{"id":3798,"date":"2026-06-21T00:18:16","date_gmt":"2026-06-21T00:18:16","guid":{"rendered":"https:\/\/tokenmetrics.com\/blog\/jaredfromsubway-eth-bot-drained-75-million-exploit\/"},"modified":"2026-06-21T03:57:33","modified_gmt":"2026-06-21T03:57:33","slug":"jaredfromsubway-eth-bot-drained-75-million-exploit","status":"publish","type":"post","link":"https:\/\/tokenmetrics.com\/eth\/news\/jaredfromsubway-eth-bot-drained-75-million-exploit\/","title":{"rendered":"Jaredfromsubway.eth Bot Drained for $7.5M \u2014 ETH Technicals Stay Bullish"},"content":{"rendered":"<h2>Signal Snapshot<\/h2>\n<ul>\n<li>Jaredfromsubway.eth, one of Ethereum&#8217;s best-known MEV bots, was drained for about $7.5 million after attackers turned its own automated trading logic against it.<\/li>\n<li>The exploit matters because it shows MEV bots can be vulnerable to the same adversarial tactics they use against other traders.<\/li>\n<li>The ETH market signal was more muted than the security headline: Token Metrics technicals still showed bullish ETH momentum at the time of publication.<\/li>\n<\/ul>\n<h2>Key Takeaways<\/h2>\n<ul>\n<li>The attack used fake wrapper tokens and pools to make the bot approve attacker-controlled contracts.<\/li>\n<li>The loss was specific to Jaredfromsubway.eth&#8217;s automated system, not a broad Ethereum protocol failure.<\/li>\n<li>For ETH traders, the main watch item is whether the incident changes MEV activity or DeFi-user sentiment, not whether it breaks Ethereum itself.<\/li>\n<\/ul>\n<h2>What Happened<\/h2>\n<p>Attackers drained roughly $7.5 million from Jaredfromsubway.eth, a prominent Ethereum MEV bot. According to <a href=\"https:\/\/www.bitget.com\/amp\/news\/detail\/12560605469431\" target=\"_blank\" rel=\"noopener\">reports on the Jaredfromsubway.eth exploit<\/a>, the attack used fake tokens and fake pools to create routes that looked profitable to the bot&#8217;s automated system.<\/p>\n<p>The attacker created fake wrapper assets, including fake versions of WETH, USDC, and USDT. The bot&#8217;s system interacted with those routes and granted approvals to helper contracts. The attacker then used those approvals to sweep funds from the bot.<\/p>\n<p>The key point: this was not a normal user-wallet phishing story. It was closer to a counter-MEV setup that exploited how the bot searched for profit.<\/p>\n<h2>Why It Matters<\/h2>\n<p>Jaredfromsubway.eth became famous because it extracted value from Ethereum users through sandwich attacks. A sandwich attack happens when a bot buys before a user&#8217;s trade and sells after it, capturing the price movement created by the user&#8217;s order.<\/p>\n<p>That made this exploit symbolically important. A bot known for extracting value from DeFi users was itself targeted by an adversarial trading setup. The incident does not point to an Ethereum consensus bug, but it does highlight how aggressive automation can create new attack surfaces.<\/p>\n<p>For the broader market, the question is whether this slows MEV activity, forces bot operators to harden approval logic, or simply becomes another one-off exploit in a competitive onchain trading environment.<\/p>\n\t\t<style id=\"tm-token-card-styles\">\n\t\t.tm-token-card {\n\t\t\tposition: relative;\n\t\t\tmargin: 1.75em 0;\n\t\t\tpadding: 1.25em 1.4em 1.4em;\n\t\t\tbackground: #17171D;\n\t\t\tborder: 1px solid rgba(255, 214, 10, 0.18);\n\t\t\tborder-radius: 16px;\n\t\t\tcolor: #e8eaf2;\n\t\t\tfont-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Roboto, \"Helvetica Neue\", Arial, sans-serif;\n\t\t\toverflow: hidden;\n\t\t}\n\t\t.tm-token-card::before {\n\t\t\tcontent: \"\";\n\t\t\tposition: absolute;\n\t\t\ttop: 0;\n\t\t\tleft: 0;\n\t\t\twidth: 4px;\n\t\t\theight: 100%;\n\t\t\tbackground: #FFD60A;\n\t\t}\n\t\t.tm-token-card__header {\n\t\t\tdisplay: flex;\n\t\t\tflex-direction: