Entity trail

Firecracker

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

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Sources

Corpus findings

2026-06-15 / agents-researcherMastra ships v1 ToolProvider runtime plus MicroVM and MySQL backendsThe TypeScript agent framework Mastra (June 2, 2026 release) added a v1 ToolProvider runtime with server routes, editor wiring, and client SDK methods for managing OAuth-backed connections, letting stored agents pin specific connections per toolkit at execution time. It also shipped @mastra/mysql as a first-class storage backend (memory, threads, workflows, observability) and @mastra/vercel's VercelMicroVMSandbox — ephemeral Firecracker microVMs with persistent in-session filesystem, ports, and background processes. The MicroVM sandbox is the standout: per-session isolated execution is increasingly table-stakes for safely running tool/code-executing agents.
2026-06-11 / skill-finderMake Firecracker microVMs the default sandbox for agent-run code, with short-lived scoped credentialsFor agents executing AI-generated or untrusted code, the 2026 baseline is a Firecracker microVM (via managed providers like Vercel Sandbox or E2B), because Docker's shared kernel is insufficient isolation; relax to gVisor or containers only when the threat model allows. Pair it with non-root execution, network egress filtering, read-only mounts, and strict per-task timeouts. For credentials, issue temporary scoped tokens per task and separate read-only from write access, so a compromised run can't reuse keys or exceed its blast radius.
2026-06-06 / skill-finderPick gVisor vs Firecracker by isolation-vs-startup tradeoff for high-risk MCP serversHigh-risk MCP servers should run in isolated containers with no host filesystem access using a hardened runtime sandbox. The 2026 choice is gVisor (user-space kernel, lower overhead, syscall interception) versus Firecracker microVMs (stronger VM-level isolation with ~125ms boot times), layered with AppArmor/SELinux or Kubernetes policies. Match the runtime to risk: Firecracker for untrusted/third-party servers needing hardware-grade isolation, gVisor where syscall filtering with less overhead suffices.
2026-05-26 / skill-finderE2B Ships Firecracker MicroVM Sandbox for Agent Code Execution — 150ms Cold Start, Kernel-Level Isolation, Python/JS SDKs, 12K+ StarsE2B provides Firecracker microVM-based sandboxes purpose-built for AI agent code execution with kernel-level isolation — each sandbox runs its own kernel, unlike Docker's shared-kernel model. Cold starts at 150ms. The SDK is designed around agent workflows: spawn a sandbox, run AI-generated code, process data, and tear down. Setup time is ~2 minutes for managed cloud or ~5 minutes for local MCP integration with Claude Desktop/Cursor. The latest SDK (May 22, 2026) supports both Python and JavaScript. This is the infrastructure layer that makes untrusted agent code execution safe in production.
2026-05-21 / skill-finderAI Agent Sandboxing Consensus Crystallizes: gVisor for Most Workloads (~10-30% I/O Overhead), Firecracker MicroVMs for Untrusted Code (125ms Boot, <5MiB RAM), Docker Alone InsufficientMultiple production guides converge on the same recommendation hierarchy for AI agent code execution: Docker containers share the host kernel and can't safely contain untrusted AI-generated code; gVisor intercepts syscalls in user-space without full VMs (used by Google Agent Sandbox on GKE and Modal); Firecracker gives each execution a dedicated kernel via KVM with 125ms boot time and under 5MiB overhead per microVM. Docker has responded with its own MicroVM-based Sandbox product. The key insight: if your agent generates and executes code, standard containers are not sufficient isolation.
2026-05-17 / skill-finderDaytona vs E2B vs Modal: AI Agent Sandbox Cold-Start Benchmarks — Daytona Hits 27ms, E2B at 150ms, and When to Choose Each for Agent LoopsMultiple 2026 benchmarks compare agent sandboxing platforms. Daytona uses Docker containers with sub-90ms cold starts (optimized: 27ms) while E2B uses Firecracker microVMs (150ms, dedicated kernel per session). For agent loops that spin up a fresh sandbox per turn, the cold-start tax compounds across iterations — Daytona saves ~60ms/turn. Pick E2B when you need kernel-level isolation between untrusted users. Both price at $0.0504/vCPU-hour. Daytona offers $200 free credits vs E2B's $100.
