What is Sniping

Introduction

In the evolving landscape of blockchain technology, ensuring transaction transparency and security is paramount. A prevalent tactic known as "sniping" enables some users to get a major advantage on a token launch. Recognizing the need to identify and mitigate such practices, Webacy has introduced a robust Sniper Detection feature for Solana.

What is Sniping?

Sniping refers to traders who attempt to buy large portions of a token's supply immediately after it is minted, often using automated tools or bots to gain an advantage. Traders that lack the sophistication of sniping can be put at a major disadvantage if a token is heavily sniped. There is also an additional financial risk when a major portion of a token is controlled by snipers, who may be solely involved for financial gain and could dump when the price is right. It can also be misused to manipulate token distribution or conceal malicious activities.

🚧
Why Snipe?
Since a token's financial gains are most opportunistic in the earliest moments of a launch, successful sniping enables a buyer to get a token when the price is extremely low.

How Webacy's Sniper Detection Works

Webacy's Sniper detection feature analyzes transaction patterns and trading activity in real-time to identify potential sniper activities. Our sniper detection analyzes time proximity to mint, buying patterns, purchase amounts, automated trading behavior, front-running, and more. The sniper detection feature also calculates a confidence score (0-100) that represents the likelihood of sniper activity based on these factors.

Considerations

While Webacy's Sniper Detection feature is designed to identify sniper activities on a token, it's important to note that not all detected snipes are indicative of malicious intent. For example, high-demand token launches may result in multiple unrelated wallets transacting within the same time slot. Therefore, it's crucial to analyze the context of the token and consider additional factors before drawing conclusions.

Also note that this feature has been released for Solana only. If you'd like to request this analysis on other chains, please get in touch.

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❗️
Endpoint Specifics
Sniper analysis is currently only available through the Holder Analysis endpoint. Visit the Holder Analysis endpoint page for API limitations, details, and expectations.

👍
Try these addresses!
EvSMwAQYT18skxseSZaooXV7RzNbTTVQFrYEux19pump
13fUms9P4BrP91N4U9sdNoJhCceamrQhZ6WtzW9Jpump

Example Data Return

📘
Important Field
Many customers start by implementing the bundled_percentage_supply_bought field. This displays the percentage of the initially acquired supply was purchased in a bundled scheme.

