Crypto World
What’s the Status of Trump’s Border Wall?
An additional 22 miles of the waterborne barrier system has been constructed since Trump’s return to office.
Challenges in construction
Trump’s Administrations have faced several hurdles in constructing the border wall.
One aspect of the construction that has posed significant challenges has been the need to acquire land that is already owned. Approximately 70% of the border is made up of private, tribal, or state-owned land, according to the GAO. And the federal government has faced pushback from all three fronts.
Among multiple challenges that have been made in response to the government’s attempts to acquire land, the Texas General Land Office in July sent CBP and an agency contractor a cease-and-desist letter after it said it discovered that the contractor had cleared over a mile of state land for construction, using heavy machinery and destroying vegetation.
“Texas sovereignty will not be infringed upon by failure to follow established protocol,” said Commissioner Dawn Buckingham in a statement. “I am committed to maintaining a positive relationship with CBP, but we will not allow rogue actors who breached our agreement to undermine the incredible work we do for Texas.”
Crypto World
Southeast Asia’s Next Growth Engine Runs on AI Infrastructure, United Overseas Bank Says
Artificial intelligence (AI) has stopped being a technology story in Southeast Asia and has become an economic growth engine, according to United Overseas Bank (UOB) executives speaking at the ASEAN Conference 2026.
The opportunity lies less in adopting AI tools than in building the physical infrastructure that makes them possible.
Where the Data Center Capacity Is Going
A hyperscaler is a company that operates data centers at a massive scale, typically a cloud provider serving global computing demand. Those firms are now accelerating capacity across the region.
Malaysia has captured much of the recent growth. Thailand, Indonesia, and Vietnam are also expanding aggressively as investment spreads across the region.
Singapore faces different constraints entirely. Long the premium hub, it now faces land and energy constraints that have prompted spillover effects on neighboring markets.
The numbers illustrate the scale. Industry trackers show Southeast Asia already hosts dozens of AI-focused facilities with several gigawatts of operational and planned capacity.
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Projections point sharply higher. Wood Mackenzie estimates data-center power demand could quadruple from 2.6 gigawatts in 2025 to 10.7 gigawatts by 2035.
A separate report reinforces that trajectory. The e-Conomy SEA 2025 study by Google, Temasek, and Bain estimates over 4,600 megawatts of new capacity in the pipeline. That expansion implies roughly 180% capacity growth, faster than the rest of Asia-Pacific.
The build-out demands more than servers and chips. Reliable power, advanced cooling, land, and robust grid connections all form essential components.
Capital requirements are correspondingly large. UOB’s Edmund Leong estimated that roughly $150 billion could flow into regional energy infrastructure over the next five years.
The Bottlenecks That Could Slow It Down
That figure spans multiple categories. Renewables and broader energy-transition projects both feature prominently in the projected investment. The dependency runs both ways. Without adequate energy and grid upgrades, the entire AI opportunity risks being constrained regardless of demand.
Financial institutions occupy a pivotal position. Banks with regional footprints mobilize loans, bonds, and equity while facilitating cross-border capital flows. Their role extends beyond financing. Those institutions connect developers with regulators, utilities, and telecom providers across multiple jurisdictions.
Selectivity matters considerably. Not every project proves bankable, and success depends on operators with technical expertise, committed shareholders, and long-term vision. Bottlenecks remain genuine obstacles. Power availability and semiconductor supply both constrain how quickly capacity can materialize.
Market dynamics offer some relief. Demand should eventually spur supply-side responses, gradually lowering costs and improving efficiency. Execution determines outcomes. Translating infrastructure investment into measurable results requires clear strategies, governance, and workforce readiness.
The potential prize justifies the attention. Southeast Asia’s digital economy should exceed $300 billion in gross merchandise value, with AI potentially adding up to $1 trillion to regional GDP by 2030.
Funding patterns reveal an interesting split. Equity concentrates in Singapore, while physical construction is dispersed, with Malaysia alone attracting tens of billions in commitments.
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The post Southeast Asia’s Next Growth Engine Runs on AI Infrastructure, United Overseas Bank Says appeared first on BeInCrypto.
Crypto World
Ondo Finance hit by corporate control fight as founder’s mother seeks to oust CEO
According to the complaint, Allman appointed herself to the board, adopted an interim policy allowing ordinary business operations to continue, reaffirmed De Bode as president and requested basic corporate information, including a shareholder list, while expressing a desire to work collaboratively.
The estate said those efforts failed after De Bode and the company’s outside counsel refused to recognize her actions or provide the requested corporate records. Kathleen Allman subsequently expanded the board, appointed new directors and, at a July 24 board meeting, voted to remove De Bode from all company positions while appointing herself chair and interim CEO.
The filings characterize Kathleen Allman’s leadership as transitional rather than permanent, arguing that her objective is to stabilize governance while the board searches for Nathan Allman’s long-term successor and ensure the business continues operating without interruption.
The estate is seeking an expedited ruling because uncertainty over who controls the company could affect contracts, expenditures, equity issuances and other corporate decisions, the filings said.
The court has not ruled on the allegations, and the filings reflect only the estate’s version of events.
The Ondo Board of Directors said in a separate emailed statement that it “remains committed to our founder Nate Allman’s belief that onchain markets are the future of finance. We are focused on serving our community without interruption, and empowering our people to maintain our momentum, as we search for his successor.”
