Defend AI Runtime Security & Guardrails
Detect and block prompt injection, data exfiltration, and agent manipulation in coding agents, productivity agents, and custom-built AI agents.
PRODUCT OVERVIEW
Defend AI delivers runtime security for AI agents across coding copilots like Cursor, Claude Code, and GitHub Copilot, productivity agents like MS Copilot and ChatGPT Enterprise, and custom-built agents on AWS Bedrock and Azure AI Foundry. Powered by a high-efficacy AI engine, not legacy rule-based approaches, it inspects every prompt, reasoning step, and tool call to stop prompt injection, data exfiltration, and agent manipulation in real time.
Protect Every AI Agent Type
Coding Agents
AI coding agents take real actions like running commands, calling APIs, connecting to external tools. Straiker blocks destructive actions, data exfiltration of company secrets, and malicious MCP connections at runtime.
Custom-Built Agents
Your custom AI agents make dozens of autonomous decisions per session. Straiker monitors every step at runtime by catching jailbreaks, enforcing safe tool use, and flagging compliance gaps.
Productivity Agents
Productivity agents read your email, access your calendar, and act across your entire SaaS stack. Straiker catches hidden malicious instructions that can hijack your agent.
Runtime Security and Protection for AI Agents
AI agents are dynamic, multi-step, and unpredictable, making accurate threat detection uniquely hard. Defend AI is the industry's first runtime security engine trained on millions of real-world agent traces, delivering 6-21x lower false positive rates than frontier model judges with 98.1% detection accuracy at <300ms latency.
Runtime Security for AI Agents
Stop direct and indirect prompt injection, data exfiltration, and agent manipulation across coding agents, productivity agents, custom-built agents, and multi-agent workflows.
Multimodal Threat Detection
Detect threats hidden in text, code, images, audio, and file uploads that single-mode tools miss. Multi-language support included.
MCP & Tool Security
Identify malicious or vulnerable MCP servers and tool connections in real time, backed by Straiker's MCP Threat Database that is purpose-built to cover local and remote MCP risks where misclassifications have real consequences
AI Agent Observability & Forensics
Trace every interaction across the user, model, tool chain, and agent-to-agent calls for root-cause analysis. for root-cause analysis, anomaly detection, and audit readiness.
Application grounding & Output Safety
Detect and suppress application drift, toxic output, and policy violations before they reach users or downstream systems.
What to expect with defend AI
Built-in guardrails
Out-of-the-box, privacy-preserving guardrails you can customize to match policy and use-case needs.
Agentic AI chain of threats
Visualizes every user ↔ model ↔ tool step, enabling rapid incident triage and live threat blocking.
Frictionless deployment
Deploy in minutes with a single hook-based integration. One-line install via API, SDK, webhook, or AI sensor with no thick clients, proxies, firewalls, or infrastructure changes required.
Multimodal support
Consistent protection across any files, PDFs, text, image, audio, and visual inputs for unified policy coverage.
Real-time detection and blocking
Compact, optimized inference engine delivers subsecond decisions that scale automatically.
Monitoring and compliance
Dashboards, audit logs, and instant alerts over Slack, email, or webhook keep teams informed and audit-ready.
Adaptive threat management
Self-learning models tune themselves to your app’s behavior, reducing false positives and improving accuracy over time.
chain of threat forensics
a closed-loop system for AI security.
faq
How does Defend AI protect coding agents like Cursor and GitHub Copilot?
Defend AI provides runtime security for coding agents including Cursor, GitHub Copilot, and Claude Code. It detects and blocks destructive actions like file deletion and config changes, prevents data exfiltration of proprietary code and secrets, and identifies malicious MCP server and Skills connections in development environments.
How does Defend AI secure productivity agents like MS Copilot and Salesforce Agentforce?
Defend AI detects data exfiltration across SaaS applications, blocks prompt injection delivered through enterprise content like emails and documents, and surfaces unapproved agent usage. Agentic traces give security teams full visibility into how productivity agents interact with enterprise data.
What is runtime security for custom-built AI agents?
Runtime security for custom-built AI agents protects agents built on AWS Bedrock, Azure Foundry, and MCP from threats that emerge during multi-step tool call chains. Defend AI detects jailbreaks, prompt injection, and malicious MCP server configurations, and supports compliance with NIST AI RMF, OWASP, and EU AI Act.
How does Defend AI detect data exfiltration from AI agents?
Defend AI uses semantic detection to identify data exfiltration attempts across all agent types. It monitors for extraction of PII, PCI, HIPAA-regulated data, proprietary source code, and secrets across text, code, images, and file uploads, catching exfiltration vectors that traditional DLP tools miss.
What is MCP security and why does it matter?
MCP servers extend AI agent capabilities through tools and data access, but they also expand the attack surface. Defend AI identifies malicious, poisoned, or vulnerable MCP servers in real time, backed by Straiker's MCP Threat Database. As MCP adoption grows, securing these connections is critical to preventing supply chain attacks and unauthorized data access.
Secure every AI Agent
You’re building at the edge of AI. Forward-thinking teams use Straiker to secure AI agents, detect emerging attack paths, and safely scale agentic AI across their organization. With Straiker, you have the confidence to deploy fast and scale safely.