"sniper_analysis": {
        "sniper_addresses": [
            "7EziKQAVfPTQFPjELg2jREHgYB6q3eZJkh2HdXWhPsLh",
            "8UazMc3hG7BLtsWpcWUPh4XB78xYkVQWcfRT64xp3dD7"
        ],
        "sniper_count": 2,
        "sniper_total_percentage": 9.56,
        "block_range_analysis": [
            {
                "block_hash": "DYiXPLTP7cvAf612Zw19vtpBNxxTdY7S5dJJBxGbRjxs",
                "timestamp": "2025-04-03T06:39:03.000Z",
                "buy_count": 1,
                "block_number": 1,
                "addresses": [
                    "J16iaWtJazWEcXByJuVe1eeAey3KeiwTD8S8Xpdzppjm"
                ],
                "supply_percentage": 0.11
            },
            {
                "block_hash": "36kajGL16hQRvzoa8nq9Rd5Ge618eA2Nb1DjCuGXmcHV",
                "timestamp": "2025-04-03T06:39:05.000Z",
                "buy_count": 1,
                "block_number": 2,
                "addresses": [
                    "BzTi7n6T9EEseqcswMmLQfD9McXP7fUAbJGgWddTPfBz"
                ],
                "supply_percentage": 0.03
            },
            {
                "block_hash": "6T2yYxr1Awq4tHddm2WmuMGy2WhA6uXKoM3P74L92FfP",
                "timestamp": "2025-04-03T06:39:05.000Z",
                "buy_count": 1,
                "block_number": 3,
                "addresses": [
                    "9xBPRyX16em6fNuhts577rPUZe13KN5Enyfs8gH4bWaP"
                ],
                "supply_percentage": 0.02
            }
        ],
        "time_since_mint_analysis": [
            {
                "time_range_seconds": 10,
                "buy_count": 4,
                "addresses": [
                    "J16iaWtJazWEcXByJuVe1eeAey3KeiwTD8S8Xpdzppjm",
                    "BzTi7n6T9EEseqcswMmLQfD9McXP7fUAbJGgWddTPfBz",
                    "9xBPRyX16em6fNuhts577rPUZe13KN5Enyfs8gH4bWaP",
                    "77X6y9iFBumCEbQRMN3RBGfRPfi6cn1sNQ4L836wmarm"
                ],
                "supply_percentage": 0.18
            },
            {
                "time_range_seconds": 30,
                "buy_count": 6,
                "addresses": [
                    "J16iaWtJazWEcXByJuVe1eeAey3KeiwTD8S8Xpdzppjm",
                    "BzTi7n6T9EEseqcswMmLQfD9McXP7fUAbJGgWddTPfBz",
                    "9xBPRyX16em6fNuhts577rPUZe13KN5Enyfs8gH4bWaP",
                    "77X6y9iFBumCEbQRMN3RBGfRPfi6cn1sNQ4L836wmarm",
                    "7EziKQAVfPTQFPjELg2jREHgYB6q3eZJkh2HdXWhPsLh",
                    "8UazMc3hG7BLtsWpcWUPh4XB78xYkVQWcfRT64xp3dD7"
                ],
                "supply_percentage": 9.74
            },
            {
                "time_range_seconds": 60,
                "buy_count": 8,
                "addresses": [
                    "J16iaWtJazWEcXByJuVe1eeAey3KeiwTD8S8Xpdzppjm",
                    "BzTi7n6T9EEseqcswMmLQfD9McXP7fUAbJGgWddTPfBz",
                    "9xBPRyX16em6fNuhts577rPUZe13KN5Enyfs8gH4bWaP",
                    "77X6y9iFBumCEbQRMN3RBGfRPfi6cn1sNQ4L836wmarm",
                    "7EziKQAVfPTQFPjELg2jREHgYB6q3eZJkh2HdXWhPsLh",
                    "8UazMc3hG7BLtsWpcWUPh4XB78xYkVQWcfRT64xp3dD7",
                    "ETDEBCgUuK111MgSkhKFBx8Sp7ZFDWW3eSmKofuuPiCj",
                    "H16HsHZgtLR3rgFtPd3XJo2cp9z9GRPXUYmmW76mATTb"
                ],
                "supply_percentage": 10
            },
            {
                "time_range_seconds": 300,
                "buy_count": 49,
                "addresses": [
                    "J16iaWtJazWEcXByJuVe1eeAey3KeiwTD8S8Xpdzppjm",
                    "BzTi7n6T9EEseqcswMmLQfD9McXP7fUAbJGgWddTPfBz",
                    "9xBPRyX16em6fNuhts577rPUZe13KN5Enyfs8gH4bWaP",