column;\n\t\t\tgap: 0.4em;\n\t\t\tmargin-bottom: 1em;\n\t\t}\n\t\t.tm-token-card__eyebrow {\n\t\t\tmargin: 0;\n\t\t\tfont-size: 0.72em;\n\t\t\tfont-weight: 700;\n\t\t\tletter-spacing: 0.12em;\n\t\t\ttext-transform: uppercase;\n\t\t\tcolor: #FFD60A;\n\t\t}\n\t\t.tm-token-card__title {\n\t\t\tmargin: 0;\n\t\t\tdisplay: inline-flex;\n\t\t\talign-items: baseline;\n\t\t\tgap: 0.55em;\n\t\t\tflex-wrap: wrap;\n\t\t\tfont-size: 1.5em;\n\t\t\tfont-weight: 700;\n\t\t\tline-height: 1.15;\n\t\t\tcolor: #ffffff;\n\t\t\tletter-spacing: -0.01em;\n\t\t}\n\t\t.tm-token-card__name {\n\t\t\tcolor: #ffffff;\n\t\t}\n\t\t.tm-token-card__ticker {\n\t\t\tpadding: 0.2em 0.6em;\n\t\t\tbackground: rgba(255, 214, 10, 0.14);\n\t\t\tcolor: #FFD60A;\n\t\t\tfont-size: 0.55em;\n\t\t\tfont-weight: 700;\n\t\t\tletter-spacing: 0.08em;\n\t\t\tborder-radius: 999px;\n\t\t\ttext-transform: uppercase;\n\t\t\tline-height: 1;\n\t\t}\n\t\t\/* Recap theme forces `list-style-type: disc` on .entry-content ul\n\t\t * and `padding-left: 0` on every <li> via a high-specificity\n\t\t * selector chain (style.css:1872+). 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}\n\t\t.tm-tv-chart__change--down { color: #f87171; }\n\t\t.tm-tv-chart__canvas {\n\t\t\twidth: 100%;\n\t\t\tmin-height: 120px;\n\t\t}\n\t\t.tm-tv-chart__caption {\n\t\t\tmargin: 0.4em 0.25em 0;\n\t\t\tfont-size: 0.8em;\n\t\t\tcolor: rgba(232, 234, 242, 0.45);\n\t\t\ttext-align: right;\n\t\t}\n\n\t\t\/* Token stats panel \u2014 chart + stats + CTA stack on news posts *\/\n\t\t.tm-token-stats {\n\t\t\tmargin: 1.5em 0;\n\t\t\tpadding: 1em 1.1em 0.85em;\n\t\t\tbackground: #17171D;\n\t\t\tborder: 1px solid rgba(255, 214, 10, 0.18);\n\t\t\tborder-radius: 16px;\n\t\t\tcolor: #e8eaf2;\n\t\t\tfont-family: inherit;\n\t\t\tfont-size: inherit;\n\t\t\tline-height: 1.5;\n\t\t}\n\t\t.tm-token-stats__header {\n\t\t\tdisplay: flex; align-items: baseline; justify-content: space-between;\n\t\t\tgap: 0.75em; margin-bottom: 0.6em;\n\t\t}\n\t\t.tm-token-stats__title {\n\t\t\tmargin: 0; font-size: 0.9em; font-weight: 700; color: #FFD60A;\n\t\t\tletter-spacing: 0.04em; text-transform: uppercase;\n\t\t}\n\t\t.tm-token-stats__lookback {\n\t\t\tfont-size: 0.7em; 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'+' : '\u2212') + Math.abs(changePct).toFixed(2) + '%)';\n\t\t\tchangeEl.classList.remove('tm-tv-chart__change--up', 'tm-tv-chart__change--down');\n\t\t\tif (changeAbs > 0) { changeEl.classList.add('tm-tv-chart__change--up'); }\n\t\t\telse if (changeAbs < 0) { changeEl.classList.add('tm-tv-chart__change--down'); }\n\t\t}\n\n\t\tfunction fetchOhlc(coinId, days) {\n\t\t\tvar url = 'https:\/\/api.coingecko.com\/api\/v3\/coins\/' + encodeURIComponent(coinId)\n\t\t\t\t+ '\/ohlc?vs_currency=usd&days=' + encodeURIComponent(days);\n\t\t\treturn fetch(url, { credentials: 'omit' }).then(function (r) {\n\t\t\t\tif (!r.ok) { throw new Error('coingecko ' + r.status); }\n\t\t\t\treturn r.json();\n\t\t\t}).then(function (rows) {\n\t\t\t\tif (!Array.isArray(rows)) { return []; }\n\t\t\t\treturn rows.map(function (k) {\n\t\t\t\t\treturn { time: Math.floor(k[0] \/ 1000), value: parseFloat(k[4]) };\n\t\t\t\t});\n\t\t\t});\n\t\t}\n\n\t\tfunction renderOne(figure) {\n\t\t\tif (figure.dataset.tmChartReady) { return; }\n\t\t\tif (figure.dataset.tmChartFetching) { return; }\n\t\t\tvar coinId = figure.getAttribute('data-tm-chart-id');\n\t\t\tvar days   = figure.getAttribute('data-tm-chart-days') || '14';\n\t\t\tvar height = parseInt(figure.getAttribute('data-tm-chart-height') || '220', 10);\n\t\t\tvar canvas = figure.querySelector('.tm-tv-chart__canvas');\n\t\t\tif (!coinId || !canvas) { return; }\n\t\t\t\/\/ Greptile P1 (PR #1470): only mark the figure ready AFTER\n\t\t\t\/\/ the OHLC fetch resolves successfully. The earlier flow set\n\t\t\t\/\/ the flag before the await, so a single 429 from CoinGecko\n\t\t\t\/\/ permanently disabled retry for that page-load \u2014 every\n\t\t\t\/\/ subsequent renderAll() call (e.g. on resize \/ hashchange)\n\t\t\t\/\/ would short-circuit on the stale flag and the chart would\n\t\t\t\/\/ stay blank forever. The intermediate `tmChartFetching`\n\t\t\t\/\/ flag still prevents in-flight double-fetches.