Crypto Funds at Risk as SlowMist Exposes Flaws in AI Coding Tools

Blockchain security firm SlowMist has issued a warning about critical vulnerabilities found in AI powered coding tools, cautioning that flawed code generated by artificial intelligence could expose crypto users to serious security risks. According to the firm, attackers may exploit subtle weaknesses introduced by AI written code to steal funds without immediate detection.

The findings raise concerns as developers increasingly rely on AI assistants to write and audit smart contracts and wallet software.

AI Generated Code Creates Hidden Attack Surfaces

SlowMist researchers identified that AI coding tools can generate functional but insecure code, often missing edge cases, validation checks, or proper access controls. These flaws may not trigger obvious errors, allowing malicious actors to exploit them silently.

Because AI tools are trained on large datasets that may include outdated or insecure coding patterns, the resulting output can unintentionally reproduce known vulnerabilities. When deployed in production, these weaknesses can become high value targets for attackers.

Why Crypto Users Are Especially Vulnerable

Crypto applications operate in irreversible environments where transactions cannot be rolled back. A single vulnerability in a smart contract or wallet script can result in permanent loss of funds.

SlowMist emphasized that AI generated code is particularly dangerous when used in:

• wallet signing logic
• smart contract permission systems
• cross chain bridges
• automated trading bots

Even small logical errors can be enough to compromise an entire system.

Growing Reliance on AI Tools in Development

AI powered coding assistants have become popular for accelerating development and reducing costs. However, SlowMist cautions that convenience should not replace rigorous security reviews.

Developers who blindly trust AI output may skip essential testing and auditing steps, increasing the likelihood of exploitable flaws reaching production environments.

Security experts stress that AI tools should be treated as productivity aids rather than authoritative sources of secure code.

Best Practices to Reduce Risk

To mitigate these risks, SlowMist recommends that developers:

• conduct manual code reviews regardless of AI involvement
• use professional security audits before deployment
• avoid deploying AI generated code directly to production
• apply strict testing and simulation under adversarial conditions

For users, the firm advises caution when interacting with new or unaudited crypto applications, particularly those advertising rapid development cycles.

Conclusion

The warning from SlowMist highlights a growing challenge at the intersection of AI and crypto security. While AI coding tools offer speed and efficiency, their misuse can introduce dangerous vulnerabilities with real financial consequences.

As AI adoption continues to expand across the crypto industry, balancing innovation with security discipline will be critical to protecting user funds and maintaining trust in decentralized systems.