What is Gensee Crate?

Gensee Crate is runtime defense for AI coding agents across enterprise engineering environments. It catches unsafe behavior across user requests, agent plans, terminal commands, tool calls, memory, skills, files, network activity, credentials, processes, and execution.

How is Gensee Crate different from prompt filtering?

Gensee Crate uses defense in depth. It follows intent from the user request through agent behavior, MCP and tool calls, memory, skills, files, network activity, and processes instead of relying only on a prompt filter.

What long-horizon risks does Gensee Crate address?

Gensee Crate traces lineage across sessions so teams can detect risks planted in memory, skills, generated artifacts, or local context that trigger later system actions.

How does Gensee Crate deploy?

Gensee Crate is designed as a low-latency sidecar that works beside unmodified coding agents and can feed centralized policy, identity, evidence, and controls for enterprise deployments.

Gensee Crate Coding-agent runtime defense

Enterprise runtime defense for AI coding agents.

Gensee Crate delivers customized enterprise runtime defense for Claude Code, Codex, Cursor, and MCP-style coding workflows by connecting agent intent to OS-level activity before risky commands, file access, credential use, or tool calls happen.

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Prevent earlierbefore risky action

OS-aware contextintent to system

Longer memoryacross sessions

Enterprise controlpolicy and evidence

Enterprise runtimeAgent intent to OS activity

LongerMulti-session lineage and defense

SidecarWorks with unmodified coding agents

Defense in depthRequests, tools, memory, files, network, processes

Engineering environmentsmacOS today, Linux planned

Low latencyMillisecond-level sidecar decisions

Coding agentsClaude Code, Codex, Cursor, MCP

On-prem readyKeep policy and evidence inside your environment

Enterprise runtimeAgent intent to OS activity

LongerMulti-session lineage and defense

SidecarWorks with unmodified coding agents

Defense in depthRequests, tools, memory, files, network, processes

Engineering environmentsmacOS today, Linux planned

Low latencyMillisecond-level sidecar decisions

Coding agentsClaude Code, Codex, Cursor, MCP

On-prem readyKeep policy and evidence inside your environment

Quick answers

Gensee Crate defends enterprise coding-agent runtime.

Gensee Crate catches unsafe coding-agent behavior before it becomes a system-level side effect. It connects user requests, agent plans, terminal commands, tool calls, memory, skills, files, credentials, network activity, and processes into one policy-aware trace.

What is it?

Runtime defense for AI coding agents running across enterprise engineering environments.

How is it different?

It follows coding-agent intent all the way down: terminal commands, MCP/tool calls, memory, skills, files, credentials, network, and processes.

What risks?

Prompt injection, memory poisoning, credential exposure, unsafe shell commands, risky tool use, and delayed unsafe actions.

How does it run?

A low-latency sidecar beside unmodified coding agents, with centralized policy, monitoring, and on-prem evidence for enterprise deployments.

01 · Deeper

Defense in depth for every layer of agent action.

Any layer can be unsafe: the user request, the agent's plan, or the system action. Gensee Crate maps the full path so it can detect risk and enforce defense in depth instead of trusting one prompt filter.

Defense in depth illustration with Human Layer, Agent Layer, and System Layer stacked as protected security surfaces

02 · Longer

The dangerous action may happen three sessions later.

Agent risk is not always a single bad request. It can be planted in memory, hidden in a skill, carried through an artifact, and triggered days later by a benign-looking task.

Long-horizon agent risk timeline showing Session 1 planting memory or skills, Session 2 ordinary agent work, and Session 3 blocked system action

A long-horizon failure

Session 1 Persistence is planted.
A web page, repo, or dependency convinces the agent to save a helpful memory, modify a skill, or leave behind a shell helper.
Session 2 The user asks a normal task.
The agent returns to the project, reads local context, invokes tools, and unknowingly follows the poisoned instruction path.
Session 3 Side effects appear.
A file is staged, a secret is touched, a process runs, or a network request leaves the machine. A single-session scanner sees only the final action.

How Crate defends

Lineage across sessions.

Crate links requests, memories, skill edits, tool calls, artifacts, process launches, file effects, and network activity into one trace.