Crypto World
After Major Loss, Crypto PACs Put $1.5M Into 3 US State Races
Fairshake-affiliated political action committee groups have reported fresh ad spending aimed at congressional races in several states after a loss in Michigan earlier this week, according to Federal Election Commission (FEC) filings.
As of Thursday, Defend American Jobs and Protect Progress—two Fairshake-connected entities—disclosed more than $1.5 million combined on media advertising supporting candidates in Florida, Alaska, and Wyoming. The spending comes shortly after Protect Progress suffered a primary setback in Michigan’s 13th district, following more than $2 million in earlier advertising for the candidate who ultimately lost.
Key takeaways
- Fairshake PAC affiliates Defend American Jobs and Protect Progress reported spending over $1.5 million on election ads in Florida, Alaska, and Wyoming, per FEC filings.
- Alaska’s at-large district: Defend American Jobs spent more than $500,000 supporting Rep. Nick Begich ahead of a primary scheduled for Aug. 18.
- Florida and Wyoming races were also targeted, including spending for Republican candidates running in primaries set for Aug. 18.
- The new ad activity follows a Michigan primary loss for a Protect Progress-supported candidate, after the group spent more than $2 million earlier.
- The spending underscores ongoing efforts by Fairshake and crypto-aligned groups to influence U.S. politics around proposed market-structure legislation.
Fairshake affiliates pivot to other primaries
Federal Election Commission disclosures show that Fairshake-linked entities Defend American Jobs and Protect Progress—cited in the FEC records as PAC affiliates—spent a combined $1.5 million on ads backing both Republican and Democratic candidates.
In Alaska’s at-large congressional district, Defend American Jobs spent more than $500,000 on media supporting the re-election of Representative Nick Begich. The filings also show roughly similar levels of advertising for GOP candidate Sydney Gruters in Florida’s 16th district and for Representative Harriet Hageman, who is running for a Wyoming Senate seat expected to be vacated by Cynthia Lummis.
Florida’s 16th district, Alaska’s at-large contest, and the Wyoming Senate race all face primaries scheduled for Aug. 18, according to the reporting described in the article.
Michigan loss highlights the stakes for crypto-backed advocacy
The new expenditures follow a primary loss in Michigan’s 13th Congressional District. Earlier this week, Democratic incumbent Shri Thanedar lost a primary to State Representative Donavan McKinney after Protect Progress had spent more than $2 million on media supporting Thanedar, the earlier coverage cited in the article notes. Thanedar’s current term ends in January 2027.
For crypto-aligned PAC operations, the contrast between large ad buys and outcomes in primaries is a reminder that political advertising is not a guaranteed lever—even for well-funded groups. The Michigan result also illustrates how quickly spending strategies can shift once a race turns unexpectedly.
Who received support—and how voting records factor in
On the Democratic side, Protect Progress reported spending more than $50,000 on media supporting Lois Frankel’s re-election in Florida’s 23rd district. The article states that Frankel, Begich, and Hageman all voted in favor of the GENIUS Act and CLARITY Act while serving in Congress.
By contrast, the filings discussed for Sydney Gruters did not indicate public crypto-related positions beyond participation in a questionnaire process overseen by the advocacy organization Stand With Crypto. According to the article, Gruters stated in that questionnaire that she supports the crypto market structure bill.
That distinction—between candidates with clear legislative voting records on one hand and candidates whose support is supported primarily by advocacy questionnaires on the other—helps explain why crypto-aligned groups may tailor messaging and funding even when the broader policy objective is the same.
Campaign spending ramps up around market-structure bills
The reported expenditures fit into a broader pattern of election-focused activity by Fairshake and groups aligned with the cryptocurrency industry. The article notes that in the 2024 election cycle, Fairshake-related spending reached more than $170 million across House and Senate races, potentially influencing the composition of the current Congress.
Just as importantly, the article frames these ad buys in the context of crypto market-structure legislation—particularly the Digital Asset Market Clarity (CLARITY) Act—whose future congressional action could shape how industry groups approach the 2026 midterms.
While it was unclear as of Thursday whether the U.S. Senate would vote on the CLARITY Act before a month-long recess, the way lawmakers cast votes on the bill could determine whether crypto-aligned organizations actively back or oppose particular candidates ahead of re-election contests.
The article also points to earlier outreach from Stand With Crypto in which it described a “primary goal” for 2026: advancing crypto market structure legislation. It further notes that Stand With Crypto rates political candidates based on their record of support or opposition, using public statements and voting history—information that PACs and allied groups may rely on when deciding where to allocate resources.
What to watch next in U.S. crypto politics
With primaries on Aug. 18 and the CLARITY Act’s potential Senate vote still uncertain, investors and builders in the crypto space may want to track not only which candidates are winning races, but also how congressional voting records and public commitments evolve—since those signals may influence how aggressively Fairshake-linked groups and crypto-aligned organizations deploy funding into the 2026 election cycle.