\n\t\t\tfigure.dataset.tmChartFetching = '1';\n\n\t\t\tfetchOhlc(coinId, days).then(function (data) {\n\t\t\t\tif (!data || data.length === 0) {\n\t\t\t\t\tdelete figure.dataset.tmChartFetching;\n\t\t\t\t\treturn;\n\t\t\t\t}\n\t\t\t\tfigure.dataset.tmChartReady = '1';\n\t\t\t\tdelete figure.dataset.tmChartFetching;\n\t\t\t\tvar precision = priceFormat(data[data.length - 1].value);\n\t\t\t\t\/\/ Greptile P2 (PR #1470): canvas.clientWidth is 0 when\n\t\t\t\t\/\/ the .tm-tv-chart__canvas isn't laid out yet (lazy-load\n\t\t\t\t\/\/ container, hidden tab, accordion). lightweight-charts\n\t\t\t\t\/\/ silently accepts 0 and creates an invisible chart.\n\t\t\t\t\/\/ Fall back to offsetWidth, then a sane default.\n\t\t\t\tvar initialWidth = canvas.clientWidth || canvas.offsetWidth || 600;\n\t\t\t\tvar chart = window.LightweightCharts.createChart(canvas, {\n\t\t\t\t\twidth: initialWidth,\n\t\t\t\t\theight: height,\n\t\t\t\t\tlayout: { background: { color: TM_BRAND.bg }, textColor: TM_BRAND.text, fontFamily: '-apple-system, BlinkMacSystemFont, Segoe UI, Roboto, sans-serif', attributionLogo: false },\n\t\t\t\t\tgrid: { vertLines: { visible: false }, horzLines: { color: TM_BRAND.grid } },\n\t\t\t\t\trightPriceScale: { borderColor: TM_BRAND.border },\n\t\t\t\t\ttimeScale: {\n\t\t\t\t\t\tborderColor: TM_BRAND.border,\n\t\t\t\t\t\ttimeVisible: true,\n\t\t\t\t\t\tsecondsVisible: false,\n\t\t\t\t\t\t\/\/ End-user feedback: the default DayOfMonth formatter\n\t\t\t\t\t\t\/\/ shows bare numbers (\"4 7 10 13 16\") with no month\n\t\t\t\t\t\t\/\/ context, leaving readers to guess what month\n\t\t\t\t\t\t\/\/ they're looking at. Force a Month-Day format for\n\t\t\t\t\t\t\/\/ DayOfMonth ticks and full Month-Day-Year for\n\t\t\t\t\t\t\/\/ Month\/Year ticks. lightweight-charts passes a\n\t\t\t\t\t\t\/\/ numeric tickMarkType from its TickMarkType enum:\n\t\t\t\t\t\t\/\/ 0=Year, 1=Month, 2=DayOfMonth, 3=Time, 4=TimeWithSeconds.\n\t\t\t\t\t\ttickMarkFormatter: function (time, tickMarkType, locale) {\n\t\t\t\t\t\t\tvar d = new Date(time * 1000);\n\t\t\t\t\t\t\tif (tickMarkType === 0) {\n\t\t\t\t\t\t\t\treturn d.getUTCFullYear().toString();\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tif (tickMarkType === 1) {\n\t\t\t\t\t\t\t\treturn d.toLocaleDateString(locale, { month: 'short', year: 'numeric', timeZone: 'UTC' });\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\/\/ DayOfMonth (2) and any time-level ticks fall\n\t\t\t\t\t\t\t\/\/ through to month-day, which is the format users\n\t\t\t\t\t\t\t\/\/ actually wanted on the 14-day chart.\n\t\t\t\t\t\t\treturn d.toLocaleDateString(locale, { month: 'short', day: 'numeric', timeZone: 'UTC' });\n\t\t\t\t\t\t}\n\t\t\t\t\t},\n\t\t\t\t\tcrosshair: { mode: 0 },\n\t\t\t\t\thandleScroll: false,\n\t\t\t\t\thandleScale: false\n\t\t\t\t});\n\t\t\t\tvar series = chart.addAreaSeries({\n\t\t\t\t\tlineColor: TM_BRAND.line,\n\t\t\t\t\ttopColor: TM_BRAND.fillTop,\n\t\t\t\t\tbottomColor: TM_BRAND.fillBot,\n\t\t\t\t\tlineWidth: 2,\n\t\t\t\t\tpriceFormat: { type: 'price', precision: precision.precision, minMove: precision.minMove }\n\t\t\t\t});\n\t\t\t\tseries.setData(data);\n\t\t\t\tchart.timeScale().fitContent();\n\t\t\t\tupdateQuote(figure, data);\n\t\t\t\tif (window.ResizeObserver) {\n\t\t\t\t\tvar ro = new ResizeObserver(function () { chart.applyOptions({ width: canvas.clientWidth }); });\n\t\t\t\t\tro.observe(canvas);\n\t\t\t\t}\n\t\t\t}).catch(function (err) {\n\t\t\t\t\/\/ Greptile P1 (PR #1470): clear the in-flight flag on\n\t\t\t\t\/\/ failure so a future renderAll() can retry. Without\n\t\t\t\t\/\/ this, a 429 from CoinGecko leaves the figure\n\t\t\t\t\/\/ permanently in a half-loaded state.