SlowMist, the blockchain security company, has released a unified Web3 security stack for autonomous AI agents, implementing advanced on-chain AML checks and proactive threat intelligence. This new framework integrates management-level risk analysis into agent workflows and addresses a surge of supply chain and skills-level attacks identified by the company.
The company launched MistTrack Skills on March 3, 2026, and subsequently issued public warnings about malicious toolchains in the first weeks of March, positioning the stack as a response to emerging operational risks for agent systems managing crypto assets.
What does the new framework include?
SlowMist’s suite is centered around three main pillars. First, MistTrack Skills provides on-chain AML risk analysis that agents can review before initiating transfers, swaps, or other on-chain operations. MistTrack’s OpenAPI indexes over 400 million on-chain addresses and approximately 500,000 threat intelligence data points. The skills were released for integration with agent and wallet frameworks, such as OpenClaw, Claude Code, Bitget Wallet, and Trust Wallet.
Secondly, the company incorporated proactive threat hunting and supply chain protection. Just a few days ago, SlowMist issued a warning about a malicious npm package, @openclaw-ai/openclawai, which it claims was designed to exfiltrate system credentials, encrypted wallet private keys, and other sensitive data. Previously, on February 9th of this year, the company reported discovering 341 malicious skills on platforms like OpenClaw’s ClawHub that used so-called “intent hijacking” to execute unauthorized operations while appearing to fulfill user requests.
Third, SlowMist is promoting a transition from signature-based detection to what it calls behavioral intent monitoring. This framework monitors agent execution chains to detect discrepancies between the user’s declared intent, the agent’s interpreted intent, calls to specific skills, and the final results. The approach also emphasizes execution in isolated environments with least-privilege access and decentralized reputation or verification networks for skills.
Growing Security Needs
With the increasing use of autonomous agents in the crypto ecosystem, there has also been a significant rise in attacks and hacks targeting this technology, exposing significant vulnerabilities.
Therefore, SlowMist introduced ADSS (AI Development Security Solution), a security framework for developing AI tools and intelligent agents. Rather than being a single product, it functions as a governance system that establishes rules for how AI tools should be used within an organization, including access controls, permission limits, and auditing standards to mitigate security risks.
The framework aims to address new attack vectors that have emerged with the adoption of AI, such as prompt manipulation, malicious plugins, and compromised software dependencies. It also seeks to balance the increased efficiency of these tools with the need to comply with security standards, incorporating regular reviews and audits to prevent data breaches, automated errors, and insecure configurations over time.
