target address, source chain, target chain. We can randomly select TX from this csv for verification,it looks like:

Let us open this csv and take a look at any TX, for example, hash: 0x64448c0ee359125d8d22d7ef15398e4654e0e2ee2c4cf01f6fac2e3ada3258e1,this is the cross-chain from arbitrum to aptos:

we can see the following picture in layerzeroscan:

Then, the following image can be seen on the arbitrum blockchain browser:

Finally, the following picture can be seen on the aptos blockchain browser:

Let’s look at another one. The hash is: 0x73b31b58811ffde2ff0432a4f8812d1fdab7f6d3e7d63e357bd17896fc16e52f. This is the cross-chain from aptos to polygon:

Then, you can see the following picture on the aptos blockchain browser:

Finally, the following image can be seen on the polygon blockchain browser:

The relationship between all these wallets is found through graph calculation, which leads to the results we have seen so far.

Detailed Methodology & Walkthrough
  • [1] I noticed on the blockchain that some Aptos wallets have different incoming and outgoing addresses when transferring to EVM wallet addresses via L0
  • [2] I collected all records of cross-chain transfers to Aptos from several chains including Ethereum, BNB Chain, Avalanche, Polygon, Arbitrum, Optimism, and Base, as well as transactions from Aptos to various EVM-like chains.

I used dune to got there data,code here :

op to aptos dune sql , avax to aptos dune sql , ethereum to aptos dune sql , polygon to aptos dune sql , bsc to aptos dune sql , arbitrum to aptos dune sql

aptos to evm dune sql

  • [3] I conducted a graphical cluster analysis of these transactions and discovered that many wallets use Aptos wallets as intermediaries. In the diagram, the red dots represent EVM addresses, while the blue dots denote Aptos addresses.

simple code as below:

#Here load all the wallet addresses that I follow. I have already done the processing before. First, I filtered out the wallet addresses with tx>5 and amount>20U, then removed 803,093 suspected sybil addresses, and then got the watch list.

addr_list = load_addrs_info()

#create graph from jsons,json file from dune, The constructed cluster is a directed graph, with the wallet as a node and each tx as an edge.

G = build_directed_graph(json_list)

#Because it is a directed graph, weak correlation is used to connect it.

clusters = [c for c in sorted(nx.weakly_connected_components(H), key=len, reverse=True) if len(c) >= min_cluster_size]

final_clusters = []


for index,cluster in enumerate(clusters):

subgraph = G.subgraph(cluster).copy() # Create a copy of the subgraph

focus_nodes = [node for node in subgraph if node in addrs] #Filter the following wallets in the cluster

subgraph = remove_isolated_non_focus_links(subgraph, focus_nodes) #Delete some nodes that don’t contribute much to the results

if focus_count >= min_cluster_size: #Check whether the minimum number of nodes of interest is met,here Min_cluster_size=20

split_clusters = split_cluster_if_needed(subgraph, focus_nodes) #Check and split the cluster (if necessary)

for split_cluster in split_clusters:

final_cluster_graph = G.subgraph(split_cluster).copy()

final_clusters.append(final_cluster_graph)

else:

logger.info(f"Cluster {index} has {focus_count} focus nodes,skipping...")

for index,cluster in enumerate(final_clusters):

subgraph = G.subgraph(cluster)

eligible_wallets = [node for node in subgraph if node in addrs]

draw_html(subgraph, eligible_wallets, filename, line_type=0) #Save the cluster as an html file

save_cluster_to_file(G, cluster, filename) #Save the edges within the cluster as a csv file


  • [4] The transactions from these wallets were initiated by the wallet owners themselves, both on EVM-like chains and on Aptos. I believe this sufficiently demonstrates that they are part of a Sybil cluster.
Reward Address (If Eligible)

0x000002F8611c59a4d3ee714AD579171c55B00D34

I’m TjdnskEhdksk of github,Unfortunately, the issue I posted on github can no longer be seen.(issue #3360,#3382,#3442,#3515,#3564,#3591,#3647,#3709,#3780,#3990,#4105,#4185,#4264 and #3904)

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Danniel

3 days ago

I think I need to update the external link. I used Google Drive originally, but I updated it to git address (which is more convenient). The contents of Google file and git file are consistent.

