Solana Foundation CISO Warns AI Is Making Crypto Scams More Convincing

bitcoinistPublished on 2026-08-03Last updated on 2026-08-03

Abstract

Solana Foundation's Chief Information Security Officer, Michael Coates, warns that AI is making crypto scams significantly more convincing by enhancing social engineering, phishing, and voice impersonation tactics. The threat targets users and teams directly, not a flaw in blockchain technology itself. AI enables polished, personalized messages and convincing deepfakes, increasing the risk of irreversible financial losses from actions like approving malicious transactions. Coates emphasizes the need for "secure by default" systems across the crypto ecosystem, as traditional user-focused warnings are insufficient against sophisticated AI-driven deception. This includes safer wallet designs, clearer transaction approvals, and stronger internal team procedures like out-of-band verification and multi-signature controls. The warning applies broadly, as AI allows scammers to operate at scale with professional-looking attacks, necessitating a fundamental shift in security approaches beyond user vigilance.

Solana Foundation’s new Chief Information Security Officer, Michael Coates, has warned that AI is making crypto scams more convincing, especially through social engineering, phishing, and voice-based impersonation.

The warning is not about a flaw in Solana’s blockchain or smart contracts. It is about the way attackers target people.

That distinction matters.

Crypto security used to be discussed mostly in terms of code: smart contracts, bridges, wallets, private keys, and validators. Those are still important. But attackers increasingly go after the user, the employee, the founder, the moderator, or the support channel.

AI makes that easier because it can produce more realistic messages, voices, identities, and pressure tactics.

TL;DR

  • Solana Foundation CISO Michael Coates warned about AI-driven social engineering.
  • The risk is phishing, impersonation, and voice deepfakes.
  • This is not a claim that Solana’s blockchain itself has a security flaw.

Crypto Scams Are Becoming More Personal

The old scam email full of spelling mistakes is not the main threat anymore.

AI can write polished messages, imitate support staff, generate fake identities, create convincing voice calls, and adapt scripts to specific victims. That means users may face attacks that feel more personal and more believable.

In crypto, that is especially dangerous because mistakes can become irreversible.

If a user signs a malicious transaction, shares a seed phrase, installs fake software, or approves the wrong wallet connection, funds can move instantly. There is no chargeback, no simple password reset, and often no central authority that can reverse the transaction.

That makes social engineering a very high-impact attack vector.

Secure By Default Is The Right Goal

Coates’ emphasis on systems being secure by default is important.

Crypto has often placed too much responsibility on users. “Don’t click bad links” is good advice, but it is not enough when bad links look real, voices sound authentic, and fake support accounts respond faster than real ones.

Better design can help.

Wallets can make risky approvals clearer. Apps can reduce blind signing. Protocols can limit permissions. Exchanges can improve withdrawal controls. Teams can use internal verification steps for sensitive actions. Communities can reduce reliance on direct messages.

Security should not depend on every user being perfect every time.

AI raises the standard because it makes deception cheaper and more scalable.

Social Engineering Hits Teams Too

This is not just a retail-user issue.

Crypto teams are also targets. A convincing fake vendor, investor, journalist, applicant, or internal colleague can be used to compromise credentials, gain access to systems, or trick employees into approving transactions.

Voice deepfakes make this worse.

A team member may receive what sounds like a call from an executive asking for urgent action. In a fast-moving crypto environment, urgency can bypass normal checks.

That is why teams need procedures, not just awareness.

Out-of-band verification, multisig discipline, hardware keys, access controls, and strict treasury procedures all matter.

Solana’s Ecosystem Needs User-Level Security

Solana has attracted consumer apps, DeFi activity, meme coin trading, NFT history, payment experiments, and mobile-friendly tooling. That makes user-facing security especially important.

The more mainstream an ecosystem becomes, the more attackers target ordinary users.

A chain can be fast and technically sound, but users can still lose funds through fake mints, fake airdrops, malicious token approvals, impersonation accounts, or wallet-draining sites.

So the CISO warning is relevant beyond Solana. It applies to every crypto ecosystem.

The Scam Arms Race Is Accelerating

AI does not create fraud from nothing. It makes existing fraud more efficient.

Scammers can test messages faster, personalize attacks, generate realistic content, and operate at larger scale. Users and teams need to assume that scams will look increasingly professional.

That means crypto security has to move beyond telling users to “be careful.”

