AI‑enhanced SaaS is turning smart contract management into a proactive, automated loop: real‑time on‑chain monitoring detects issues, serverless actions trigger guarded responses, and relayers execute transactions reliably across networks with auditability.
Security networks layer machine learning on top of chain data to spot phishing and anomalous behavior early, routing alerts to teams and playbooks before funds or governance are at risk.
What it does
- Continuous monitoring watches contract events, roles, balances, and governance actions, then emits alerts to Slack/Telegram/PagerDuty with full context for triage.
- Serverless “web3 actions” automate incident response (pause, revoke roles, execute safe updates) on triggers like failed invariants, threshold breaches, or suspicious callers.
- Managed relayers abstract gas and nonce logic, sponsor gasless UX, and reliably execute policy‑bound transactions across 70+ networks with queues and webhooks.
Why AI matters
- ML‑powered detection bots learn evolving phishing and scam patterns across DeFi, NFTs, bridges, and governance, cutting time to detection versus rules alone.
- AI‑assisted anomaly detection reduces false positives and scales coverage as protocols grow multi‑chain and event volumes surge.
Platform snapshots
- OpenZeppelin Defender
- Relayer and Monitor power programmable transactions and real‑time visibility; now open‑sourced (alpha) after processing 40M+ txs and 45M alerts, with integrations to incident channels.
- Actions tie monitors to relayers so code can respond automatically to threats (e.g., pause contracts, rotate keys) without hard‑coding secrets.
- Tenderly
- Forta Network
Reference architecture
- Sense: Subscribe to contract events, state changes, and anomalies from Monitor/Alerts and Forta feeds across supported EVM networks.
- Decide: Use Web3Actions/Actions to evaluate policy (role checks, invariants, governance state) and select a safe response playbook per incident type.
- Act: Execute with Relayers to handle gas, nonces, and retries; notify ops with links to traces and simulations for verification.
- Learn: Triage alerts, tune thresholds, and adopt new ML bots as threat patterns change to improve precision over time.
30–60 day rollout
- Weeks 1–2: Instrument and baseline
- Weeks 3–4: Automate guarded responses
- Weeks 5–8: Strengthen detection and reliability
KPIs to track
- Time to detect and respond: Minutes from suspicious event to alert and from alert to on‑chain mitigation via automated action.
- Precision and noise: True‑positive rate of alerts and reduction in manual triage after ML bot adoption.
- Execution reliability: Relayer success rate, retries, and cross‑chain publication latency for incident transactions.
- Coverage: Number of monitored contracts/networks, invariant checks in place, and subscribed third‑party detection bots.
Governance and safety
- Bounded automation: Require policy checks, simulations, and role‑based approvals in Actions before any sensitive on‑chain response.
- Auditability: Store alert payloads, action logs, and relayer tx metadata for post‑mortems and compliance reviews.
- Resilience and portability: With Defender Monitor/Relayer open‑sourced (alpha), teams can self‑host critical components to reduce vendor risk over time.
Common pitfalls—and fixes
- Alert fatigue from naive rules
- Manual incident execution
- DAO/governance blind spots
Related
How can OpenZeppelin Relayer automate smart contract transactions for my SaaS
What safeguards do Monitor alerts provide against onchain threats for my product
How would integrating Relayer open source affect my gasless tx user flows
Which automation templates best fit recurring onchain updates in SaaS workflows
How can Tenderly Web3Actions complement Defender Relayer in alerts-to-actions