\n\t\t\t\tdelete figure.dataset.tmChartFetching;\n\t\t\t\tconsole.warn('[tm-tv-chart] data fetch failed for ' + coinId, err);\n\t\t\t});\n\t\t}\n\n\t\tfunction renderAll() {\n\t\t\tvar figures = document.querySelectorAll('[data-tm-chart]');\n\t\t\tif (figures.length === 0) { return; }\n\t\t\tloadLibrary(function () { figures.forEach(renderOne); });\n\t\t}\n\n\t\tif (document.readyState === 'loading') {\n\t\t\tdocument.addEventListener('DOMContentLoaded', renderAll);\n\t\t} else {\n\t\t\trenderAll();\n\t\t}\n\t})();\n\t<\/script>\n\t\t\n\t\t<aside\n\t\tclass=\"tm-token-stats\"\n\t\tdata-tm-token-stats\n\t\tdata-tm-stats-id=\"ethereum\"\n\t\tdata-tm-stats-lookback=\"365\"\n\t\taria-label=\"Ethereum key statistics\"\n\t>\n\t\t<header class=\"tm-token-stats__header\">\n\t\t\t<h3 class=\"tm-token-stats__title\">Ethereum \u00b7 Key Stats<\/h3>\n\t\t\t<span class=\"tm-token-stats__lookback\">365d lookback<\/span>\n\t\t<\/header>\n\t\t<section class=\"tm-token-stats__section\">\n\t\t\t<h4 class=\"tm-token-stats__section-label\">Market<\/h4>\n\t\t\t<dl class=\"tm-token-stats__grid\">\n\t\t\t\t<div class=\"tm-token-stats__cell\"><dt>Market Cap<\/dt><dd data-tm-stats-value=\"market-cap\">\u2014<\/dd><\/div>\n\t\t\t\t<div class=\"tm-token-stats__cell\"><dt>Vol \/ Cap<\/dt><dd data-tm-stats-value=\"turnover\">\u2014<\/dd><\/div>\n\t\t\t\t<div class=\"tm-token-stats__cell\"><dt>52-Week Range<\/dt><dd data-tm-stats-value=\"range-52w\">\u2014<\/dd><\/div>\n\t\t\t<\/dl>\n\t\t<\/section>\n\t\t<section class=\"tm-token-stats__section\">\n\t\t\t<h4 class=\"tm-token-stats__section-label\">Performance<\/h4>\n\t\t\t<dl class=\"tm-token-stats__grid\">\n\t\t\t\t<div class=\"tm-token-stats__cell\"><dt>30d<\/dt><dd data-tm-stats-value=\"change-30d\">\u2014<\/dd><\/div>\n\t\t\t\t<div class=\"tm-token-stats__cell\"><dt>1y<\/dt><dd data-tm-stats-value=\"change-1y\">\u2014<\/dd><\/div>\n\t\t\t\t<div class=\"tm-token-stats__cell\"><dt>vs BTC<\/dt><dd data-tm-stats-value=\"vs-btc\">\u2014<\/dd><\/div>\n\t\t\t<\/dl>\n\t\t<\/section>\n\t\t<section class=\"tm-token-stats__section\">\n\t\t\t<h4 class=\"tm-token-stats__section-label\">Risk (1y)<\/h4>\n\t\t\t<dl class=\"tm-token-stats__grid\">\n\t\t\t\t<div class=\"tm-token-stats__cell\"><dt>Volatility<\/dt><dd data-tm-stats-value=\"volatility\">\u2014<\/dd><\/div>\n\t\t\t\t<div class=\"tm-token-stats__cell\"><dt>Max Drawdown<\/dt><dd data-tm-stats-value=\"max-drawdown\">\u2014<\/dd><\/div>\n\t\t\t\t<div class=\"tm-token-stats__cell\"><dt>Sharpe<\/dt><dd data-tm-stats-value=\"sharpe\">\u2014<\/dd><\/div>\n\t\t\t<\/dl>\n\t\t<\/section>\n\t\t<p class=\"tm-token-stats__source\">Data via CoinGecko. Risk metrics from the trailing daily closes.<\/p>\n\t<\/aside>\n\t\t<script id=\"tm-token-stats-hydrator\">\n\t(function () {\n\t\t\/\/ Routed through the tm-coingecko-proxy Worker (5-min KV cache,\n\t\t\/\/ paid Pro key) instead of api.coingecko.com directly. Base URL is\n\t\t\/\/ resolved server-side from the `tm_token_card_coingecko_proxy_base`\n\t\t\/\/ filter \/ TM_COINGECKO_PROXY_BASE constant so staging can point\n\t\t\/\/ at a separate Worker.