EVM-wallets-list

Aptos-wallets-list

detail tx

eth2aptos dune sql

aptos2evm dune sql

Finally, because there are too many wallets to paste at once, I want to paste the top 300 addresses of EVM wallets

0x112fd63249dde0dccf9a3b6202a2f66b5edbf915
0xeb400674f1934e85d35310b6a16c73ce7e2e097e
0xe41a437562f46c3436f9f312937a34a0e8dcb70f
0x461b2acb1fe7e94069f85e7282b390dd87d0dc5a
0x2ca12a0755d49a68e4720afeb428e98340ffe058
0xa98d90db29c73ca2380758ae4c60e0e65e28a888
0x17451710f5bc0e012827b19b0949ceb5d8e0f7c0
0xe66192882c1574507953dc8cfae7d7ef9ddc797e
0xb0b2831fbe9a3a41bb90b8886119ff62b114e6c4
0x2d991110ffd81bbf9084ce5ceedba66cd490af31
0xd95711114796d142c7107f4fc984487856038e7b
0x8b8729a8400b7cdeb6314762c54c2cf6bce52ab4
0x3b8ece17d39a26c9ff67cedafa6ae340ff1e51fa
0xc4d22074699a571281f1587b24d41f1b3f61e9bf
0x9e9c0f6857d51474130ce11da6328fff6f0603ab
0x5d67f47922d096f76b2ca94e71adf87ddd747ddb
0x4ac34a242aa2866b9151a38d18cd4fb396dd7dd2
0x36b2a792ba80e75edb8b56acaacd29d81a6e7550
0x82b129a8bdfc7259485960ebb0e1702c88b96831
0xe5a592287d786c5ea99123f056ee7da922d62c70
0x35028ee21a43f62553bfff5f64eb5c6497e376a7
0x01448709426d8623bf29267091f9d664b1bd9d73
0xae07422545bf09e8a898d356035aafb254d3da28
0x43dd98ea0b6487a4dc6b8b1d50c1946074b7fc17
0x66de7cc6f5fe6374da5cc34958d9d170c098f913
0x9b9b198d9bed7ffb7ee9203b4a074f6831ff4fd2
0xbb1fb5f5a33c3d2fe084df7ee63d35247ab631bd
0xc542b4ec40207fa48ac04533f5000a632836165d
0x4ccef3ff00ed64509c136454ae3e175d561ad456
0x5709b3aabde465798383f9d0f87d158b106dc5a8
0x4bda35410e7511d86ae8c4d11b02387eea8b3d13
0xa18702983d40092f61bfe949e5e269e5dec2a6fc
0x84beb6cbd6d3f3ccf8025e446f667b22d62f7769
0x3efb0c319e50dc0d972e6708cf2196b1db1d685e
0x033b32bbcb86fc3cdbb88f8d9daffe528e873943
0x486be265449fb7319af81c99ec9707423ad12fc9
0x11774d79ed95059deb87dce466a2f20476541a64
0xfb59470cbe2b28a2bd82111c13db470f7fe83fc0
0x4a9d766ad2e11039f8c6c97fab886807060927ed
0xa8cf069e842d671aa1c2096b714ea9d70527d62b
0xa06d4ecf79144fd0f3fdc6ccbb36af26702df23d
0xe08deb92e022717839e80c8cbec0727335dc7ae1
0x65914792452ba3d9f5b24e5526e01bc046577841
0xe38561c2c220d5ce9580b5a3d8f57d504a21197c
0xeb7717afe9b2416489e02f4885bbdd0a745f9f36
0x21a937f024787b7c1794d0c53dd35f36ec91f718
0xc9a8d33f952ada95da2652bab477a9863a36696d
0xbc1402ff3b20e65fe6f8d38c1d9031bb3ac58658
0xbd64399a9943a8697bec18d3d90fe76b54814efe
0x29dbe423faafe1c54f86747be6b2c44a384f76c9