                    "77X6y9iFBumCEbQRMN3RBGfRPfi6cn1sNQ4L836wmarm",
                    "7EziKQAVfPTQFPjELg2jREHgYB6q3eZJkh2HdXWhPsLh",
                    "8UazMc3hG7BLtsWpcWUPh4XB78xYkVQWcfRT64xp3dD7",
                    "ETDEBCgUuK111MgSkhKFBx8Sp7ZFDWW3eSmKofuuPiCj",
                    "H16HsHZgtLR3rgFtPd3XJo2cp9z9GRPXUYmmW76mATTb",
                    "J5cNqWPo6cv8BfPdd8tTpu2gwAVnrHnaAxXoYc5A7ncG",
                    "5MQYH9mLMrvUDczsp2FGti8xv2GBZaWeJQQHoQoWmJSj",
                    "vNkGP6fLgfQ9uRzpK6NtcZ8RnVnBwJFNUqP8KJZ94QW",
                    "pYtYY2JitBETru3vhWjAn1SWjWoZkbBgiq7GVh9ibcV",
                    "2i8QndpSRDJUvJjNM9wttvbEKHPf6tEGgsXmNxVc5saY",
                    "6EPbr4awvtDspFp274bGjXf68UjH1eydhWMcRisMxiPm",
                    "AGiSdEqhifFFEvtijtUBQneF1SpUwukFKFu81ckmfpja",
                    "AGqLpggf2yUXQ7UA3kngJS4o6qFywASJ9mn3HUsCmoct",
                    "AGdmgSvVoC3h8VoSsuAX6DcEB3LJmssSsLLc7cjhGzuT",
                    "2QpQqQExhsTCaXmFUQzH13jcvRd1rkTrk9G4LPijaHFj",
                    "GChjA9fKjL81yDkt34BcfCjkksDg6sGQcz4MJw4KiWqo",
                    "33GtNAQzmdq4jELpHxXYqW3vDy7fux89zevVU4hP7BTX",
                    "GtcHd1edpYmwB3j52BbZHg6uwYxP2ZKcSfVsN1v6f1b6",
                    "HU4ZgrZoVa2HxDmQhszcyQJj9DejibHMXjAriZjagso4",
                    "CRcAZ6vgNYBJUsoZQrd3TLbQVguSLiCcf5pASSs36UcL",
                    "CdEVwh1kFBfpYrPTC4EtWY4X9ZRArTo61wZ6r1SWM2Dp",
                    "PEaaf8rJJTaVQKwxNKSw8SYWBMGhnpNAubKJVtHHgbP",
                    "AWNJ5HuNUaQX8whB84egGWWmtPE59G1WfCbvdpDUGVfp",
                    "CpHV6Ux4PR3X571GWysJqfEZ54YHriKdLan1wQbQGYBm",
                    "74CfQdUFGvhRUQ5GR4dHpmi4NXqMhwLs3KuCUHMKyCXC",
                    "C1twpWx3vBpWDrXXvFbLd4zFCALRfhFdKrebNjeza7p3",
                    "Fr78FexaX9XkszsUUHJFFKSQgpi7m1t9X5uwXQyJRoS6",
                    "FLAKeimo8zqdvVoJJhaxJu9yAMB3cgYbY8raTgHQ9XVU",
                    "5H2oQhBqqXXdTc7u7usR1woL5XJ1zGuiCJqQe3NKAyAT",
                    "8mY6HVDFNdZHV9gPAQESTGDAFpqq8qcwt6D25Kvd4XKn",
                    "BmDDuGCBWgPH3muuzvyvSDwzBdCZ2AjTnKVFH8fXSzzJ",
                    "4FuhtiBu8rKq31CRKdwwBcSTqoPxwwcEp1274hP7AUoW",
                    "DXdyKDmdefHAb9D45A2EWTs9AiaCCJKWmE9AWi78gKyM",
                    "AGyuzEzA6Fd9AMRW7DU7jy3CePwM2yLLiRh4usivEGyE",
                    "62rxA3WZSTBEFb5dM2rCBaQzyYKuMvLJfPVWtex1LcPT",
                    "",
                    "TDJzAcsV8Ck2fEbALRb8efP7uA2oxy96XjmVV7wnio3",
                    "EEEEEc4xfLKqnRBRq4wsQVJu9HaN6TuVonx54RGy4WNN",
                    "HR574nkdga5juXFeTtu2Rm9ao8iQs6TXCsL9DKZiTHWC",
                    "9UDUGmptuY2bvyEs51CFkoRCMBEhPj7iSgzoPjzH1D4R",
                    "EPp5ovWE593zfyrXVv7X2MHQAvGa22wovzfLUFRt9pno",
                    "5F9EQBrQHcDvFPVSvx5utdAVHpeu9iQoJ2Srgui5rSZD",
                    "2CHdAE9p4u2ZWcsp1WyhE8VYjPWTmuTPq89aEXHRUFm9",
                    "waTeRoKz7KrhSMMBqEmdgSxQejKVSU4msEXUrwMNBF9",
                    "CC1Vo9y9183zoiyckDwmwwNYhTB8vfyP7UGjZUR1wX4m"
                ],
                "supply_percentage": 60.72
            },
            {
                "time_range_seconds": 600,
                "buy_count": 60,
                "addresses": [
                    "J16iaWtJazWEcXByJuVe1eeAey3KeiwTD8S8Xpdzppjm",
                    "BzTi7n6T9EEseqcswMmLQfD9McXP7fUAbJGgWddTPfBz",
                    "9xBPRyX16em6fNuhts577rPUZe13KN5Enyfs8gH4bWaP",
                    "77X6y9iFBumCEbQRMN3RBGfRPfi6cn1sNQ4L836wmarm",
                    "7EziKQAVfPTQFPjELg2jREHgYB6q3eZJkh2HdXWhPsLh",
                    "8UazMc3hG7BLtsWpcWUPh4XB78xYkVQWcfRT64xp3dD7",
                    "ETDEBCgUuK111MgSkhKFBx8Sp7ZFDWW3eSmKofuuPiCj",
