A recent exploit that forced three Solana-based platforms — including Step Finance and SolanaFloor — to suspend operations has re-ignited debate over whether traditional smart contract audits are enough to protect DeFi projects. The incident underscores a growing belief in the security community: one-off code reviews are no longer sufficient in an environment where attacks unfold in minutes. Why one-time audits are showing their limits Audits remain a de facto launch requirement on chains like Solana, but their value is inherently time-bound. An audit reviews code as it exists at a moment in time; once a protocol is live, attackers and environmental changes can create new risks that static reports don’t catch. Security teams often shift to reactive modes after deployment, leaving gaps that fast-moving exploits exploit. AI-powered monitoring moves security into real time That gap has accelerated demand for AI- and machine learning-driven monitoring tools that watch on-chain behavior continuously. These systems aim to detect anomalous wallet patterns, unusual governance activity, suspicious cross-protocol fund flows and other early signs of exploitation — actions that rule-based systems and periodic audits can miss. As blockchain analytics providers point out, ML can surface emerging threats in real time by finding patterns across massive transaction data sets. In practice, proponents say predictive models can buy critical minutes of warning — time that teams can use to pause contracts, restrict withdrawals, or otherwise limit damage. Attack surfaces extend beyond smart contracts The recent shutdowns also highlight that vulnerabilities aren’t confined to core contract code. APIs, front-end infrastructure, or third-party data integrations can provide attackers alternative entry points. Traditional audits typically focus on contract logic and may not cover the full operational stack, widening the possible avenues for breach. Solana’s recovery narrative at stake The platform’s security record has been under pressure since the FTX collapse in 2022 dented activity and confidence. While capital has flowed back to Solana and broader DeFi, repeat incidents threaten to slow the rebound and raise the cost of building on the network. A layered, continuous defense — but no silver bullet Security teams are increasingly adopting layered defenses: audits as a baseline, plus continuous monitoring, clearer risk disclosures, faster incident-response playbooks, and AI-driven detection as an additional line of defense. Yet skeptics warn there’s no way to eliminate risk entirely in permissionless systems where transactions are irreversible. What projects must do next For Solana-native teams affected by the exploit, recovery will require more than code fixes. Rebuilding user trust means demonstrating ongoing surveillance, transparent communication about risks, and the ability to respond quickly when anomalies appear. Bottom line The industry is shifting from static pre-launch assurance toward continuous, predictive threat detection. AI-driven monitoring is emerging as a practical early-warning layer in DeFi security — not a cure-all, but increasingly essential in a landscape where exploits happen in minutes and capital moves even faster. Read more AI-generated news on: undefined/news

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