0xdde41272c07224c50676faae1d0e550f6e9bf91f
0x7c7ae5c481960e5dea78991c3dbe1dfb35014cb7
0x07fb1be1a6766df5737a284094152f5ab20676aa
0xcf3e4b3b32737bd33963b2e33f628cec2b5ea1c7
0x22d90a0a5be591ee6fb278b87b1e4f3cf5b96ef6
0x13e5a69b5fd7e15b861e2e9126967b6acb3ee808
0xae101108569ca02a3ea166e11b042bb45b51322d
0xcf4842e47da5de35e7f890e72d7a83fdfc0997ea
0xadeaa3b9f123b92ba0b5f6f13ef7b91e3ee3def4
0xc16887cac1428aece6a44f9af9add1f61ea87c6c
0xa815313d23c914fc41738abf26c2631df53c1fc8
0x91f40037e8ecc55c08acb2cf6a8de2e9700fddb2
0x23da44f17d19baf664a4870ffc43697ce6ec8806
0x53cc2f776b42d6f333657618cf96ba4fc165073e
0x4419b10642f24852b3093b20d6286a56e2336ee9
0xedfa550642e6c768c59f460cc2f613b20cc41078
0xd035158950024a2f0e337628898e883417a7a0d0
0x336539e40ce80645c83aa15183d8d14eb590e8a2
0x9074e123926e9e05f3497fdae050a37df7fecc9f
0xb20c9a292dc6914899f1ec5f2a4950b8595809fa
0x328723e8440357eec1894329c4a5d988aa0807d8
0xe14d892e96c653e066bff037af93a6507b4cbffe
0x639522fe64a339bd913875ef79d39971295614b0
0x652ec4aed36397db3206d624ef2c623696ccf694
0x01531590d5da4b8a28fcccca499f35cca517c307
0x8d65af590dc056a9219682cfdb1041699ae29951
0x3cdcfea36653a75b07a68e42355b87f88562e5dc
0xd2bc2287449c1a7a96451f018d0ebf0179b424cc
0xda123320b1f61d18cc24b539c76e6ab6b711346f
0x09165ace351f732d697a378b5761b81df7e2f334
0xcba1e6c0bc056c908b7f57f9ce5bebac08de4fb5
0x0fd19d1cc12093395a4d12dddf8ec91e24f4b870
0xd2cb5c06c2059108d84f64d7543951c1fb78618d
0xb405bf7c53a9332156f72befe4fc857d56460f1e
0xdd54b8ab5922313f9f67b594f3895ae4949df596
0x02cb58518c859bcadb7aee9e0e9e04144970c992
0x49ec41b0be196529416e30ea1f608c6b6b6ea848
0xed5bd7dfd0ec674094e35b2c8c07558b36163aa6
0x0b3744dc0e7ca4be62776d59008753e327aefb91
0xcf071191f0cf062987166f6834a4e1d9fad85681
0x1003f7c841b78059ef48ad35c74d23bbfbdfb81b
0x120957f71c61dea368eaf54a76b9e0695206bac1
0x495cbb1394745950231dbd9f440e662f9be40f04
0x0f8290d13e3e292ef824ef019fa33eac907f98fb
0x9b824e697656bb47ffa3dfe1ffa7c1ced25880c4
0xeeb484ea269c3d4baa1d95f274ac4ac6bbb801ab
0xeea4bba11e413c68b29cdecca56bc14bcb633842
0x1edb4b5cca6e6110f17e85b33bbcf72454cda39b
0x4093e4446f31889b5cef1e05efce1ff238bb0ee8
0x98cc995a85afb7a9fa4e4a978d54af3dce57e6f8
0x4ef12f331a45d914fe616d51e13828cb82b49da8
0xff52b674f325f8f48ea4316e914b022a2fdbcd4a
0x59d6a4e418ddb6f9cc1808bada84f944d02fa51d
0x773dbd285831ed170857adec5a733d13c8d5c9d8