Crypto World
Robinhood Chain's DEX Volume Fell 72% While Transactions And Deposits Set Records
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Robinhood Chain's decentralized exchange volume fell 72.5% between its Jul. 11 peak and Aug. 1, but every other headline metric on the chain kept climbing through the drop. While transactions, total value locked and stablecoin supply are all at record highs, the size of the average trade collapsed…. Read the full story at The Defiant
Crypto World
Bitcoin Network Warning: Developers Find Nearly 5,000 Vulnerabilities
Volunteer developers filed 4,962 security findings across 390 Bitcoin projects in about 30 hours. Of the 391 codebases they reviewed, exactly one came back clean.
The group calls itself the Bitcoin Red Team. It rated 720 of those findings high or critical. Only 147 have reached the maintainers who have to fix them.
Every 1 in 7 Findings is Serious
The severity split is narrower than the raw total suggests. Reviewers logged 85 critical issues and 635 high ones.
That works out to 14.5% of everything filed. The rest sit in medium, low, or informational buckets. Another 246 findings carry no severity label at all.
Evidence quality varies too. About 21.4% came with working proof-of-concept code. Roughly 91% arrived through automated scanning. Reviewers retired just eight as false positives.
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One Hour Produced 83% of the Findings
The 30-hour framing needs a caveat. A single hour absorbed 4,101 findings. That spike was a backfill, not live scanning. Rob Hamilton, chief executive of Bitcoin insurer AnchorWatch, ran his own review before the campaign formally began.
He said he spent over $10,000 scanning more than 100 libraries.
Strip the dump out, and the pace changes sharply. Roughly 840 findings were received over the other 29 hours. That is closer to 29 an hour than the 166.3 the report advertises.
The Data Points Away From Hardware Wallets
The category breakdown carries a surprise. Hardware wallets and firmware, the group Coldcard belongs to, ranked second lowest for serious flaws at 9.6%.
Other corners fared worse. Mining pools hit 21.7%, infrastructure and tooling 21.5%, and swaps and exchanges 20.9%. Privacy tools topped the table at 24%, though reviewers covered only three of them.
Crypto libraries carried the volume instead. They produced 1,385 findings across 128 projects, more than a quarter of the corpus.
Calle, the pseudonymous physicist who created the Cashu ecash protocol, said maintainers are confirming the worst reports.
Most of the critical reports we’ve made so far were quickly verified by project owners. We know we’re hitting real targets,” they wrote.
Why the Red Team Formed After Coldcard
The sweep began because of one broken chip. Coinkite disclosed on July 30 that seed generation on affected Coldcard devices fell back to a predictable software routine.
The shortfall was severe. Only 32 bits came from the secure element, capping an attacker’s search at about 4.3 billion guesses.
Galaxy Research pegged confirmed thefts at 1,596 Bitcoin (BTC) from roughly 7,300 addresses on Aug. 4. A suspected fourth attack wave would bring the total to nearly $130 million. Galaxy stresses its address list is not definitive.
The panic showed up on-chain, where active addresses spiked to a 20-month high. Korean holders largely escaped because dice-based seeds are common there.
Weak randomness keeps returning in Bitcoin, however. The 2023 Milk Sad bug seeded Libbitcoin Explorer keys from 32 bits of clock time. In May, the Ill Bloom vulnerability drained $5.7 million from wallets built on a weak JavaScript generator.
Funding Follows the Findings
OpenSats, a nonprofit that funds Bitcoin development, launched a Code RED grant track on Thursday. It pays researchers who disclose flaws. It also refunds the artificial intelligence (AI) bills the work runs up.
Meanwhile, Bitcoin traded near $64,396 on Thursday, up 0.5% over 24 hours. The audit has not moved the market.
Context still matters for the raw number. These are findings, not confirmed exploits, and most will never be weaponized.
On the evidence so far, though, Coldcard was not an isolated failure. The data also suggests the next one will not be a hardware wallet.
The post Bitcoin Network Warning: Developers Find Nearly 5,000 Vulnerabilities appeared first on BeInCrypto.
Crypto World
Google Gemini AI Predicts Most Likely Bitcoin Price by End of 2026
Six separate forces must align for Bitcoin to double from here. Google Gemini AI predicts they will, and its price prediction calls for $120,000 to $150,000 before 2026 closes.
Accelerating global M2 money supply growth tops that list. Central bank interest rate cut cycles follow close behind.
Then comes the delayed supply squeeze from the post-halving issuance deficit. New coins arrive more slowly while demand keeps building.
Expanding institutional spot ETF allocations add steady bid pressure. Emerging momentum in sovereign strategic reserves brings a buyer class that did not exist a few years ago.

Impending legislative clarity on the market is the final piece. Gemini treats the combination as a confluence rather than any single trigger.
The bear scenario is framed as minor. Inflation sticky enough to delay rate cuts would remove the monetary tailwind entirely.
Unexpected regulatory enforcement friction could do similar damage. Temporary spot ETF net outflows round out the risks.
Any of those stalling momentum would test a deeper support zone around $48,000 to $55,000. Gemini AI still argues that leverage has largely been flushed out already.
Long-term institutional holders continue absorbing sell pressure. That skews structural risk and reward toward aggressive expansion into new high-water marks.
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Bitcoin Price Prediction: Six Tailwinds And The Question Of Whether Bitcoin Waits For Them
The daily chart tells a rougher story than the forecast. Bitcoin peaked near $126,000 in October and lost ground for months. February brought the violent part of the decline. Price broke from roughly $90,000 down to $60,000 in a matter of weeks.