                    "H16HsHZgtLR3rgFtPd3XJo2cp9z9GRPXUYmmW76mATTb",
                    "J5cNqWPo6cv8BfPdd8tTpu2gwAVnrHnaAxXoYc5A7ncG",
                    "5MQYH9mLMrvUDczsp2FGti8xv2GBZaWeJQQHoQoWmJSj",
                    "vNkGP6fLgfQ9uRzpK6NtcZ8RnVnBwJFNUqP8KJZ94QW",
                    "pYtYY2JitBETru3vhWjAn1SWjWoZkbBgiq7GVh9ibcV",
                    "2i8QndpSRDJUvJjNM9wttvbEKHPf6tEGgsXmNxVc5saY",
                    "6EPbr4awvtDspFp274bGjXf68UjH1eydhWMcRisMxiPm",
                    "AGiSdEqhifFFEvtijtUBQneF1SpUwukFKFu81ckmfpja",
                    "AGqLpggf2yUXQ7UA3kngJS4o6qFywASJ9mn3HUsCmoct",
                    "AGdmgSvVoC3h8VoSsuAX6DcEB3LJmssSsLLc7cjhGzuT",
                    "2QpQqQExhsTCaXmFUQzH13jcvRd1rkTrk9G4LPijaHFj",
                    "GChjA9fKjL81yDkt34BcfCjkksDg6sGQcz4MJw4KiWqo",
                    "33GtNAQzmdq4jELpHxXYqW3vDy7fux89zevVU4hP7BTX",
                    "GtcHd1edpYmwB3j52BbZHg6uwYxP2ZKcSfVsN1v6f1b6",
                    "HU4ZgrZoVa2HxDmQhszcyQJj9DejibHMXjAriZjagso4",
                    "CRcAZ6vgNYBJUsoZQrd3TLbQVguSLiCcf5pASSs36UcL",
                    "CdEVwh1kFBfpYrPTC4EtWY4X9ZRArTo61wZ6r1SWM2Dp",
                    "PEaaf8rJJTaVQKwxNKSw8SYWBMGhnpNAubKJVtHHgbP",
                    "AWNJ5HuNUaQX8whB84egGWWmtPE59G1WfCbvdpDUGVfp",
                    "CpHV6Ux4PR3X571GWysJqfEZ54YHriKdLan1wQbQGYBm",
                    "74CfQdUFGvhRUQ5GR4dHpmi4NXqMhwLs3KuCUHMKyCXC",
                    "C1twpWx3vBpWDrXXvFbLd4zFCALRfhFdKrebNjeza7p3",
                    "Fr78FexaX9XkszsUUHJFFKSQgpi7m1t9X5uwXQyJRoS6",
                    "FLAKeimo8zqdvVoJJhaxJu9yAMB3cgYbY8raTgHQ9XVU",
                    "5H2oQhBqqXXdTc7u7usR1woL5XJ1zGuiCJqQe3NKAyAT",
                    "8mY6HVDFNdZHV9gPAQESTGDAFpqq8qcwt6D25Kvd4XKn",
                    "BmDDuGCBWgPH3muuzvyvSDwzBdCZ2AjTnKVFH8fXSzzJ",
                    "4FuhtiBu8rKq31CRKdwwBcSTqoPxwwcEp1274hP7AUoW",
                    "DXdyKDmdefHAb9D45A2EWTs9AiaCCJKWmE9AWi78gKyM",
                    "AGyuzEzA6Fd9AMRW7DU7jy3CePwM2yLLiRh4usivEGyE",
                    "62rxA3WZSTBEFb5dM2rCBaQzyYKuMvLJfPVWtex1LcPT",
                    "",
                    "TDJzAcsV8Ck2fEbALRb8efP7uA2oxy96XjmVV7wnio3",
                    "EEEEEc4xfLKqnRBRq4wsQVJu9HaN6TuVonx54RGy4WNN",
                    "HR574nkdga5juXFeTtu2Rm9ao8iQs6TXCsL9DKZiTHWC",
                    "9UDUGmptuY2bvyEs51CFkoRCMBEhPj7iSgzoPjzH1D4R",
                    "EPp5ovWE593zfyrXVv7X2MHQAvGa22wovzfLUFRt9pno",
                    "5F9EQBrQHcDvFPVSvx5utdAVHpeu9iQoJ2Srgui5rSZD",
                    "2CHdAE9p4u2ZWcsp1WyhE8VYjPWTmuTPq89aEXHRUFm9",
                    "waTeRoKz7KrhSMMBqEmdgSxQejKVSU4msEXUrwMNBF9",
                    "CC1Vo9y9183zoiyckDwmwwNYhTB8vfyP7UGjZUR1wX4m",
                    "DkkyAa5wAUwwSQTRrcWZZW8nPaknqCkC7SHSrKnLksnp",
                    "4wumkPWPkK3hqGmnQdjpk5Abcc91dsUsofoi99KzGEe6",
                    "GgYS4Y2ppkVuqp32QjVSDGsoZLjTWmHLPrFTYJ49Y7Zf",
                    "GSwomz9JBhL5jZmmFjJoT3YQEgbV99JMXgWFvxmCyhfp",
                    "4Fx3b67vYhkx4xLjTSU5KefMBLwcBMpSGEJcwxyvfz9r",
                    "125Pu2xKqNHbDdiBd1Jo4jDco8ygfawhs9Ngzjyyqx2",
                    "HBzKhJsow7nDMDx1THY7cQMKmNkjFyZyqWMVVRb4Ra5Z",
                    "J9vVF9cYFRf37FDSPzCFvtUyrg1kVgCRDhrQZUCoNQXP",
                    "4wJRN1Kqk24bvwNBJ4siq2VG2c78x4N9pLBLM1jMcuZN"
                ],
                "supply_percentage": 69.89
            }
        ],
        "average_time_since_mint": 198.1,
        "median_time_since_mint": 227.5,
        "potential_frontrunning_detected": false,
        "sniper_confidence_score": 9

