How to stop AI agents contacting malicious URLs and domains
Deny the tool call before an AI agent reaches a malicious URL or domain.
Read guideAI Security
Runtime controls, enforcement architectures, and operational guidance for production AI agents.
AI agent security governs what an agent may do while a production workflow is running. It extends beyond model output filtering because an unsafe outcome can emerge from a valid tool call, a compromised data source, a dangerous action sequence, or authority that is technically valid but inappropriate for the current task. Runtime protection evaluates identity, tool arguments, target resources, prior steps, sensitive data, and accumulated cost at boundaries where the application can still block or restrict an operation. Architecture matters because proxies, AI gateways, in-code checks, and supervisory agents observe different parts of the workflow and fail in different ways.
Read the runtime security guide first for the risks and control model. Then open the security guide for the framework you ship. Follow with the architecture comparison to decide which checks belong in application code, a proxy, an AI gateway, or a supervisory security agent.
Deny the tool call before an AI agent reaches a malicious URL or domain.
Read guideA rogue MCP server is one that your agents can call but that your organization hasn't reviewed or can't trust.
Read guideAn egress allowlist lists the hosts that an agent may contact, and a policy that the agent can't edit enforces it on every tool call.
Read guideCheck each shell command and fetch before a coding agent runs it.
Read guideMap AI agent trust boundaries, tool permissions, and attack paths.
Read guideGive each AI agent only the tools, credentials, resources, and execution time its task needs.
Read guideTest whether an AI agent can cause an unauthorized action or disclosure.
Read guideContain an AI agent incident, preserve tool-call evidence, trace downstream effects, and remove persistence.
Read guideThe best AI security for healthcare inspects PHI and PII in your process so the raw body never leaves to be classified.
Read guideThe useful fintech control inspects financial PII in-process, gates the transfer or refund at the tool boundary, and records who did what for the audit.
Read guideThe best AI security provider for enterprises depends on the layer: identity, gateway, guardrails, observability, or in-code enforcement.
Read guideEve agent security is three jobs: screen the channel, gate tools and connections, and treat hooks as observe-only.
Read guideWiring recipe for Mastra: screen with guardProcessor, wrap createTool, and deny MCP with guardHooks.
Wiring recipe for Claude Agent SDK: screen prompts on UserPromptSubmit and deny tools at PreToolUse.
Read guideA human click is a hold, not a remote allow or deny. Eve user-approval, Mastra requireApproval, and Claude canUseTool park a call.
Read guideClaude's canUseTool looks like a gate. allowedTools, allow rules, and bypassPermissions / acceptEdits skip it. A Bash or Write in allowedTools never.
Read guideAn agent sandbox isolates untrusted code from your app runtime and your secrets.
Read guideMastra guardrails classify messages. An action gate decides whether this tool runs. A clean prompt-injection score can still open a pull request that pastes.
Read guidePrivate data, untrusted content, and external communication in one agent let an attacker steal data through content the agent already reads.
Read guideSimilarity retrieval finds on-topic chunks, not safe ones. Screen retrieved content before it enters the model context.
Read guideGuardian Agents supervise the agents you run with visibility, assurance, and runtime enforcement.
Read guideApplication-native, code-authored rules give engineers context, review, and tests.
Read guideCompare in-code, proxy, AI gateway, and security-agent controls by visibility, enforcement, and context.
Read guideAI agent runtime security enforces policy while an agent is interpreting input, calling tools, accessing data, and taking actions.
Read guidePrompt injection, data exfiltration, and unsafe tool use — the three runtime failure modes for LLM apps.
Read guideScreen the user message before the model, and screen tool or retriever output before it re-enters context.
Read guideAI security tools cluster into pre-runtime, runtime, and post-runtime.
Read guideMost security tooling has to receive your traffic to inspect it.
Read guideWhen agents touch CRMs, warehouses, and internal APIs, the control has to run at each action.
Read guideA runaway agent is a budget problem before it is a security problem.
Read guideStop agents leaking sensitive data without sending that data to a third-party scanner.
Read guideScoped credentials limit what an agent can reach.
Read guideScan the prompt before the provider sees it and the completion before it renders — inbound, outbound, and streaming boundaries.
Read guideRuntime PII detection ships in three shapes, and they differ on where the text goes to get classified and which paths they can see.
Read guideStop the string reaching the provider, in the handler that makes the provider call.