Spring produced a genuine recovery attempt toward $82,000 by May. June erased it, dragging Bitcoin back near $58,000.
Since then, the market has carved out a base. July and August have formed a series of higher lows with little conviction on the upside.
The latest close is $64,858, up 1.25% and $801 on the day. The session ranged from $63,820 to $64,862. Support sits at $60,000 first and $58,000 at the June floor. Resistance shows up at $68,000, then $72,000 and $76,000.
RSI reads 54.39 with its signal line at 49.58. The 5-point gap places momentum slightly on the bullish side of neutral. Both readings sit near the middle of the range. Nothing here suggests exhaustion in either direction.
Gemini needs roughly a double from this base. The chart is not there yet, though a monthly close above $68,000 would be the first real evidence.
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Analyst Predicts 1,700% LDO Rally From Long-Term Support
Analyst Crypto Patel said on August 6 that Lido DAO’s LDO token could recover more than 1,700% after falling nearly 94% from its previous all-time high.
The market watcher believes LDO is sitting in a high-risk accumulation zone but warned that the token’s bearish structure remains intact until it reclaims major resistance levels.
LDO Tests Multi-Year Support After Heavy Sell-Off
Crypto Patel’s analysis on X placed LDO inside a long-term demand area after its decline from the previous cycle peak near $4.
“Everyone Forgot About $LDO After A -94% Crash,” he wrote. “The Long-Term Recovery Potential From Here Could Exceed 1,700%.”
The token is currently trading around $0.29, close to the analyst’s proposed accumulation zone between $0.275 and $0.24.
He said that LDO is still inside a multi-year descending channel, with price action still showing lower highs and lower lows. A weekly close below $0.23 would invalidate the current setup, while a move above $0.47 would be needed to signal a possible trend change.
The token’s recent weakness has been linked to concerns around Ethereum’s proposed EIP-8361. Developer Jerome de Tychey said on August 5 that the proposal aims to prevent staking from rising without limits.
Analyst Ted Pillows suggested that LDO’s decline was likely connected to fears that lower ETH fstaking rewards could reduce demand for liquid staking tokens such as stETH.
“$LDO is selling off because of concerns around Ethereum’s EIP-8361 proposal,” Pillows wrote on X.
He added that the proposal is still an early draft and has a long process before any possible implementation.
Lido has also had to deal with changing conditions across Ethereum staking. As CryptoPotato reported last month, the platform started moving around $16 billion worth of staked ETH onto larger post-Pectra validators, with the idea being that Lido’s curated node operators stop running thousands of identical 32 ETH validators and collapse them into fewer, bigger ones.
Case for a Longer-Term Bottom
LDO is currently about 25% above the $0.235 low it hit on June 25, a level that replaced its previous floor and now marks the bottom of its five-year trading history since launching in 2021 at an all-time high near $7.30.
In the last seven days, it has fallen close to 18% and is down roughly 27% over the past two weeks, according to CoinGecko. Furthermore, trading volume sits near $50 million, down 43% from the previous day.
The bullish case hinges on LDO reclaiming $0.47 on a weekly closing basis, a level that flipped from support to resistance after a breakdown in 2024. From there, Crypto Patel maps out targets at $1.50, $2.50, and eventually back toward the token’s old cycle high near $4, the move that would produce the kind of gain he’s describing. He points to Lido’s continued lead in Ethereum liquid staking and the shrinking token supply left to unlock as reasons the setup could work if ETH climbs back above $3,000.
The post Analyst Predicts 1,700% LDO Rally From Long-Term Support appeared first on CryptoPotato.
Crypto World
The Quiet Miracles of Ordinary Life in New Syria
What do we talk about in Syria?
What was changing in Syria was not only what people were able to do, but what they were able to say. The shroud of silence and fear that enveloped Syria throughout the Assad decades was gone. Syrians were, finally, speaking freely about those dark decades.
In Hama, a city 130 miles north of Damascus, I visited the atelier of one of the last traditional weavers in the city. We drank coffee as he told stories of February 1982, when Hafez al-Assad put the rebellious city under siege and the regime’s army killed tens of thousands in a single month. Others in the shop shared stories of entire families being killed together in their homes. What felt radical was that we were in Hama, openly speaking about the stories of Hama.
In Aleppo, which is 220 miles northwest of Damascus, a kind man sitting next to me at dinner casually recounted how he and his wife—both were jailed for opposing Assad during the revolution—had survived. Their survival and our ability to speak openly about the brutal past felt miraculous. I teared up listening to them. I couldn’t get over what it meant to hear these stories exactly where they had happened. Just being there, bearing witness together, speaking and listening without fear or filter seemed to loosen some of the pain trapped inside us. In Hama, the wounds are 44 years old; the city was hollowed out, every family touched by loss. In Aleppo, in the suburbs of Damascus, across Syria, people and neighborhoods heaved under the trauma of the last 14 years. Thousands of families are still searching for answers about their loved ones—more than 100,000 of whom had disappeared under Assad’s rule.
Crypto World
What are Telegram trading bots? How they work
Telegram trading bots let users buy and sell tokens directly from a chat interface. This guide explains how they work, which bots dominate the market, and what risks come with handing a bot your private key.
