Declaw
Summary
Running an AI agent in production without isolation means a single prompt injection can exfiltrate credentials, hit arbitrary endpoints, and leave no audit trail — and stitching together five separate vendors to prevent that creates gaps at every seam. Declaw collapses that stack into one SDK: Firecracker microVMs, network controls, PII redaction, a credential vault, and a full audit trail sharing the same execution context.
Each agent execution runs inside a hardware-isolated microVM with a warm-pool restore measured in milliseconds. Outbound traffic passes through a per-sandbox proxy the agent cannot bypass, enforced at both L3/L4 and L7 — so if your allowlist says api.openai.com only, evil.com gets blocked and logged automatically. The credential vault injects secrets at the proxy layer, meaning API keys never enter the VM itself. Where Declaw shows its limits: there is no self-hosted option, so teams in air-gapped environments or with data-residency requirements that preclude third-party cloud infrastructure hit a hard wall. Those teams look at building their own Firecracker wrapper.
Bottom line: Pick Declaw when you need a production-grade agent sandbox without assembling five vendors — but plan a different architecture if your compliance requirements mandate that no traffic, including inspection proxies, leaves your own infrastructure.
Pricing Plans
Usage-Based- Free Tier
- $100 one-time sandbox free credits; $200 one-time guardrails free credits
Free
One-time $100 sandbox free credits and $200 guardrails free credits
- Sandbox compute from free credits
- Guardrails scans from free credits
Paid
Deposits into paid balance after free credits exhausted
- Per-second sandbox metering
- Per-scan guardrails metering
View full pricing on declaw.ai →
Pricing may have changed since last verified. Check the official site for current plans.
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Pros
Sign in to edit- All security primitives — network policy, PII redaction, credential vault, and audit log — share the same execution context inside one SDK, so there are no integration gaps between vendors where an injection or exfiltration can slip through unlogged.
- Credentials are injected at the egress proxy rather than passed into the VM, which means a compromised agent process cannot read the raw API key even if it tries.
- L7 domain and SNI filtering with wildcard and regex matching lets you define exactly which external endpoints an agent is allowed to reach, so a prompt injection that tries to POST to an attacker-controlled domain is blocked and audited rather than silently succeeding.
- Snapshot and pause/resume support lets you freeze idle agents and stop paying for compute mid-task, which matters for long-running workflows where billing otherwise accumulates during wait states.
- Drop-in compatibility with OpenAI, Anthropic, LangChain, and CrewAI means existing agent code runs inside the sandbox without a rewrite, so the migration cost is measured in configuration rather than refactoring.
Cons
Sign in to edit- There is no self-hosted deployment option — every agent execution and its outbound traffic passes through Declaw's cloud infrastructure. Teams with data-residency requirements or compliance mandates that prohibit third-party traffic inspection hit this wall immediately; those teams typically end up building a custom Firecracker wrapper with open-source guardrails libraries rather than adopting Declaw.
- The audit log and guardrail features are only as useful as the policies you define upfront — the docs describe allowlist-based network control, meaning any allowed domain your agent abuses (for example, an attacker using a permitted API as an exfiltration relay) passes through without detection. Teams handling adversarial inputs at scale need to layer additional behavioral monitoring on top, adding back some of the complexity Declaw was meant to eliminate.
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About
- API Available
- Yes
- Self-Hosted
- No
- Last Updated
- 2026-07-03T04:41:24.554Z
Best For
Who it's for
- Developers building production AI agents
- Teams requiring compliance and audit logging
- Workloads needing granular usage-based billing
What it does well
- Secure execution of AI agents in isolated sandboxes
- PII redaction and prompt injection defense in agent workflows
- Code security and toxicity scanning for agent-generated content
- Network-controlled environments for agent operations
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Frequently Asked Questions
- Is Declaw free?
- Declaw has a permanent free tier alongside paid upgrades. You can keep using a baseline version indefinitely without paying.
- Is Declaw open source?
- No — Declaw is a closed-source tool. Source code is not publicly available.
- Does Declaw have an API?
- Yes. Declaw exposes a developer API. See the official documentation at https://declaw.ai for details.
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Curated lists that include this category
Most agent security stacks are assembled from parts: a sandbox vendor, a guardrails vendor, DIY network filtering, and a separate audit log — none of which share context. Declaw replaces that with a single SDK wrapping Firecracker microVMs. You create a sandbox, attach a security policy, and your agent runs inside a hardware-isolated VM whose outbound traffic is inspected by a proxy it cannot circumvent. PII is redacted and optionally rehydrated, prompt injection attempts are blocked, and every event — boot, egress decision, redaction, credential injection — lands in a structured audit log.
The differentiating feature is that the network controls and guardrails are not layered on top of the sandbox after the fact — they are enforced at the egress proxy as a condition of the VM’s execution context. The vendor states that API keys stored in the credential vault are injected into outbound requests at the proxy layer, so the secret value is never visible inside the VM. L3/L4 filtering handles IP and CIDR ranges at the kernel level; L7 inspection adds domain and SNI matching with exact, wildcard, and regex patterns, giving you fine-grained control over what an agent can reach.
Declaw fits teams shipping agents where a prompt injection or credential leak would be a production incident: financial data pipelines, customer-facing agents with access to external APIs, or any workflow where you need a tamper-evident record of what the agent did and what it touched. It integrates drop-in with OpenAI, Anthropic, LangChain, CrewAI, and any OpenAI-compatible API — the docs describe no code changes required for existing agent code. The ceiling appears for teams that cannot route traffic through a third-party cloud proxy under any circumstances: Declaw offers no self-hosted deployment path, so air-gapped environments and strict data-residency requirements are out of scope.
The SDK ships in Python, Node, and Go. Snapshots freeze the full guest state — memory, CPU registers, and disk — so long-running agents can be paused to stop compute billing and resumed exactly where they left off. Volumes provide up to 64 GiB of persistent storage attachable across sandboxes in either copy-on-boot or live-mount mode, covering agent workflows that need to read and write shared datasets across executions.