Persistence-aware policy.

Memory writes, skill changes, generated scripts, hooks, and executable artifacts become policy surfaces, not invisible agent state.

Explainable response.

When Crate blocks or asks for approval, teams can see the chain that made the action risky, not just the last command.

Early benchmark signal

Higher defense rates across agent threat types.

Preliminary AgentCanary Benchmark results show Gensee Crate improving defense rate across threat types.

Memory poisoning

Baseline75%

With Gensee93.8%

18.8 pt lift

Long-horizon tasks

Baseline65.4%

With Gensee100%

34.6 pt lift

Prompt injection

Baseline77.8%

With Gensee93.5%

15.7 pt lift

Runtime overhead 0.6%-1.2% 10ms-400ms per request

* Results tested on MacOS running Claude Code with Qwen-3.5-397B model.

03 · Sidecar

Runs beside the coding agents teams already use.

Gensee Crate is designed as a non-intrusive runtime sidecar. It works with unmodified coding agents across enterprise engineering environments, without forcing teams to rebuild their agent stack around a security SDK.

Distributed Gensee Crate setup with developer laptops running AI Agent and Crate Sidecar, connected to an MCP Skills Harness Gateway, Company Policy, and Gensee Dashboard

Unmodified agents

Start with Claude Code, Codex, Cursor, and MCP-style tool use as they run today, instead of rebuilding the agent stack around a security SDK.

Engineering environments

Designed for where coding agents actually run: developer machines today, managed Linux runtimes next, and centralized enterprise controls across both.

Sidecar enforcement

Observe and interpose around tools, files, network, execution, memory, skills, and artifacts without sitting in the user's way.

Unchanged developer/user experience

Targets low false positives and interactive latency, so protection stays practical for real coding sessions instead of slowing developers down.

Enterprise path

The same runtime layer feeds company-set policy, centralized monitoring, on-prem evidence storage, identity, alerting, SIEM, and internal developer systems.

Market signals

Early demand for coding-agent runtime defense.

Enterprise AI and security teams are starting to ask for runtime defense that follows coding agents across terminals, repos, tools, credentials, endpoints, managed runtimes, and long-running sessions.

Enterprise demandDeep-stack, long-horizon defense

Research ecosystemEigentAI, CamelAI, UCSD

Coding-agent workflowsClaude Code now; Codex and Cursor next

Enterprise runtimesmacOS now, Linux planned

Enterprise signal

“We seek solutions from GenseeAI for in-depth, long-horizon defense for our company-wide AI agent system.”

AI Security Team from a hyperscale IT company

Research and partner network

GenseeAI partners with EigentAI and CamelAI, is backed by research from UCSD WukLab, with venture backing from TSFV.

Two offerings

From runtime enforcement to centralized enterprise control.

Gensee Crate starts with runtime enforcement around coding agents and extends into centralized policy, monitoring, identity, evidence, and multi-agent controls for company-wide engineering safety.

Layered OWASP and ASI threat map showing Gensee Crate defense coverage across model and coding-agent risks, runtime enforcement, and centralized enterprise control — Coverage map: runtime enforcement grounds coding-agent actions in system events; enterprise deployment adds identity, policy, monitoring, and evidence.

Open source individual tool

For individual developers who want local protection when coding agents interact with LLMs, terminals, MCP tools, skills, websites, files, and execution surfaces.

Individual developers Coding agents LLM threats Tool threats Skills Websites Terminal

Enterprise deployment

For company-wide engineering safety: distributed deployment, centralized monitoring and control, integration with existing security tooling, company-set policy, identity binding, tamper-evident evidence, quotas, MCP/tool manifests, SIEM integrations, and controls for malicious-human and multi-agent risks.

Central control Distributed Company policy Identity binding Tamper-evident Quotas MCP manifests SIEM Multi-agent

Get started

Secure the coding agents your team already uses.

Book a demo to see Gensee Crate around Claude Code, Codex-style workflows, MCP tools, skills, memory, terminal commands, and system actions. The open-source individual edition is available on GitHub for local trials.

Book a demo Open Source