Products need safer defaults. Wallets need better warnings. Protocols need permission limits. Teams need stronger internal controls. Communities need trusted communication channels.

The next wave of crypto scams may not look obviously fake.

That is the warning.

This article is based on public comments from Solana Foundation CISO Michael Coates on AI-driven crypto scams.

This article was written by the News Desk and edited by Samuel Rae.

This report is based on information released in disclosures at primary source documentation.

Trending Cryptos

Related Questions

QAccording to Solana Foundation's CISO, what specific aspect of crypto scams is being made more convincing by AI?

AAccording to Solana Foundation CISO Michael Coates, AI is making crypto scams more convincing through social engineering, specifically by enabling more realistic phishing attempts, impersonation, and voice-based deepfakes.

QWhy does the article say social engineering is a particularly high-impact attack vector in the crypto space?

ASocial engineering is a high-impact attack vector in crypto because mistakes like signing a malicious transaction or sharing a seed phrase can lead to irreversible loss of funds, as there is typically no chargeback, password reset, or central authority to reverse the transaction.

QWhat shift in security focus does the article suggest is necessary in response to AI-enhanced scams?

AThe article suggests a shift from placing too much responsibility on users (e.g., telling them to 'be careful') towards designing systems to be 'secure by default' with safer product designs, clearer warnings, permission limits, and stronger internal controls for teams.

QBesides retail users, who else is identified as a target for AI-driven social engineering attacks in the crypto ecosystem?

ABesides retail users, crypto teams and their employees are also prime targets. Attackers may use convincing impersonations of vendors, investors, or colleagues to compromise credentials, gain system access, or trick employees into approving fraudulent transactions.

QWhat is the article's conclusion about the future appearance of crypto scams due to AI?

AThe article concludes that the next wave of crypto scams, accelerated by AI, may not look obviously fake. They will appear increasingly professional, personalized, and believable, making traditional advice like 'be careful' insufficient on its own.

Related Reads

In-depth: The Foreign Guest Genspark

The article "The Foreign Guest: Genspark" investigates the identity and business practices of AI startup Genspark, which presents itself as a Palo Alto-based "AI Costco" offering a subscription bundle of over 70 models and numerous AI agent tools. Despite its official Silicon Valley narrative, Genspark's founding team has deep roots in Chinese tech giant Baidu, a history systematically downplayed in its branding. The company actively cultivates an image as an elite US firm, heavily publicizing partnerships and endorsements from OpenAI, Anthropic, and Microsoft, while distancing itself from the Chinese AI community and obscuring its connections to Chinese investors and open-weight models (like those from DeepSeek, Moonshot AI, and MiniMax) that power its services. Genspark's core strategy involves rapidly cloning and integrating successful AI product concepts (e.g., from Perplexity, Manus, Plaud) into its unified platform, supported by aggressive marketing, including Super Bowl ads and paid native content in publications like The Wall Street Journal. Critically, the article suggests a significant portion of its engineering and product development is conducted by a team in Beijing, operating outside its official US corporate structure. This duality allows Genspark to leverage Chinese talent and models for efficiency and cost reduction while constructing a public facade as a purely American success story. The piece concludes that Genspark's most effective agent is its own corporate identity, meticulously engineered to obscure its Chinese underpinnings and be perceived solely as a Silicon Valley company.

marsbit2m ago

In-depth: The Foreign Guest Genspark

marsbit2m ago

Debate: Korean Workers Fear Unemployment, While Musk Envisions a Society 'Without Work'?

