Straiker is a commercial security platform for AI agents and agentic applications. It combines discovery and posture management, adversarial testing, and runtime protection.
The platform covers coding agents, productivity agents, custom-built agents, tools, and Model Context Protocol connections. It belongs in the AI security tools category rather than a general application-security scanner list.
Straiker announced a $64 million Series A on June 29, 2026. The company says the round brought its total funding to $85 million; those figures are vendor-reported.
What is Straiker?
Straiker organizes its product around three connected components: Discover AI , Ascend AI , and Defend AI .
Discover identifies agents and their connections. Ascend tests them for exploitable behavior, while Defend applies runtime controls.
Straiker describes a closed loop in which production detections improve testing and test findings harden runtime defenses. The public pages document the workflow but do not provide an independent comparison of its effectiveness.
A vendor product image of an Ascend AI assessment, with attack attempts grouped by risk category.
Key features
| Product | Current documented scope |
|---|---|
| Discover AI | Inventory of agents, tools, MCP servers, Claude Skills, permissions, and integrations |
| Posture management | Misconfigurations, excessive permissions, unsafe MCP integrations, and risky connections |
| Ascend AI | Continuous, scheduled, on-demand, and CI/CD-triggered adversarial testing |
| Test surface | Models, agents, tools, MCP servers, RAG components, data, identities, and web workflows |
| Defend AI | Runtime inspection of prompts, reasoning steps, and tool calls |
| Runtime threats | Prompt injection, data exfiltration, tool abuse, MCP exploitation, and agent manipulation |
| Deployment | API, logs, SDK, AI sensors, gateway, or proxy, depending on product and workflow |
| Evidence | Assessment reports, audit logs, downloadable prompts, and conversational traces |
Discover AI
Discover AI builds an inventory of agents, tools, MCP servers, Claude Skills, APIs, and integrations. Straiker names AWS Bedrock AgentCore, Azure AI Foundry, Microsoft Copilot Studio, Cursor, Claude Code, and GitHub Copilot among the covered platforms.
Its posture layer checks agent configuration, permissions, MCP connections, and integrations. Framework mappings include the OWASP Top 10 for Agentic Applications, MITRE ATLAS, and NIST AI RMF; mappings support governance work but do not prove compliance.
Ascend AI
Ascend AI runs adversarial tests across an agentic application stack. The vendor documents prompt injection, MCP tool misuse, agentic exploits, data leakage, and data exfiltration among the tested risks.
Tests can run continuously, on a schedule, on demand, or through CI/CD hooks. Straiker also documents API, log, SDK, and sensor-based deployment options.
A vendor product image of an Ascend AI assessment summary.
Defend AI
Defend AI is the runtime layer. Straiker says it inspects prompts, reasoning steps, and tool calls across coding, productivity, and custom-built agents.
Documented controls cover prompt injection, data leakage and exfiltration, agent manipulation, destructive actions, tool misuse, and malicious MCP connections. Enforcement can include detection, blocking, response shaping, or sanitization.
A vendor product image showing Defend AI controls in detect or protect mode.
MCP security
Straiker’s MCP security coverage spans inventory, hygiene checks, adversarial testing, and runtime enforcement. The vendor describes tests for tool poisoning, rug pulls, output injection, privilege escalation, unsafe actions, and data exfiltration.
Public pages also contain accuracy and latency claims. This review does not repeat them as established performance because the figures come from Straiker’s own testing and no independent benchmark was identified.
STAR Labs research
STAR Labs is Straiker’s internal threat-research team. Its published figures are useful signals about the vendor’s threat model, but they are not independent prevalence estimates.
Straiker reports that 28.6% of cataloged MCP tools present direct security risk. It also reports that 36% of successful attacks on coding agents led to remote code execution and 91% of successful attacks on productivity agents led to silent data exfiltration.
Those percentages describe the vendor’s catalog and adversarial tests. They should not be generalized to all MCP servers, coding agents, or productivity agents without the underlying sampling and methodology.
Commercial status
Straiker says it launched in 2025. Its June 2026 funding announcement names Marathon Management Partners, Citi Ventures, Illuminate Financial, and Workday Ventures as Series A leads, with continued support from Bain Capital Ventures and Lightspeed.
The vendor site publishes customer testimonials from Omada Health, Coupa, American Express Global Business Travel, EnterpriseDB, and Automation Anywhere. These are vendor-selected references rather than comparative product evidence.
No public list price appeared on the product pages reviewed. Straiker routes prospective customers to a demo or free risk assessment.
When to use Straiker
Straiker fits teams that need one platform to inventory, test, and protect a mixed estate of enterprise agents and MCP connections. The broadest fit is an organization running coding, productivity, and custom-built agents together.
Run a proof of concept against your own agent frameworks, tool chains, traffic, and latency budget. Product breadth and vendor research do not replace workload-specific validation.