Teams hosting AI agents outside their own environment keep asking the same handful of questions: how to evaluate a sandbox vendor, how an agent keeps reaching enterprise data once someone else hosts it, what to do about shared memory, and what happens when an agent goes wrong. Below are direct answers to nine questions we hear from teams building with agents, with the practical steps first and where KollGuard fits — and doesn't — after each one.
How do we evaluate several third-party sandbox providers for our agent team?
Evaluate a sandbox vendor as you would any vendor that will touch your data, not by feature list: isolation model and tenant separation, network egress controls, secrets and credential handling, data handling and retention, data residency and deployment model, attestations, the vendor's own subprocessors, logging and incident response, availability and abuse controls, and how it handles agent memory or persistent state.
Ask what actually runs under a vendor's marketing name for isolation — container, microVM, user-space kernel, WASM sandbox, or full VM — whether that boundary has ever had a public escape, whether egress defaults to deny, whether it supports short-lived scoped credentials instead of static keys, and whether it holds a current SOC 2 report and will sign a BAA or DPA.
KollGuard's Questionnaires page has a starter template covering those categories, which you start from a template and link to the vendor in your register. A short catalog of commonly used agent sandbox vendors is also there as a quick-add convenience; it only records a name, website, and category and makes no claim about any vendor's security, so assessing the vendor itself is still on you.
Why use a third-party sandbox or VM provider instead of hosting agents ourselves?
It depends on what you already have and what the agent touches, not on which option is inherently safer. A third-party sandbox tends to win when you don't have a platform team to build and patch isolation infrastructure, when you want the agent isolated from your own production environment, when usage is bursty, or when you want a vendor's dedicated isolation expertise. In-house hosting tends to win when you already run container or VM infrastructure, the workload touches data that can't leave an environment you control, or data-residency rules constrain where it can run. Most teams end up hybrid — third party for lower-risk or dev/test agents, in-house for anything touching regulated production data. Whichever you pick, choose an isolation model on purpose (container, microVM, user-space kernel, WASM, or full VM) based on what you're protecting against, not the default a vendor ships.
KollGuard doesn't make this decision for you; the agent hosting and deployment checklist walks through the trade-offs and an isolation-model comparison. Once you've decided, Agent Watch and Agent Control let you record and monitor whichever option you chose.
How does a third-party-hosted agent keep continuing access to our enterprise data?
Give the agent its own identity and short-lived, narrowly scoped credentials issued per session or task — never a static credential baked into the sandbox image. Route its calls to your systems through a broker or proxy in your own network that authenticates the specific agent and task, issues a scoped credential for that one call, and enforces an egress allowlist. Default every data path to read-only and require logged human approval before any write reaches production data.
KollGuard doesn't broker those credentials — that pattern is something you build. What it does: each agent's runtime record lets you declare its data sources (classification, access level, credential type) and egress allowlist, then flags gaps automatically — write access on a static key, a regulated data source with no allowlist, or PHI exposure with no signed BAA on a linked vendor.
Limits: every field here is operator-declared. KollGuard doesn't inspect the actual hosting environment, and the egress check only compares against hosts the agent itself reports contacting — one that under-reports isn't caught.
Is there a cheat sheet for agent hosting and deployment?
Yes — the AI agent hosting and deployment checklist is built as one. It's an eight-step checklist (build vs. buy, pick an isolation model on purpose, per-agent identity with short-lived credentials, a data broker with an egress allowlist and read-only defaults, memory governance, vendor due diligence, and ongoing operations) plus a table comparing isolation models and a compact summary at the bottom of the page.
It's a reference, not a product feature — no account required, and reading it doesn't configure anything. Once you've made the decisions it walks through, Agent Watch and Agent Control are where you record and monitor them.
How do we govern several agents sharing one memory without compromising our source knowledge vault?
Treat the shared memory store as a governed data store, not scratch space. Know what's accumulating in it — conversation history, retrieved documents, embeddings — which agents and tenants can read it, whether it can hold regulated data, and whether writes into it get the same approval and audit as writes to your primary systems. Keep your source knowledge vault separate from what agents write into shared memory, so agents mutate their own working state rather than the material of record.
KollGuard's per-agent runtime record lets you declare a memory store as a data source with its own classification, access level, and credential type, and link its vendor with a "memory" role separate from hosting or model vendors. The posture monitor then flags a memory vendor with no current SOC 2, PHI exposure with no signed BAA on that vendor, or a regulated data source with no declared egress allowlist.