\n\t\tvar PROXY_BASE = \"https:\\\/\\\/tokenmetrics.com\\\/api\\\/cg\";\n\t\tvar DAYS_PER_YEAR = 365;\n\t\tvar coinCache = {};\n\t\tfunction fetchJson(url) {\n\t\t\treturn fetch(url, { credentials: 'omit' }).then(function (r) {\n\t\t\t\tif (!r.ok) { throw new Error('coingecko ' + r.status); }\n\t\t\t\treturn r.json();\n\t\t\t});\n\t\t}\n\t\tfunction fetchSnapshot(id) {\n\t\t\tif (coinCache['snap_' + id]) { return coinCache['snap_' + id]; }\n\t\t\tvar url = PROXY_BASE + '\/coins\/' + encodeURIComponent(id)\n\t\t\t\t+ '?localization=false&tickers=false&community_data=false&developer_data=false&sparkline=false';\n\t\t\tcoinCache['snap_' + id] = fetchJson(url);\n\t\t\treturn coinCache['snap_' + id];\n\t\t}\n\t\tfunction fetchSeries(id, days) {\n\t\t\tvar key = 'series_' + id + '_' + days;\n\t\t\tif (coinCache[key]) { return coinCache[key]; }\n\t\t\tvar url = PROXY_BASE + '\/coins\/' + encodeURIComponent(id)\n\t\t\t\t+ '\/market_chart?vs_currency=usd&days=' + encodeURIComponent(days);\n\t\t\tcoinCache[key] = fetchJson(url).then(function (d) {\n\t\t\t\treturn Array.isArray(d.prices) ? d.prices : [];\n\t\t\t});\n\t\t\treturn coinCache[key];\n\t\t}\n\t\tfunction fmtUsd(value) {\n\t\t\tvar abs = Math.abs(value);\n\t\t\tvar precision = abs >= 0.01 ? 2 : (abs >= 0.0001 ? 6 : 8);\n\t\t\treturn '$' + value.toLocaleString('en-US', { minimumFractionDigits: precision, maximumFractionDigits: precision });\n\t\t}\n\t\tfunction fmtCompactUsd(value) {\n\t\t\tif (value === null || value === undefined || isNaN(value)) { return '\u2014'; }\n\t\t\tvar abs = Math.abs(value);\n\t\t\tif (abs >= 1e12) { return '$' + (value \/ 1e12).toFixed(2) + 'T'; }\n\t\t\tif (abs >= 1e9)  { return '$' + (value \/ 1e9).toFixed(2)  + 'B'; }\n\t\t\tif (abs >= 1e6)  { return '$' + (value \/ 1e6).toFixed(2)  + 'M'; }\n\t\t\tif (abs >= 1e3)  { return '$' + (value \/ 1e3).toFixed(2)  + 'K'; }\n\t\t\treturn fmtUsd(value);\n\t\t}\n\t\tfunction fmtPct(value) {\n\t\t\tif (value === null || value === undefined || isNaN(value)) { return '\u2014'; }\n\t\t\tvar sign = value >= 0 ? '+' : '\u2212';\n\t\t\treturn sign + Math.abs(value).toFixed(2) + '%';\n\t\t}\n\t\tfunction trendOf(value) {\n\t\t\tif (value === null || value === undefined || isNaN(value)) { return null; }\n\t\t\tif (value > 0) { return 'up'; }\n\t\t\tif (value < 0) { return 'down'; }\n\t\t\treturn null;\n\t\t}\n\t\tfunction setCell(root, key, text, trend) {\n\t\t\tvar el = root.querySelector('[data-tm-stats-value=\"' + key + '\"]');\n\t\t\tif (!el) { return; }\n\t\t\tel.textContent = text;\n\t\t\tif (trend === 'up' || trend === 'down') { el.setAttribute('data-trend', trend); }\n\t\t\telse { el.removeAttribute('data-trend'); }\n\t\t}\n\t\tfunction dailyReturns(prices) {\n\t\t\tvar rets = [];\n\t\t\tfor (var i = 1; i < prices.length; i++) {\n\t\t\t\tvar prev = prices[i - 1][1], cur = prices[i][1];\n\t\t\t\tif (prev > 0 && isFinite(prev) && isFinite(cur)) { rets.push(cur \/ prev - 1); }\n\t\t\t}\n\t\t\treturn rets;\n\t\t}\n\t\tfunction mean(arr) {\n\t\t\tif (arr.length === 0) { return 0; }\n\t\t\tvar s = 0; for (var i = 0; i < arr.length; i++) { s += arr[i]; }\n\t\t\treturn s \/ arr.length;\n\t\t}\n\t\tfunction stddev(arr, mu) {\n\t\t\tif (arr.length < 2) { return 0; }\n\t\t\tvar s = 0;\n\t\t\tfor (var i = 0; i < arr.length; i++) { var d = arr[i] - mu; s += d * d; }\n\t\t\treturn Math.sqrt(s \/ (arr.length - 1));\n\t\t}\n\t\tfunction maxDrawdown(prices) {\n\t\t\tif (prices.length < 2) { return { value: 0, duration: 0 }; }\n\t\t\tvar peak = prices[0][1], peakIdx = 0;\n\t\t\tvar maxDd = 0, troughIdx = 0, troughPeakIdx = 0;\n\t\t\tfor (var i = 1; i < prices.length; i++) {\n\t\t\t\tvar p = prices[i][1];\n\t\t\t\tif (p > peak) { peak = p; peakIdx = i; }\n\t\t\t\tif (peak > 0) {\n\t\t\t\t\tvar dd = (p - peak) \/ peak;\n\t\t\t\t\tif (dd < maxDd) { maxDd = dd; troughIdx = i; troughPeakIdx = peakIdx; }\n\t\t\t\t}\n\t\t\t}\n\t\t\tvar duration = 0;\n\t\t\tif (prices[troughIdx] && prices[troughPeakIdx]) {\n\t\t\t\tvar ms = prices[troughIdx][0] - prices[troughPeakIdx][0];\n\t\t\t\tduration = Math.max(0, Math.round(ms \/ 86400000));\n\t\t\t}\n\t\t\treturn { value: maxDd, duration: duration };\n\t\t}\n\t\tfunction quantStats(prices) {\n\t\t\tif (!prices || prices.length < 30) { return null; }\n\t\t\tvar rets = dailyReturns(prices);\n\t\t\tif (rets.length === 0) { return null; }\n\t\t\tvar mu = mean(rets);\n\t\t\tvar sd = stddev(rets, mu);\n\t\t\tvar