Summary
- Telegram trading bots are automated tools that connect to decentralized exchanges through the Telegram messaging app, letting users swap tokens, snipe new listings, and set limit orders without using a traditional wallet interface
- The leading bots by volume include Banana Gun, Maestro, Unibot, BONKbot, and Trojan, each handling hundreds of millions of dollars in weekly trading volume across Ethereum, Solana, and Base
- These bots generate revenue through transaction fees, typically charging 0.5% to 1% per trade on top of the standard DEX swap fees and network gas costs
- The primary convenience is speed: a trader can paste a contract address into a Telegram chat and execute a buy in under two seconds, compared to the 15 to 30 seconds required to navigate a DEX interface manually
- The primary risk is custody: most Telegram bots generate a wallet for the user and hold the private key on their servers, meaning a bot compromise could result in total loss of funds
Telegram trading bots emerged in 2023 as a response to a specific problem in decentralized finance: the gap between the speed at which opportunities appear and the speed at which a human can execute a trade through a conventional DEX interface. When a new token launches on Uniswap or Raydium, the first buyers often capture the largest gains. By the time a trader opens their browser, connects their wallet, approves the token contract, sets slippage, and confirms the transaction, the price may have already moved 50% or more.
Telegram bots compressed that entire workflow into a single message. Paste a contract address, tap a button, and the bot submits the transaction on your behalf. The interface is a chat window. The execution happens on-chain. The speed advantage turned what started as a niche tool for memecoin traders into an infrastructure layer that now processes billions of dollars in monthly volume.
This guide explains how these bots work under the hood, which ones dominate the market, what they cost, and where the risks hide.
How Telegram trading bots work
A Telegram trading bot is a program that runs on a server, connects to one or more blockchain networks, and accepts commands through the Telegram Bot API. When a user starts a bot for the first time, the bot generates a new crypto wallet (a public-private key pair) and associates it with the user’s Telegram account. The user funds this wallet by sending tokens to the generated address.
Once funded, the user can trade by sending commands to the bot. The most basic command is a buy: the user pastes a token contract address, selects an amount, and the bot constructs a swap transaction on the relevant decentralized exchange, signs it with the user’s private key, and broadcasts it to the network. The entire process typically completes in one to three seconds on Solana and three to ten seconds on Ethereum, depending on network congestion.
The bot handles several technical steps that would otherwise require manual interaction. It automatically detects which DEX has liquidity for the token. It calculates the optimal route through liquidity pools, sometimes splitting the trade across multiple pools to reduce price impact. It sets gas parameters to prioritize transaction inclusion. On Ethereum, many bots integrate with block builders and private mempools to avoid sandwich attacks, a form of MEV (maximal extractable value) that front-runs and back-runs a user’s trade to extract profit.
The user interface is entirely within Telegram. Buttons replace the connect-wallet and approve-token steps of a traditional DEX. Portfolio tracking, profit and loss calculations, and token watchlists are all presented as inline messages or callback buttons within the chat.
The major Telegram trading bots
The Telegram bot landscape has consolidated around a handful of dominant platforms, each with different strengths.
Banana Gun is the highest-volume Telegram trading bot as of mid 2026. It operates on Ethereum, Solana, Base, and Blast. Banana Gun is known for its sniping capabilities: the ability to detect a new token listing and execute a buy transaction in the same block as the liquidity addition. The bot charges a 0.5% fee on manual buys and a 1% fee on snipes. Banana Gun processed more than $8 billion in cumulative trading volume in its first year of operation and has generated hundreds of millions in fee revenue, a portion of which is distributed to holders of the BANANA token.
Maestro was one of the earliest Telegram trading bots, launching on Ethereum before expanding to Solana and other chains. Maestro offers sniping, limit orders, copy trading (automatically mirroring the trades of a specified wallet), and anti-rug protection that attempts to detect and front-run liquidity removals. Its fee structure is 1% per transaction.
Unibot launched in mid 2023 and was among the first bots to gain significant traction. It pioneered the revenue-sharing model where a percentage of trading fees is distributed to token holders. Unibot operates primarily on Ethereum and introduced features like private transactions routed through Flashbots to protect against MEV. Trading fees are 1% for non-token-holders and 0.5% for UNIBOT holders.
BONKbot is the dominant Telegram trading bot on the Solana network. Named after the BONK memecoin community, BONKbot specializes in Solana token trading and benefits from Solana’s low transaction fees and fast confirmation times. A trade on BONKbot costs a fraction of a cent in network fees compared to several dollars on Ethereum, making it the preferred tool for high-frequency memecoin trading where traders execute dozens of small trades per day.
Trojan emerged as a competitor to BONKbot on Solana, differentiating itself through a cleaner interface and additional features such as DCA (dollar-cost averaging) orders and multi-wallet management. Trojan has grown rapidly and regularly competes with BONKbot for the top position in Solana trading volume.
What Telegram bots actually cost
The total cost of a Telegram bot trade includes three components: the bot fee, the DEX swap fee, and the network gas fee.
The bot fee is the primary revenue source for the bot operator. It typically ranges from 0.5% to 1% of the trade value. On a $1,000 trade, this means $5 to $10 goes to the bot.
The DEX swap fee is paid to liquidity providers on the underlying decentralized exchange. On Uniswap V3, this is typically 0.3% for established tokens and 1% for newer, lower-liquidity tokens. On Raydium (Solana), the standard fee is 0.25%.