Read guideBetween the message and the answer, an agent calls tools, reads results back into context, writes to memory, and hands off to other agents.
Read guideMiddleware around OpenAI and Anthropic clients: reversible redaction, streaming chunks, tool arguments, and why provider filters run too late.
Read guidePermission-aware retrieval, tenant boundaries in memory and vector stores, and why fine-tuning has no runtime remedy.
Read guideMap GDPR and CCPA requirements to controls: minimization, erasure, processor scope, transfers, and audit trails without a second PII store.
Read guideA five-layer defense stack: input screening, instruction and data separation, output validation, privilege limiting, and action gating.
Read guideWhy escaping and regex fail, what structural separation looks like, and the multi-turn payload single-message screening misses.
Read guideA hijack is a well-formed call the model was persuaded to make. Validate arguments, scope tools, and budget actions.
Read guidePayloads arrive through retrieved content. Screen before context, track provenance, and limit blast radius.
Read guideCompare heuristics, classifiers, LLM-as-judge, canary tokens, and behavioral divergence — and where each is enforced.
Read guideArcjet, Lakera Guard, Azure Prompt Shields, LLM Guard, Rebuff, and Guardrails AI compared for production.
Read guideThe best tools are the ones you call in the handler before the provider or tool runs — not a dashboard after the refund.
Read guideSome agent actions should not execute without a human.
Read guideAuditors do not want your system prompt.
Read guideMCP tools have no HTTP front door. How to add budgets, injection detection, and data controls where the.
Read guideCorrectly scoped tools can still enable fraud — the question is the sequence of calls, not any single tool.
Read guideEnforce on the outbound HTTP call, inside the tool that makes it.
Read guideA chat route is a user string, then retrieved context, then a completion.
Read guideCompare runtime security integration points for LangChain, LangGraph, CrewAI, AutoGPT, and Vercel AI SDK.
Read guideDeny transfers, deletes, and prod config by default. Hold a human only where needed, and resume with an idempotency key.
Read guideThe 2026 OWASP GenAI list is the source of names and order.
Read guideApply 20 verifiable AI security controls for production LLM apps.
Read guideAI security protects models, data, applications, and infrastructure.
Read guideFour surfaces appear when a handler calls a model.
Read guideScreen user prompts before AI-generated content, including image prompts.
Read guideA tool list names functions the model can call. Least privilege also covers objects, arguments, and how often.
Read guideScreen the request that asks for it, screen the response that carries it, and keep anything that would hurt you out of the prompt.
Read guideContent guardrails label text. Action gates allow or deny operations. Most libraries only do the first job.
Read guideMCP support can mean four different things. Sort vendors by which side of the connection they sit on.
Read guidePick tools by the boundary they reach. Most stacks leave tool arguments and tool results uncovered.
Read guideDetection wants to inspect content; privacy wants it to stay put. Platforms that claim both often send your data away.
Read guideMulti-tenancy, subprocessor obligations, and per-plan behavior separate a SaaS requirement from a general one.
Read guideFor a small team, the right tool is one engineer can install in an afternoon — and that still runs in six months.
Read guideCloud workload protection secures compute. AI application security secures what the model does inside it.
Read guideSecure Claude Agent SDK applications in TypeScript and Python with prompt screening, tool policies, resource authorization, and isolated sessions.
Read guideSecure Claude Managed Agents with inbound screening and custom-tool policies.
Read guideSecure Cloudflare Think agents with inbound screening and beforeToolCall policy.
Read guideSecure CrewAI with kickoff screening, tool-call hooks, resource authorization, and standalone tool wrappers.
Read guideSecure Genkit with inbound screening, authored-tool wrappers, and middleware.
Read guideSecure Google ADK in TypeScript and Python with inbound screening and before-tool policies.
Read guideApply runtime security to LangChain JavaScript and Python agents.
Read guideSecure LangGraph JavaScript agents with input screening and ToolNode policies.
Read guideSecure Mastra messages, authored tools, MCP capabilities, and memory.
Read guideSecure Microsoft Agent Framework for Go with inbound and tool policies.
Read guideSecure OpenAI Agents SDK applications in JavaScript and Python.
Read guideSecure Strands Agents in JavaScript and Python with prompt screening and tool policies.
Read guideSecure TanStack AI with prompt screening and server-side tool policies.
Read guideSecure Vercel AI SDK tools and application actions with policy checks.
Read guideSecure Vercel Eve channels, tools, and connections.
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