ann_mu = mu * DAYS_PER_YEAR;\n\t\t\tvar ann_sd = sd * Math.sqrt(DAYS_PER_YEAR);\n\t\t\tvar dd = maxDrawdown(prices);\n\t\t\treturn {\n\t\t\t\tvolatility:      ann_sd,\n\t\t\t\tmaxDrawdown:     dd.value,\n\t\t\t\tmaxDrawdownDays: dd.duration,\n\t\t\t\tsharpe:          ann_sd > 0 ? ann_mu \/ ann_sd : 0\n\t\t\t};\n\t\t}\n\t\tfunction totalReturn(prices) {\n\t\t\tif (!prices || prices.length < 2) { return null; }\n\t\t\tvar first = prices[0][1], last = prices[prices.length - 1][1];\n\t\t\tif (!isFinite(first) || !isFinite(last) || first <= 0) { return null; }\n\t\t\treturn last \/ first - 1;\n\t\t}\n\t\tfunction setRangeCell(root, key, low, current, high) {\n\t\t\tvar el = root.querySelector('[data-tm-stats-value=\"' + key + '\"]');\n\t\t\tif (!el) { return; }\n\t\t\tel.removeAttribute('data-trend');\n\t\t\tif (!isFinite(low) || !isFinite(high) || !isFinite(current) || high <= low) {\n\t\t\t\tel.textContent = '\u2014'; return;\n\t\t\t}\n\t\t\tvar pct = ((current - low) \/ (high - low)) * 100;\n\t\t\tpct = Math.max(0, Math.min(100, pct));\n\t\t\tel.innerHTML = '';\n\t\t\tvar wrap = document.createElement('div'); wrap.className = 'tm-token-stats__range';\n\t\t\tvar track = document.createElement('div'); track.className = 'tm-token-stats__range-track';\n\t\t\tvar dot = document.createElement('div'); dot.className = 'tm-token-stats__range-dot';\n\t\t\tdot.style.left = pct.toFixed(1) + '%';\n\t\t\ttrack.appendChild(dot);\n\t\t\tvar bounds = document.createElement('div'); bounds.className = 'tm-token-stats__range-bounds';\n\t\t\tvar loSpan = document.createElement('span'); loSpan.textContent = fmtUsd(low);\n\t\t\tvar hiSpan = document.createElement('span'); hiSpan.textContent = fmtUsd(high);\n\t\t\tbounds.appendChild(loSpan); bounds.appendChild(hiSpan);\n\t\t\twrap.appendChild(track); wrap.appendChild(bounds); el.appendChild(wrap);\n\t\t}\n\t\tfunction renderOne(root) {\n\t\t\tif (root.dataset.tmStatsReady) { return; }\n\t\t\tvar coinId = root.getAttribute('data-tm-stats-id');\n\t\t\tvar lookback = root.getAttribute('data-tm-stats-lookback') || '365';\n\t\t\tif (!coinId) { return; }\n\t\t\troot.dataset.tmStatsReady = '1';\n\t\t\tPromise.all([\n\t\t\t\tfetchSnapshot(coinId),\n\t\t\t\tfetchSeries(coinId, lookback),\n\t\t\t\tfetchSeries('bitcoin', lookback)\n\t\t\t]).then(function (results) {\n\t\t\t\tvar snap = results[0]; var prices = results[1]; var btcPrices = results[2];\n\t\t\t\tvar md = (snap && snap.market_data) || {};\n\t\t\t\tsetCell(root, 'market-cap', fmtCompactUsd(md.market_cap && md.market_cap.usd));\n\t\t\t\tvar vol = md.total_volume && md.total_volume.usd;\n\t\t\t\tvar mcap = md.market_cap && md.market_cap.usd;\n\t\t\t\tvar turnoverText = '\u2014';\n\t\t\t\tif (vol && mcap && mcap > 0) {\n\t\t\t\t\tturnoverText = fmtCompactUsd(vol) + ' (' + ((vol \/ mcap) * 100).toFixed(2) + '%)';\n\t\t\t\t} else if (vol) { turnoverText = fmtCompactUsd(vol); }\n\t\t\t\tsetCell(root, 'turnover', turnoverText);\n\t\t\t\tif (prices && prices.length > 1) {\n\t\t\t\t\tvar lo = Infinity, hi = -Infinity;\n\t\t\t\t\tfor (var i = 0; i < prices.length; i++) {\n\t\t\t\t\t\tvar p = prices[i][1];\n\t\t\t\t\t\tif (p < lo) { lo = p; } if (p > hi) { hi = p; }\n\t\t\t\t\t}\n\t\t\t\t\tvar cur = (md.current_price && md.current_price.usd) || prices[prices.length - 1][1];\n\t\t\t\t\tsetRangeCell(root, 'range-52w', lo, cur, hi);\n\t\t\t\t}\n\t\t\t\tsetCell(root, 'change-30d', fmtPct(md.price_change_percentage_30d), trendOf(md.price_change_percentage_30d));\n\t\t\t\tsetCell(root, 'change-1y',  fmtPct(md.price_change_percentage_1y),  trendOf(md.price_change_percentage_1y));\n\t\t\t\tvar tokenRet = totalReturn(prices), btcRet = totalReturn(btcPrices);\n\t\t\t\tif (tokenRet !== null && btcRet !