The network gas fee varies dramatically by chain. On Ethereum, a swap transaction costs $3 to $15 depending on network congestion. On Solana, the same transaction costs less than $0.01. On Base, gas fees typically fall between $0.01 and $0.10.
Adding these together, a $1,000 trade on Ethereum through a Telegram bot with a 1% fee costs roughly $10 (bot fee) + $3 (DEX fee at 0.3%) + $5 to $10 (gas) = $18 to $23. The same trade on Solana costs roughly $10 (bot fee) + $2.50 (DEX fee) + $0.01 (gas) = $12.51. These costs are meaningful for small trades. A $100 trade on Ethereum through a Telegram bot loses 18% to 23% of its value to fees before any price movement occurs.
The fee economics explain why Telegram bot trading has concentrated on Solana, where the low gas costs make small, frequent trades economically viable. On Ethereum, Telegram bot trading is more practical for larger position sizes where the fixed gas cost represents a smaller percentage of the trade.
Sniping and launch trading
Sniping is the feature that originally drove adoption of Telegram trading bots. When a new token launches on a DEX, the token creator adds liquidity to a pool. The first trades against that liquidity get the lowest prices. Sniping bots monitor the blockchain for liquidity addition transactions and attempt to place a buy order in the same block.
The technical mechanics differ by chain. On Ethereum, snipers use private transaction channels such as Flashbots or MEV Blocker to submit transactions directly to block builders, bypassing the public mempool where they could be front-run. The bot must predict the exact block in which liquidity will be added and submit a transaction with sufficient gas priority to be included immediately after the liquidity transaction.
On Solana, sniping works differently because the network uses a leader-based block production model rather than a mempool auction. Bots connect to multiple RPC nodes and submit transactions with optimized compute budgets to maximize the probability of early inclusion. The speed competition on Solana is measured in milliseconds, and the leading bots invest heavily in infrastructure co-located with Solana validators. Some bots maintain dedicated connections to multiple validator operators, paying for priority access that shaves tens of milliseconds off submission times. The infrastructure arms race mirrors the high-frequency trading competition in traditional finance, where firms spend millions on co-location and network optimization to gain microsecond advantages.
Sniping carries substantial risk. Many new token launches are scams, rug pulls, or honeypot contracts that allow buying but prevent selling. A successful snipe on a fraudulent token results in a total loss. The anti-rug features offered by bots like Maestro attempt to simulate a sell transaction before executing the buy, checking whether the token contract allows selling. However, sophisticated scam contracts can pass these checks and then enable restrictions after a set number of blocks or a specific volume threshold.
The custody problem
The most significant risk of Telegram trading bots is the custody model. When a user creates a wallet through a Telegram bot, the bot generates the private key and stores it on its servers. The user receives the public address and sometimes can export the private key, but the bot retains a copy.
This means the bot operator has full access to every wallet created through the platform. If the bot’s servers are compromised, every user’s funds are at risk. If the bot operator decides to act maliciously, they can drain every wallet simultaneously. This is the exact opposite of the self-custody principle that decentralized finance was built to enable.
Several Telegram bots have experienced security incidents. In September 2023, Maestro experienced an exploit through a vulnerability in its token approval router contract, resulting in approximately $280,000 in user losses. The bot reimbursed affected users, but the incident highlighted the concentrated risk. In late 2023, Unibot experienced a contract exploit that affected users who had granted token approvals through the bot.
The practical advice for managing this risk is straightforward: treat the Telegram bot wallet as a hot wallet with limited funds. Transfer only the amount needed for immediate trading. Move profits to a hardware wallet or self-custody solution regularly. Never store a significant portion of your portfolio in a Telegram bot wallet. Some traders set a hard rule: never keep more than they can afford to lose entirely in the bot wallet.
Some newer bots have introduced partial mitigations. A few support connecting external wallets through WalletConnect, so the user retains custody of the private key and approves each transaction through their own wallet app. This approach sacrifices speed (each trade requires a manual approval step) but eliminates the custody risk. The tradeoff reflects the fundamental tension in Telegram bot trading: speed and convenience on one side, security and self-custody on the other.
The custodial risk is compounded by the lack of regulatory oversight. Traditional exchanges that hold customer funds are subject to licensing requirements, capital reserves, and regular audits. Telegram trading bots operate outside these frameworks entirely. There is no deposit insurance, no regulatory body to file complaints with, and no legal obligation for the bot operator to maintain solvency or segregate user funds. Users are trusting anonymous or pseudonymous teams with their private keys, and the only recourse in the event of a loss is whatever goodwill or reputational incentive the bot operator feels.
Revenue, tokens, and the bot economy
Telegram trading bots have created a new category of crypto revenue-generating businesses. The fee revenue is substantial: Banana Gun alone has generated more than $100 million in cumulative fees. Several bots have issued tokens that entitle holders to a share of the fee revenue, creating a form of equity-like exposure to the bot’s trading volume.
The token economics vary by project. Banana Gun distributes a percentage of trading fees to BANANA token holders who stake their tokens. Unibot distributes a share of fees to UNIBOT holders. The yield depends on trading volume, which is highly correlated with market sentiment. During bull markets and memecoin frenzies, daily fee revenue can spike by ten times or more. During quiet markets, revenue can drop to a fraction of peak levels.