Understanding Fields

The SniperAnalysisResult is a comprehensive analysis output with the following fields:

Field	Description	Example Value
sniper_addresses	Array of wallet addresses identified as potential snipers	["ARD9GAKA6LAz...", "o7RY6P2vQMu..."]
sniper_count	Number of identified sniper addresses	5
sniper_total_percentage	Total percentage of token supply acquired by snipers within the analyzed time window	77.18%
block_range_analysis	Block-by-block breakdown of trading activity	See below
time_since_mint_analysis	Trading activity analyzed by time intervals	See below
average_time_since_mint	Average time (seconds) of buys after mint	224.36 seconds
median_time_since_mint	Median time (seconds) of buys after mint	150 seconds
potential_frontrunning_detected	Whether potential frontrunning was identified	true
sniper_confidence_score	Overall score (0-100) indicating confidence in sniper activity	46
risk_assessment	Overall risk assessment ("low", "medium", or "high")	"medium"

Block Range Analysis

This provides insights into buying activity by block:

{
  "block_hash": "917TtwH3X6NLwAtWsWLPejRBw9b7W1cD1NadihRNYZZY",
  "timestamp": "2025-03-21T13:10:22.000Z",
  "buy_count": 3,
  "block_number": 1,
  "addresses": ["ARD9GAKA6LAzufwqZ3BTKcnJmaeNyGHp3n7UU4eiJ3mS", 
                "o7RY6P2vQMuGSu1TrLM81weuzgDjaCRTXYRaXJwWcvc", 
                "29eiZNQKgbTNMMx5MtffRiVnTSPAe5GDHGTyr1HqyR87"],
  "supply_percentage": 71.56
}

This shows that in the first block after mint, 3 buyers acquired 71.56% of the token supply, a strong indicator of sniper activity.

Time Since Mint Analysis

This analyzes trading activity by time windows after mint:

{
  "time_range_seconds": 10,
  "buy_count": 16,
  "addresses": ["ARD9GAKA6LAzufwqZ3BTKcnJmaeNyGHp3n7UU4eiJ3mS", "o7RY6P2vQMuGSu1TrLM81weuzgDjaCRTXYRaXJwWcvc", ...],
  "supply_percentage": 72.81
}

This example shows that within 10 seconds of mint, 16 buyers acquired 72.81% of the supply.

Confidence Score Calculation

The confidence score is calculated based on multiple factors:

First block buying activity: Higher percentage of buys in first block = higher score
Time proximity to mint: Faster buys = higher score
Supply percentage: Larger percentage acquired = higher score
Front-running indicators: Adds 15 points if detected
Ratio of snipers to total buyers: Higher ratio = higher score
Bot-like patterns: Adds points based on percentage of buyers showing bot activity

The final score determines the risk assessment:

Score	Value
Low	x <= 40
Medium	40 < x <= 75
High	x > 75 OR x >=60 and token age < 12 hours

What is Sniping

Introduction

What is Sniping?

🚧
Why Snipe?

How Webacy's Sniper Detection Works

Considerations

❗️
Endpoint Specifics

👍
Try these addresses!

Example Data Return

📘
Important Field

Understanding Fields

Block Range Analysis

Time Since Mint Analysis

Confidence Score Calculation

Introduction

What is Sniping?

🚧Why Snipe?

How Webacy's Sniper Detection Works

Considerations

❗️Endpoint Specifics

👍Try these addresses!

Example Data Return

📘Important Field

Understanding Fields

Block Range Analysis

Time Since Mint Analysis

Confidence Score Calculation

🚧
Why Snipe?

❗️
Endpoint Specifics

👍
Try these addresses!

📘
Important Field