== null) {\n\t\t\t\t\tvar vsBtc = (tokenRet - btcRet) * 100;\n\t\t\t\t\tsetCell(root, 'vs-btc', fmtPct(vsBtc), trendOf(vsBtc));\n\t\t\t\t}\n\t\t\t\tvar qs = quantStats(prices);\n\t\t\t\tvar btcQs = quantStats(btcPrices);\n\t\t\t\tif (qs) {\n\t\t\t\t\tsetCell(root, 'volatility', (qs.volatility * 100).toFixed(1) + '%');\n\t\t\t\t\tvar ddText = fmtPct(qs.maxDrawdown * 100);\n\t\t\t\t\tif (qs.maxDrawdownDays > 0) { ddText += ' (' + qs.maxDrawdownDays + 'd)'; }\n\t\t\t\t\tsetCell(root, 'max-drawdown', ddText, 'down');\n\t\t\t\t\tvar sharpeText = qs.sharpe.toFixed(2);\n\t\t\t\t\tif (btcQs && btcQs.sharpe !== 0) { sharpeText += ' \u00b7 BTC ' + btcQs.sharpe.toFixed(2); }\n\t\t\t\t\tsetCell(root, 'sharpe', sharpeText, trendOf(qs.sharpe));\n\t\t\t\t}\n\t\t\t}).catch(function (err) { console.warn('[tm-token-stats] fetch failed for ' + coinId, err); });\n\t\t}\n\t\tfunction renderAll() {\n\t\t\tvar roots = document.querySelectorAll('[data-tm-token-stats]');\n\t\t\troots.forEach(renderOne);\n\t\t}\n\t\tif (document.readyState === 'loading') {\n\t\t\tdocument.addEventListener('DOMContentLoaded', renderAll);\n\t\t} else {\n\t\t\trenderAll();\n\t\t}\n\t})();\n\t<\/script>\n\t\t\n\t\t<aside\n\t\tclass=\"tm-token-card\"\n\t\trole=\"complementary\"\n\t\taria-label=\"Track Ethereum (ETH) with Token Metrics\"\n\t\tdata-tm-token-card=\"eth\"\n\t>\n\t\t<header class=\"tm-token-card__header\">\n\t\t\t<p class=\"tm-token-card__eyebrow\">Track this token with Token Metrics<\/p>\n\t\t\t<h3 class=\"tm-token-card__title\">\n\t\t\t\t<span class=\"tm-token-card__name\">Ethereum<\/span>\n\t\t\t\t<span class=\"tm-token-card__ticker\">ETH<\/span>\n\t\t\t<\/h3>\n\t\t<\/header>\n\t\t<ul class=\"tm-token-card__benefits\">\n\t\t\t\t\t\t\t<li class=\"tm-token-card__benefit\">7-day free trial of Signal<\/li>\n\t\t\t\t\t\t\t<li class=\"tm-token-card__benefit\">Smart-money wallet flows across the top tokens<\/li>\n\t\t\t\t\t\t\t<li class=\"tm-token-card__benefit\">Daily technical setup labels \u2014 Bullish to Bearish, both directions<\/li>\n\t\t\t\t\t\t\t<li class=\"tm-token-card__benefit\">Polymarket consensus on near-term catalysts<\/li>\n\t\t\t\t\t<\/ul>\n\t\t<div class=\"tm-token-card__footer\">\n\t\t\t<a class=\"tm-token-card__cta\" href=\"https:\/\/tokenmetrics.com\/?utm_source=tm_blog&#038;utm_medium=token_card&#038;utm_campaign=signal_eth#premium\" rel=\"noopener\" target=\"_blank\">Catch crypto trades before the crowd \u2192<\/a>\n\t\t\t<span class=\"tm-token-card__meta\">Signal alerts include the setup, risk, and what would change the trade.<\/span>\n\t\t<\/div>\n\t<\/aside>\n\t\n<h2>Market Context<\/h2>\n<p>MEV is a persistent part of Ethereum&#8217;s DeFi market structure. Bots monitor pending transactions and try to reorder or surround trades for profit. That activity can improve some forms of liquidity, but it can also create worse execution for normal users.<\/p>\n<p>The Jaredfromsubway.eth name is closely tied to that debate because the bot has been associated with high-volume sandwich activity on Ethereum. A successful exploit against the bot is therefore both a security story and a market-structure story.<\/p>\n<p>ETH itself did not need to be the direct victim for the story to matter. The exploit happened inside Ethereum&#8217;s trading environment, and it may influence how users, bot operators, and protocols think about approvals, routing, and MEV protections.<\/p>\n<h2>Risks to Watch<\/h2>\n<ul>\n<li>Copycat attacks against other MEV bots using fake-token or fake-pool routes.<\/li>\n<li>More aggressive approval controls from bot operators after this loss.<\/li>\n<li>Temporary changes in sandwich-attack activity if Jaredfromsubway.eth stays offline or slows down.<\/li>\n<li>Negative DeFi sentiment if users see the incident as another sign that onchain trading remains hostile to normal participants.<\/li>\n<li>ETH technical support if the security headline begins to affect broader market confidence.