This volume sensitivity makes Telegram bot tokens among the most volatile assets in crypto. UNIBOT rose from $3 to $200 during its initial hype cycle in 2023, then declined more than 90% before finding a lower range. BANANA experienced similar volatility. Traders who buy bot tokens are effectively making a leveraged bet on future DEX trading volume, particularly memecoin trading volume, which has historically been the most cyclical segment of the crypto market.
The competitive dynamics are intense. Bots compete on speed (fastest execution wins the sniping market), fees (lower fees attract volume-sensitive traders), features (copy trading, limit orders, DCA), and chain coverage (supporting more chains captures more trading activity). The low barriers to entry mean new bots can launch quickly, but the network effects of user adoption and the infrastructure investment required for competitive sniping speeds create meaningful advantages for established players.
The relationship between Telegram bots and decentralized exchange volume is symbiotic. Bots route a significant share of total DEX volume, particularly on Solana where BONKbot and Trojan together have accounted for more than 30% of all Raydium swap volume during peak memecoin periods. This makes bots a critical distribution layer for DEXs, and some DEX protocols have begun offering fee rebates or priority routing to the highest-volume bots. The arrangement benefits both sides: bots get better execution for their users, and DEXs get more volume and fees.
What this does not cover
This guide does not cover the legal and regulatory status of Telegram trading bots, which remains unclear in most jurisdictions and may evolve as regulators examine unregistered trading platforms. It does not cover the specific token contract risks of memecoin trading, including honeypot contracts, hidden mint functions, and transfer tax manipulation, which are the most common causes of loss for Telegram bot users. It does not cover the broader MEV landscape beyond its relevance to Telegram bot users, nor the technical details of Solana validator operation or Ethereum block building that underpin the sniping infrastructure.
Practical checks before using a Telegram trading bot
Check the bot’s track record. Search for past security incidents, contract exploits, or reports of fund losses. A bot that has been operating for more than 12 months without a major incident has passed a meaningful stress test, though past safety does not guarantee future safety.
Check the fee structure. Calculate the total cost of a round-trip trade (buy and sell) including bot fees, DEX fees, and gas on the specific chain you plan to trade. If the total cost exceeds 3% to 5% of your trade size, the fee drag will make it very difficult to trade profitably.
Check the custody model. Determine whether the bot generates and holds your private key, or whether it supports external wallet connections. If the bot holds your key, plan your fund management accordingly and never keep more in the bot wallet than you are prepared to lose.
Check the withdrawal process. Before trading, test a small withdrawal to confirm that you can move funds out of the bot wallet to an external address without delays or restrictions.
Check the bot’s social channels. Active developer communication, regular updates, and transparent incident response are positive signals. A bot with no public developer presence or communication channel is a higher risk.
Are Telegram trading bots legal?
The legality depends on jurisdiction. In most countries, using a bot to trade on decentralized exchanges is not explicitly prohibited, but the bots themselves may be operating as unregistered broker-dealers or money transmitters. Users should research their local regulations before using these tools.
Can I lose all my money using a Telegram trading bot?
Yes. The two most common ways to lose everything are trading a scam token (honeypot or rug pull) and a bot security breach where the private key is compromised. Limiting the funds stored in the bot wallet reduces the maximum loss from a security breach.
Which Telegram trading bot is best for beginners?
BONKbot on Solana is often recommended for beginners because Solana’s low gas fees make experimentation cheap. A failed trade on Solana costs less than a cent in gas, compared to several dollars on Ethereum. The lower cost of mistakes allows beginners to learn without significant fee-related losses.
How do Telegram trading bots make money?
Through transaction fees, typically 0.5% to 1% per trade. Some bots also earn revenue through priority transaction routing, where they charge additional fees for guaranteed fast execution during high-demand periods such as token launches.
Can Telegram bots protect me from rug pulls?
Some bots offer anti-rug features that simulate sell transactions before executing buys, check for blacklisting functions in the token contract, or monitor for liquidity removal events. These protections catch basic scams but cannot detect sophisticated exploits or delayed rug mechanisms. No bot can guarantee protection against all forms of token fraud.
Do I need to pay taxes on Telegram bot trades?
In most jurisdictions, yes. Each swap is a taxable event, and the high-frequency nature of Telegram bot trading can create dozens or hundreds of taxable transactions per day. Most bots do not provide tax reports, so users need to export their wallet transaction history and use third-party tax software to calculate their obligations.
What is the difference between sniping and copy trading?
Sniping targets new token launches, attempting to buy in the same block as the initial liquidity. Copy trading replicates the trades of a specified wallet address in real time. Sniping is a speed competition against other bots. Copy trading is a strategy that relies on the skill of the wallet being copied.
Can I use multiple Telegram trading bots at the same time?
Yes. Many traders use different bots for different chains or strategies. A common setup is BONKbot or Trojan for Solana memecoin trading and Banana Gun for Ethereum sniping. Each bot generates its own wallet, so funds must be distributed across multiple wallets accordingly.
Disclaimer
This article is for informational purposes only and does not constitute financial or investment advice. Cryptocurrency investments carry significant risk, and you should conduct your own research before making any investment decisions. Information is accurate as of August 6, 2026.