Limits: KollGuard is not a memory provider and doesn't inspect what's actually stored — these are fields you declare, checked for internal consistency, not audited against the real contents of the store.
Can we require human approval before an agent writes into our knowledge vault or another system?
Yes, if the agent is built to ask first. The runtime authorization gate lets an agent call one endpoint before a sensitive action, such as writing into a knowledge vault, and get back allow, deny, or pending. A pending request lands in the Agent Control approvals inbox for an admin to approve or deny, optionally with a reason the agent can read. The decision follows the agent's autonomy tier and tenant policy: only a fully autonomous tier can get an automatic allow, and only for a write inside its declared scope; anything less autonomous goes to a human.
A pending request expires after 15 minutes if nobody acts, and an allow is only good for 15 minutes once issued. The kill switch is re-checked on every poll, so an in-flight approval can still be cut off, and every decision is recorded and audited, with the request's target stored and shown redacted.
Limits: this is a cooperative gate. The agent has to call it and honor the answer — KollGuard doesn't block the write at the infrastructure level, so an agent that skips the call or ignores a deny can still act on whatever credentials it holds. Pairing the gate with credentials issued only after an allow, such as a short-lived write token from your own broker, makes a deny actually stick.
Does KollGuard host or run our agents?
No, not the agents you build and operate. KollGuard doesn't host, run, or sandbox your agents, and it doesn't enforce anything at the infrastructure level — you keep hosting and running them yourself, in-house or with a third-party provider. What KollGuard does run, and shows in your fleet alongside your own agents, are its own bounded platform agents — the scanners that assess your systems and a remediation agent that proposes fixes under a policy you set. That's KollGuard's own scanning and remediation work, not a substitute for your production agent infrastructure.
For the agents you run, KollGuard governs and watches them: an inventory with a hash-chained, tamper-evident run log; least-privilege checks against each agent's declared tools and scopes; a declared egress allowlist compared against what an agent reports contacting; optional output scanning for secret and PHI indicators, with the sample scanned in memory and never stored; and a kill switch per agent, including automatic disable after repeated failed runs.
Limits: all of this is either reported by the agent or declared by you. KollGuard doesn't inspect the actual runtime, container, or network boundary your agent runs in.
What happens when an agent misbehaves?
Depends on the kind of misbehavior, and none of these mechanisms reach into your infrastructure directly.
Three consecutive failed runs trigger auto-disable: KollGuard engages that agent's kill switch and raises a critical alert. A loop in a run's call graph — a repeated call, two agents handing control back and forth, a call nested inside itself — is flagged with a severity and, where the model is known, a priced token cost; an optional policy can escalate a high- or critical-severity loop straight into the kill switch. An hourly posture monitor separately checks each agent's declared runtime and data-access fields and alerts on gaps such as an autonomous agent with a dangerous tool and no declared isolation.
What the kill switch actually does: it stops KollGuard from accepting that agent's telemetry and makes the authorization gate deny its requests. It does not stop a process already running on your host, or revoke the credentials it holds — that part is on you. An admin can also engage a kill switch by hand, per agent or tenant-wide.
How do we show all of this to an auditor or a customer's security team?
Three things stack together. Agent Watch and Agent Control give a hash-chained, tamper-evident run log and an audited decision history. AI Governance maps your AI systems, each classified by EU AI Act risk tier, to ISO 42001, the NIST AI Risk Management Framework, and the EU AI Act, with technical controls auto-evidenced from Agent Watch and your existing findings. Vendor Watch, the subprocessor chain, and BAA tracking cover the third parties involved.
For an inbound questionnaire, the Security Questionnaires page drafts answers grounded in your real posture and any documents you add, with a confidence level and citations, and exports carry an "AI-drafted, human-reviewed" label.
Limits: KollGuard drafts and stores; it doesn't submit anything for you, and every answer is meant to be reviewed first. Vendor Watch results are web-verified, not authoritative — confirm anything material with the vendor. A drafted answer is also only as current as your last scan.
None of this replaces your own risk judgment or a tested kill switch. If you're setting up agent hosting from scratch, start with the AI agent hosting and deployment checklist. When you're ready to put an inventory, a run log, and an approval gate behind your own fleet, create a KollGuard account.
Get new posts by email
SOC 2, HIPAA, post-quantum readiness, and the engineering behind continuous compliance. No spam, unsubscribe anytime.