0xb755f823538e7db52792681a8ce0f20f6ea38e2f
0x862a7dbc564c4658db5d74c6462dd5dc5e065f77
0x5086788638ab82bbca16faa526103c72a38ea116
0x95a120ed7be45179ff748f893afe264d00349372
0xaae6f0ac99116da7bd9b9e4853d523c031d9f661
0x0fef6208560b8c073b4e679db52b9375724e84f4
0x1c446f98222bffc81aaf35f1c8671e096e96b316
0x46ae3560a8ece66476e202f43a32ac08728d047b
0xae5dd8adc417e8116711f5a84f718e5acf61999f
0x468e52bb6fd99a8772111b8da665a9eb1284c608
0x1b8a949b6f440f6df588b781ad678568bb63d6d4
0x2e5c68c5504c740a49f665303734b6a0faaaf69d
0xee05c5fe9f7725cfdf79f3d6bf6cc5008fbdb4a0
0xeb6a51e4f28091d284df7a827523cb04edb577db
0xabc41f23536a72f6453fd37e43e64ced70238a5a
0x510e7c3d9c53f5c6354c2e93e590bc99594242bd
0x7418ed0fd4487fceedfa177c265376e9b426f4b3
0x80797871de0852cf76acb8554a9c5e657afa1e37
0xbef4b6a02739c3ccab22fa251664e857f94c4826
0x0ae7d83ea538e334e4a0358d4355fc0b380c8b20
0x25abf40340be9b0c208c92e7a69ad1c763d62647
0x5ce335dc66b28c3e5b3ca672d6f499f87ecd1319
0x273bfe0344bb71c92ad2ece561ba53db93896d22
0xebee5930c1df313cddfc9879c9c72006790aefde
0x9dd3fea9b2b22c45c2c50cb5532987a3fd243741
0x3d693025f3216bbd48e037bd1b77ff2bc4f0b87a
0x65c0e2316c5b97235081a4e832bd1b5d5bfac410
0x086cf07dd897bd5aa31942b1064d8c2f02ac756f
0xe64559aa3e687fd1f8b0a836f8496aaa838bf935
0x122591eb8d9a63adfd1471ce40a635c83a5e5518
0xabec2e681c18f0b4bcf141173d9da8194494f4d8
0x3c16a4d59804b28145f620841f7b1246e1784fe2
0xbf3fb5c96bbaef9f0da2ca3c03fbfc73ad50512f
0x684e5bd57547a26d1e0531cd991b97c077feec47
0xd237f03bb8b3982db0c87c22ce84f36927a57872
0xfa9e50cfdfb31c3908b495f51ca4bc97d65b9b44
0x6d05f9cc8174b20374d7ace8fd6f06a66e2f3ff0
0xf30f442073f1da4aad9f0c857c4ac09f8d2a3ff8
0xe531c667f9627059d427d47aed7b1b7b79b0a42f
0xf2ac87c985efd0041f6838dc4cb55c2bf77779cb
0x1c5802273cf1e4d246284b1a359b86ce077f8de9
0x4b22df5e7d2e6690e962cededf54b841965735c5
0xb596752545d3ebaee38fdac8472f8f3663ff7079
0x5f679ec3c04c2f6678f381fe75958cdc802c92ca
0x3a7aa35067b187367bbbf0b265f32ec14180300d
0x9272735be4c04d9533067cdf617767adcc17b291
0xaca6c73161c7a24e8945d765e5bd4bf75f0b8629
0x15a5e803b28de2a1cf77f60e5af8c60f2ba43bb6
0x292456f9b5272924b58063443e06ca61d75e5f06
0x601adacbf83164c48ad0fa6e5de7987cb4b5fa5f
0xd09199a5e3e0fbfb4156546665f5a6c342c44b53
0x0c6f3bc7fa7ae738840eb20fef9a0342d8fc1ca4
0x5bc041a6b133428ce74f4bb237e83568c118a464
0x30d18486d3d2aac8ba56ca1e3f456a211dc41719
0x3a270f238aea3076b492156b4928b43459941c54