Crypto World
Bitcoin Miners’ AI Move Fails to Impress Wall Street Investors
Bitcoin miners are increasingly positioning themselves as providers of artificial intelligence infrastructure and high-performance computing capacity, but the stock-market reaction to fresh AI hosting deals has cooled markedly in the past couple of years. New research suggests that while contract values are growing, investors are paying less attention to the headline announcement and more attention to what happens next—execution, funding, and long-term profitability.
According to an analysis by Blocksbridge Consulting published in TheEnergyMag’s Miner Weekly, deals tied to AI infrastructure have become less “market-moving.” The report reviewed 25 AI and HPC infrastructure contracts announced between June 2024 and August 2026, finding that the average stock move on announcement day fell from roughly 24% for the earliest deals to about 10% for the most recent ones. Median gains also declined by around half over the same period, even as the reported size and value of the contracts increased.
Key takeaways
- Blocksbridge Consulting’s review shows AI/HPC deal announcement-day reactions weakening from ~24% average moves to ~10% in later deals.
- Median gains from these announcements dropped by about half despite larger contract sizes, implying investors value execution more than upfront figures.
- Revenue per contracted megawatt has inched higher over time, suggesting AI hosting agreements are becoming more financially attractive.
- Major early wins for miners tied to notable AI counterparties produced sharp stock jumps, while newer mega-deals have generated smaller, shorter-lived reactions.
- Investor caution is also visible in infrastructure-focused indices, with TheEnergyMag’s TEM AI Infrastructure Growth Index down ~28.5% from its June peak.
Why AI-hosting news is moving stocks less
The central takeaway from the Blocksbridge Consulting analysis is not that AI hosting deals are shrinking—they appear to be growing in economic importance—but that markets have started to anticipate them. As more miners and infrastructure providers offer similar propositions, investors may treat new contracts as incremental confirmation rather than a sudden re-rating of business prospects.
The report points to a nuanced shift. On one hand, annualized revenue per contracted megawatt has edged upward across the sample, an indicator that AI hosting agreements may be improving in value. On the other hand, the reduced market reaction suggests that investors now scrutinize the substance behind those deals: whether capacity can be delivered on time, how projects are financed, and how durable profitability will be once contract ramp-ups and operational costs are accounted for.
In other words, it’s possible for deals to be economically better while still failing to trigger the same stock enthusiasm as earlier announcements—because expectations adjust. When investors believe execution risk is either higher or more variable than the market used to assume, the “surprise” embedded in contract headlines becomes smaller.
Early deal spikes versus muted mega-deal reactions
The difference between early and later announcements stands out in examples cited alongside the Blocksbridge Consulting findings. According to the report’s examples, initial agreements connected to AI infrastructure sparked dramatic moves for certain miners and hosting operators.
Core Scientific’s initial hosting agreement with CoreWeave reportedly pushed its shares up by more than 40%. Applied Digital’s first CoreWeave lease gained nearly 49%, while TeraWulf’s first Fluidstack deal surged almost 60%.
But as the market has absorbed similar news, later mega-deals have tended to elicit more modest reactions. TeraWulf’s 401-megawatt lease with Anthropic lifted its shares by about 5%. CleanSpark’s $6.6 billion AI hosting agreement reportedly gained nearly 9%. Bitdeer’s new Tydal contract briefly pushed its stock up roughly 12%, but the gains reportedly faded by the close.
That pattern fits the report’s broader conclusion: investors appear more likely to react to earlier “proof points” and less likely to reprice rapidly when a company announces a larger continuation of an established AI hosting strategy. For traders and portfolio managers, the implication is straightforward—volatility around announcements may be structurally lower than it was during the market’s earlier phase of AI infrastructure discovery.
Indexes show momentum slowing, not demand disappearing
The cooling enthusiasm is also reflected beyond individual stock moves. The TheEnergyMag TEM AI Infrastructure Growth Index—tracking publicly traded companies developing AI data center and digital infrastructure businesses—has reportedly fallen about 28.5% from its June peak, even though the index remains sharply higher than a year earlier. The implication is that investors have not abandoned the sector, but they have reduced the intensity of the chase.
The same article notes that the slowdown in these AI infrastructure equities has mirrored broader risk appetite. It cites the Philadelphia Semiconductor Index falling nearly 17% from its July peak, suggesting that part of the recent softness could be tied to sector-wide sentiment rather than purely idiosyncratic execution concerns for specific mining or hosting players.
For Bitcoin miners that have broadened into AI workloads and high-performance computing, this matters because their ability to convert new contracts into steady earnings depends not only on deal economics, but also on the capital markets environment. When AI infrastructure equity momentum slows, lenders and equity investors often become more selective about who can finance expansions and meet delivery timelines—exactly the areas the Blocksbridge analysis implies investors are emphasizing more now.
What investors should watch next
If the market is indeed moving toward a more “disciplined” pricing of AI hosting deals, the next signals will likely be less about the size of the headline contract and more about execution milestones: ramp schedules, delivery progress, and evidence that annualized megawatt economics can hold up as contracts scale. Readers should watch whether announcement-day reactions continue to weaken as deals become more common, or whether new structures—potentially with clearer financing and delivery frameworks—can restore stronger sentiment.
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