While South Korean auto workers fear job losses from robotics, Elon Musk envisions a future where AI and robots render most work optional. This article explores the growing tension between immediate anxieties over automation and long-term visions of a post-work society. The piece begins with recent strikes at Hyundai's Korean plants, where unions, amid standard wage negotiations, also sought job guarantees against advancing robotics—specifically mentioning Boston Dynamics' Atlas. This reflects how anxiety about technological displacement is emerging even before robots are fully capable of replacing skilled labor on assembly lines. The author argues that while current robotics still struggle with the nuanced, experiential knowledge of veteran workers, the *perception* of imminent replacement is fueling social conflict prematurely. This modern "Luddite" sentiment is compared to the 19th-century English textile workers who smashed machines. Historically, Luddites weren't simply anti-technology; they were protesting the rapid devaluation of their skills and the unequal distribution of productivity gains. Similarly, today's workers ask who will bear the cost of transition and share in the new wealth created by machines. In contrast, figures like Elon Musk propose an optimistic endpoint: with AI and robotics driving extreme abundance, the link between work and survival could break. He suggests concepts like "Universal High Income" could allow society to share the technological bounty, transforming work from a necessity into a choice. The core challenge, however, lies in the transition. The author notes that technology's benefits diffuse slowly, while its disruptive costs—job losses, skill obsolescence—can be concentrated and immediate. The risk is a painful interim period where productivity gains are captured by a few before new social contracts, safety nets, and retraining systems are established. The conclusion calls for proactive governance. Just as past industrial revolutions gave rise to labor standards and social safety nets, the robotics era needs its own frameworks. These should address job transition support, distribution of productivity gains, safety liability, and ethical deployment. Embracing such "constraints" is not opposition to progress but a necessary step to ensure technology benefits society broadly. The discussion sparked by Hyundai's workers, therefore, is not premature but essential.

marsbit15m ago

Debate: Korean Workers Fear Unemployment, While Musk Envisions a Society 'Without Work'?

marsbit15m ago

CATL Invests in a 00s Graduate from Harbin Institute of Technology

Contemporary Amperex Technology Co., Limited (CATL) has exclusively invested in the Pre-A round of RoboParty, a company founded by 22-year-old Huang Yi. A former student at Harbin Institute of Technology, Huang built a bipedal humanoid robot in his dorm room and later dropped out to launch RoboParty in Shanghai. The company focuses on developing a fully open-source platform for humanoid robots, combining self-developed hardware, operating systems (Party OS), and foundational models. RoboParty's strategy emphasizes open-source collaboration to accelerate development and build a developer ecosystem, positioning itself as foundational infrastructure for embodied AI. Since its 2025 founding, the team—composed largely of top-tier university graduates—has secured six funding rounds in eight months, with investors including Matrix Partners, Xiaomi, and now CATL. This investment by CATL's corporate venture arm signals strong industry confidence in RoboParty's potential for real-world manufacturing and complex scenarios. Huang Yi prioritizes technological excellence and developer community growth over rapid commercialization. The company has already garnered significant interest from developers and research institutions globally. With a focus on continuous, rapid iteration and open innovation, RoboParty aims to prove the versatility of humanoid robots and drive the field toward an open-source future.

marsbit18m ago

CATL Invests in a 00s Graduate from Harbin Institute of Technology

marsbit18m ago

Will SpaceX's First Quarterly Report Rescue Its Stock Price Under the Pressure of 1.2 Billion Shares Unlocking?

SpaceX is set to release its first quarterly earnings report since going public, a key test for its stock which has declined 20% from its IPO price. Approximately 9.12 billion shares are set to unlock on August 6, with an additional 3.19 billion following a week later, creating potential selling pressure from early investors. A strong report may be the only catalyst to reverse the downtrend. The report will cover three segments: Space, Connectivity (Starlink), and AI. The AI business, centered on the merged xAI, is the biggest uncertainty. While it generated $818 million in revenue last quarter, it also reported a $2.5 billion operating loss and $7.7 billion in capital expenditures. New data center rental agreements with Anthropic and Google, particularly the substantial $1.25 billion monthly deal with Anthropic, add significant revenue variability this quarter. Investors await guidance on AI's future outlook and the timeline for launching AI computing satellites via Starship. Starlink remains the stable profit driver, ending last quarter with 10.3 million subscribers. Key metrics will be user growth, average revenue per user (ARPU), and enterprise/government contract backlogs. The Space segment, which posted a $657 million operating loss last quarter, will be scrutinized for updates on Starship development following its 13th test flight and the pace of Falcon 9 launches, many of which support internal Starlink deployment. Wall Street expects Q2 revenue of around $6.9 billion and EBITDA of $2.1 billion. However, as this is the first earnings report, analyst forecasts lack a historical baseline and could see significant variance. With a current market cap of ~$1.4 trillion and a high valuation, the market's reaction post-earnings will hinge on the report's strength, the magnitude of post-lockup selling, and ongoing investor concerns.

marsbit18m ago

Will SpaceX's First Quarterly Report Rescue Its Stock Price Under the Pressure of 1.2 Billion Shares Unlocking?

marsbit18m ago

Trading

Spot

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of AI (AI) are presented below.

活动图片