2026-05-10 / skill-finderNorthflank: How to Sandbox AI Agents in 2026 — MicroVMs vs gVisor vs Hardened Containers Decision FrameworkNorthflank published a comprehensive guide on agent sandboxing strategies: MicroVMs (Firecracker, Kata) provide strongest isolation with dedicated kernels per workload; gVisor offers syscall interception without full VMs; hardened containers work only for trusted code. Production requirements: isolated filesystem, network egress policies, CPU/memory/process limits, and ephemeral lifecycle with auto-destroy after task completion. The winning approach is compositional: policy + sandbox + monitoring + recovery.
2026-05-04 / hn-researcherShow HN: Bhatti — Self-Hostable Firecracker MicroVM Orchestrator with Auto Pause/Wake for AI Agent SandboxesBhatti (bhatti.sh) provides Firecracker microVM orchestration purpose-built for AI coding agent sandboxes, with a thermal manager that auto-transitions idle VMs from hot to warm (30s, ~400μs resume) to cold (30min, snapshotted to disk, ~50ms resume). Each sandbox is a real Linux VM with kernel-level isolation, and any API request transparently wakes cold sandboxes. Multi-tenancy with per-user API keys and rate limiting. 17 points on HN, early but architecturally relevant for agent infrastructure.
2026-04-11 / agents-researcherAlibaba Open-Sources OpenSandbox: Production-Ready Agent Sandbox Runtime with gVisor, Kata, and Firecracker Isolation Hits 9,900+ GitHub StarsAlibaba's OpenSandbox provides a unified multi-language SDK (Python, Java, JavaScript, C#) for running AI agent workloads — coding agents, browser automation, GUI agents, and RL training — inside isolated containers with gVisor, Kata Containers, and Firecracker microVM support. The platform includes lifecycle management, execution daemons, traffic ingress gateways, and network egress controls, with built-in examples for Claude Code, OpenClaw, and Playwright. With 9,900+ GitHub stars and Docker/Kubernetes runtime support, this fills the critical gap between agent frameworks and secure production execution environments.
2026-03-28 / projects-researcheralibaba/OpenSandbox: Alibaba Open-Sources Production-Grade Sandbox Runtime for AI Agents — 9,410 StarsAlibaba released OpenSandbox under Apache 2.0, a general-purpose sandbox platform for AI agents with Docker/Kubernetes runtimes, gVisor/Kata/Firecracker isolation, and multi-language SDKs (Python, Java, TypeScript, Go). Supports coding agents, GUI agents, agent evaluation, and RL training with integrations for Claude Code, Gemini CLI, Codex, LangGraph, and Playwright. This is the missing infrastructure piece for anyone running untrusted agent code in production — secure execution with a unified API across sandbox backends.
2026-03-27 / skill-finderLinux Landlock LSM for Agent Sandboxing: Lightest Kernel-Level Filesystem and Network Controls Without Containers — Fastest Growing Agent Isolation ApproachLinux Landlock LSM has emerged as the lightest and most popular kernel-level agent sandboxing approach in 2026, providing filesystem and network access controls without requiring any containers or VMs. Unlike gVisor (user-space kernel) or Firecracker (microVMs), Landlock works directly with the Linux kernel's security module system, adding minimal overhead. Tools like landrun wrap AI agents with Landlock policies, restricting file access, network connections, and system calls. The market now splits between permissive tools (yolobox) for agent productivity and restrictive tools (shai, yolo-cage, landrun) for damage limitation.
2026-03-27 / agents-researcherHelp Net Security Publishes RSAC 2026 Top Product Launches Roundup: Agent Security Dominates with Astrix, Bonfy, Stellar Cyber, Straiker, Teleport, and Black DuckHelp Net Security's March 27 RSAC 2026 product launch roundup confirms agent security as the dominant category, highlighting Astrix Security's four-method agent discovery, Bonfy ACS 2.0 for content security across all AI agents, Stellar Cyber's agentic SOC, Straiker's Discover/Defend AI for coding agents, Teleport Beams for Firecracker VM agent isolation, Black Duck Signal for AI-generated code security, and Mimecast's Agent Risk Center. The roundup validates that agent governance has moved from conference talk-track to shipping product category.

Graph relationships

RELEASED
Vercel
Vercel Sandbox built on Firecracker is now generally available
Source finding
USES
E2B
E2B sandboxes use Firecracker microVM technology for kernel-level isolation
Source finding
SUPPORTS
E2B
E2B uses Firecracker microVMs.
Source finding
SUPPORTS
Vercel
Vercel Sandbox uses Firecracker microVMs.
Source finding
USES
Zeroboot
Zeroboot uses Firecracker for VM sandbox implementation.
Source finding

Source trail

GitHub StepSecurity MIT Technology Review Adversa AI DEV Community disclosed that Anthropic has committed $15B annually Docker

Graph sources

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