Wingback SecuritySecurity for autonomous AI agents
An AI agent is an actor on your network that reasons, calls tools, and takes actions on its own. Wingback secures agents the way you secure people and services: it discovers every one, controls what they are allowed to do, and stops malicious actions while they happen.
The problem
Agents move fast and change weekly. They call tools and MCP servers, assume identities, and reach into sensitive data, often across several agents in a single workflow. Traditional controls were built for people and services, so they miss the agent entirely: endpoint tools watch processes, not prompts and tool calls; cloud posture tools inventory infrastructure, not agent behaviour. An attack rarely stays in one place. A poisoned document becomes a tool call becomes an exfiltration, and if your visibility stops at a layer boundary, that boundary is where the attacker goes.
How Wingback secures AI agents
Wingback provides Agent Detection & Response (ADR): continuous discovery plus inline enforcement across every layer where agents run.
- Discover every agent. Agentless discovery finds the agents, models, MCP servers, and inference paths across your cloud, SaaS, code, and endpoints, and scores each for risk.
- Control actions, not just text. Each tool call, identity use, and data access is evaluated against policy before and during execution. Wingback can block, sanitise, throttle, terminate, or alert.
- Per-agent guardrails. Tool and model allowlists, budget caps, recursion limits, and a kill switch, tuned per agent.
- Trace every delegation. Agent-to-agent handoffs carry a single auditable chain of custody, so privilege escalation across a multi-step workflow is a first-class detection.
- Hardened by red teaming. An adaptive attacker probes your agents with 800+ techniques mapped to the OWASP LLM and Agentic Top 10 and MITRE ATLAS, and every validated finding compiles into a runtime guard.
What you get
- Real-time detection and response for agent actions, not alert-only monitoring.
- Coverage across LangChain, CrewAI, AutoGen, OpenAI and Anthropic agent SDKs, MCP servers, and custom frameworks.
- Monitor-only mode for discovery and tuning, then enforce mode on the highest-risk paths.
- Structured events that slot into your existing SIEM (Splunk, Datadog, Snowflake, Chronicle).
FAQ
- What is AI agent security?
- AI agent security is the practice of discovering, monitoring, and controlling autonomous AI agents and the actions they take: the tools and MCP servers they call, the identities they assume, and the data they touch. Unlike prompt filtering, it governs what an agent does at runtime, not only what it says.
- How does Wingback secure AI agents?
- Wingback provides Agent Detection & Response (ADR). It discovers every agent across your endpoints, cloud, and software, then inspects each agent action inline and can block, sanitise, throttle, or terminate it. Per-agent policy sets tool and model allowlists, budget caps, and recursion limits, and every delegation is traced end to end.
- Which agent frameworks does Wingback support?
- LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, and the OpenAI and Anthropic agent SDKs, plus MCP servers and custom in-house frameworks via a lightweight SDK or gateway proxy.
- Can Wingback stop an agent from exfiltrating data or misusing a tool?
- Yes. Agent actions such as tool calls and data access are evaluated against policy before and during execution, so an agent that tries to exfiltrate secrets or invoke a dangerous tool is blocked in real time, with the full chain of custody recorded for forensics.