0x35080d9d93998b1b200a8c8c86dc9fe87cf87490
0x43e5f69c911f6e4445eb93705b97c4de18e187e1
0x39d3cb1e9734abde9759b0cfdf2dbf7516f055f6
0xda289d54263422826807c695fe13f9437fba84ff
0x73ca914124434a3aaa718fb6afcafe9a49fa0977
0x40d8f052b2b54001620280514c9c6ed8056b2d30
0xc0cdfbbcd2c8b8617539d2a7bbfd493314e14d1f
0xcf89493b781c64e611066f987cbb2a6abcf8394c
0xf4c2b55c5da3d9cb4424c9ee79b4b6bf891e5dcd
0xaba8d19b1c17230136406848d2e42ba2ed2ddc74
0x49c600e770370f4f8037b5fb6279f91b3f790051
0x0582ca62c4b807f3788142dab35c15e7199e3b6d
0xfbfec9950fbea300672de84d071fd0e0329d2e3b
0x9d1f2194dbb27241e45200e0bf48547baacfc426
0x9df3818984fda4d35ab414ef76ba3ed7c97bf3c8
0xffd30ebd2f3bc072d484ca58ed760292da0e4cda
0x444007235c591493d6c322fbda0f322b95b3543b
0xcef835535defd3e8f6d9f1c3c99c68e623ad0208
0x9d6a0e08fe4ccea08dd5eb113eb06db7fc4c1c19
0x5b88297c4d3cc8f1dd4ae1fa28ebc1c30aa108eb
0x4fd0f7f90f01edcfd083420bf45acc3b62a28756
0x53218d53bada80cf77d15f2f40587b806ed1923f
0x3f47ec3c4bbef752946ea2f85e5ce34192863303
0x90fcc4d662dc08554f93f042c5c041c8a92f447c
0x17d075f9a0dade80ca5317afad70783af18311b5
0x1769c4392bd972dc4525503d9eb0621665104554
0x996569a8d94882b629d9b86d787c3897942bb714
0x81627e5763c13adae4dee28d50cb104e3b623322
0x3e27d96bf4ae0a2d6e027032fdd7c4635c5b097e
0xf6042659683f01894552158ef2df27308291aff6
0x1b58ccaffb290e64ad4b661e6d488e4b019796bd
0x81431336bc01eeb96320541130fcc33ea0a3ec08
0xfd1a65004e148a8bb94f62f0ad9301f5e20aa989
0xbac0e4545143f6c2f826952bf5132072504283af
0x7ddaceea0c46d33203fdd002a923255634e9a1e6
0x9099694d7a74004c55dc9262f9870adf0812e09f
0x9c11182a5067cad772f3a53773222f2b987ad3ac
0x0c2d312d35474a4757017f571f4a4f1155ceeb3d
0x061a7e08fe30e9b0174afea9f1a2f2c81259f4c9
0xf53aba30bd18b33728e4da7879ebb208e858985d
0x28d83489696679962de61b96d393fb5e91852b72
0xeeaf0b1ae160506d91fa78637f723f222fcb3629
0x5489a7a7af5e0181b7ed2824dd058bf2f1bb7493
0xed4337055fd4407b426a818fd6790d0f1ed66d6b
0xd853f93e4ba71c17769568f77c2c62750c42bb01
0xa994554b1b11b8fb3bfd7acc25f4799e35887808
0x6c4eb85dcbd0588a3f4cdda59d08c9b5aa79996f
0x208abe2fc7a61643f5921c4b0e68f9e908ad85af
0x41ed7dbf4d44ecf97d399623d414334cf6b037e6
0x78a4b5ab91fd46270e789f9cb40bac6e7874e522
0xa3393f4321414b8dfcffe6e64f77d75b2da9093a
0x046f6015ee70afe623ccf3e75eb6a5b8472343b4
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Thank you for your patience in reading