<\/li>\n<\/ul>\n<h2>What to Watch Next<\/h2>\n<ul>\n<li>Whether Jaredfromsubway.eth resumes normal activity after the loss.<\/li>\n<li>Whether security firms publish a fuller transaction trace of the exploit path.<\/li>\n<li>Whether other MEV bots change approval behavior or routing filters.<\/li>\n<li>Whether Ethereum sandwich-attack volumes decline after the incident.<\/li>\n<li>Whether ETH remains technically resilient despite the DeFi security headline.<\/li>\n<\/ul>\n<h2>Sources \/ Data Used<\/h2>\n<ul>\n<li><a href=\"https:\/\/www.bitget.com\/amp\/news\/detail\/12560605469431\" target=\"_blank\" rel=\"noopener\">Bitget summary of the Jaredfromsubway.eth exploit<\/a><\/li>\n<li><a href=\"https:\/\/bingx.com\/en\/flash-news\/post\/ethereum-mev-bot-jaredfromsubway-eth-loses-over-m-in-anti-mev-honeypot-attack-using-fake-token-contracts\" target=\"_blank\" rel=\"noopener\">BingX flash report on the anti-MEV honeypot attack<\/a><\/li>\n<li>Token Metrics ETH technical snapshot used by the original article run.<\/li>\n<\/ul>\n<p>This information is for educational purposes only and does not constitute financial advice.<\/p>\n","protected":false},"excerpt":{"rendered":"Jaredfromsubway.eth was drained for about $7.5 million after attackers used fake-token routes against the MEV bot. The incident highlights MEV automation risk while ETH technicals remained resilient.","protected":false},"author":1,"featured_media":3797,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_tm_paid_cta_tier":"","_tm_paid_cta_heading":"","_tm_paid_cta_body":"","csco_display_header_overlay":false,"csco_singular_sidebar":"","csco_page_header_type":"","csco_page_load_nextpost":"","csco_page_reading_time":"","csco_page_toc_navigation":"","csco_post_video_location":[],"csco_post_video_location_hash":"","csco_post_video_url":"","csco_post_video_bg_start_time":0,"csco_post_video_bg_end_time":0,"csco_post_video_bg_volume":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[204,158],"tags":[208,32,716,715,283],"sections":[183],"entities":[205],"class_list":["post-3798","post","type-post","status-publish","format-standard","has-post-thumbnail","category-eth","category-news","tag-defi","tag-ethereum","tag-jaredfromsubway-eth","tag-mev","tag-security","section-news","entity-eth","cs-entry","cs-video-wrap"],"jetpack_featured_media_url":"https:\/\/tokenmetrics.com\/blog\/wp-content\/uploads\/2026\/06\/jaredfromsubway-eth-bot-drained-75-million-exploit-featured.webp","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/tokenmetrics.com\/blog\/wp-json\/wp\/v2\/posts\/3798","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tokenmetrics.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/tokenmetrics.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/tokenmetrics.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/tokenmetrics.com\/blog\/wp-json\/wp\/v2\/comments?post=3798"}],"version-history":[{"count":1,"href":"https:\/\/tokenmetrics.com\/blog\/wp-json\/wp\/v2\/posts\/3798\/revisions"}],"predecessor-version":[{"id":3799,"href":"https:\/\/tokenmetrics.com\/blog\/wp-json\/wp\/v2\/posts\/3798\/revisions\/3799"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/tokenmetrics.com\/blog\/wp-json\/wp\/v2\/media\/3797"}],"wp:attachment":[{"href":"https:\/\/tokenmetrics.com\/blog\/wp-json\/wp\/v2\/media?parent=3798"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/tokenmetrics.com\/blog\/wp-json\/wp\/v2\/categories?post=3798"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/tokenmetrics.com\/blog\/wp-json\/wp\/v2\/tags?post=3798"},{"taxonomy":"section","embeddable":true,"href":"https:\/\/tokenmetrics.com\/blog\/wp-json\/wp\/v2\/sections?post=3798"},{"taxonomy":"entity","embeddable":true,"href":"https:\/\/tokenmetrics.com\/blog\/wp-json\/wp\/v2\/entities?post=3798"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}