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How We Built Runtime Security for AI Agents

DEV Community
samueloladji-beep

AI agents are going to production. And most of them have no security layer underneath them. ** ** What Vaultak Actually Does Monitors every action the agent takes in real time The SDK integration is two lines of code: vt = Vaultak(api_key="vtk_...") with vt.monitor("my-agent"): The Risk Scoring Engine Action Type What category of action is this? Read operations score low. Write operations score higher. Delete, drop, and truncate operations score highest. We maintain a taxonomy of action types and their base risk scores. Resource Sensitivity What is being acted on? An agent writing to a logging table is different from an agent writing to a user credentials table. We classify resources by sensitivity tier; public, internal, sensitive, and critical. Blast Radius How much damage could this action cause if it goes wrong? An action affecting one row has a small blast radius. An action affecting all rows in a table has a large one. We estimate blast radius from the scope of the operation. Frequency How often is this action being taken? A single write is expected. A hundred writes in ten seconds is a signal. We track action frequency over a rolling time window and score anomalies. Context Deviation Does this action fit the behavioral pattern we have observed for this agent? If an agent has never sent an external email before and suddenly tries to, that is a deviation worth flagging; even if email sending is not explicitly blocked. Each dimension produces a sub-score. The overall risk score is a weighted average. When the score crosses your configured threshold, Vaultak intervenes. Policy Enforcement pythonvt = Vaultak( Block; the action is stopped immediately, the agent receives a policy violation response The approval workflow was something we added after talking to security teams. They did not want to just block agents; they wanted to stay in the loop for high-stakes operations without creating so much friction that the agent became unusable. The pause-and-approve pattern solved that. Automatic Rollback PII Masking safe_output = mask_pii(agent_output) MCP Gateway Scanning Vaultak Sentry; Zero Code Integration The GitHub Action yaml- name: Vaultak Security Scan It runs static analysis on your agent code, flags high-risk patterns, and blocks merges that introduce critical security issues. Catching problems at the PR stage is significantly cheaper than catching them in production. What We Learned Try It SDK: pip install vaultak The Starter plan is free. No credit card required. Samuel Oladji is the CEO and co-founder of Vaultak. Orobosa Ekhator is the CTO and co-founder.