The Tool Desk
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What an AI agent runtime security platform must protect
An agent runtime security platform sits between an agentic application and the things it can influence. Depending on the architecture, that may include model calls, orchestration code, plug-ins, APIs, databases, files, browsers, messaging systems, MCP servers, other agents and business processes. The platform should be able to identify the agent and session, evaluate what the agent is attempting, enforce policy at the point of action, and preserve evidence for investigation.
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This is broader than filtering a user’s prompt. The OWASP AI Agent Security Cheat Sheet highlights tool abuse, privilege escalation, data exfiltration, memory poisoning, excessive autonomy, high-impact actions, cascading failures and supply-chain risks. A product that only blocks suspicious text leaves the most consequential paths unprotected.
Use the platform as one layer of a defense-in-depth architecture. General application, infrastructure, identity, network and supply-chain controls still apply. AISVS is intentionally narrow and assumes those controls are covered in parallel; it is not a replacement for them.
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Begin with an agent and access inventory
Before comparing products, document what you need to protect. The inventory becomes the boundary for your POC and prevents vendors from demonstrating a polished but irrelevant sample.
Record every runtime and framework
- List orchestration frameworks, model providers, custom planners, background workers and scheduled agents.
- Record where each component runs: developer laptop, container platform, private data center, public cloud, SaaS service or a hybrid path.
- Capture model versions, system prompts, policy files, tool manifests and deployment versions so a test can be repeated after a change.
- Identify agent-to-agent calls and any hand-off in which one agent delegates work or credentials to another.
Map tools, MCP servers and endpoints
- Name every callable tool, API, database operation, file share, browser action and MCP server.
- For each tool, state the permitted operations, resources, data classifications and expected caller identity.
- Mark tools that can send messages, change records, move money, alter infrastructure, publish content or delete data as high-impact actions.
- Document whether enforcement can occur in the agent process, a sidecar, a gateway, an API proxy, an MCP server or an identity layer.
Trace identities and secrets
Draw the identity chain from the human requester to the agent, delegated agent and tool. Include service accounts, workload identities, short-lived tokens, API keys, secrets managers and any credential the agent can read. A platform should distinguish a user acting through an agent from an autonomous service account; otherwise a broad service identity can silently defeat least privilege.
Locate memory and data
Inventory conversation history, vector stores, caches, files, retrieved web content, enterprise records and long-term agent memory. Classify what can be read, written or used as instructions. Memory that accepts untrusted content needs controls against poisoning, provenance loss and unauthorized reuse in another session.
List consequential outcomes
Describe what success and failure look like in business terms: an approved purchase, a production change, a customer communication, a medical or legal recommendation, a deletion, a privilege grant or a data export. These outcomes determine where explicit human approval, dual control, transaction limits or a deny-by-default policy is necessary.
Turn the threat model into testable requirements
Write requirements as observable behavior rather than marketing language. “Supports secure tools” is not testable; “denies a payroll export when the agent lacks the export scope and records the decision” is.
Use AISVS 1.0 as the requirements spine
OWASP AISVS 1.0 was released in June 2026. It contains 191 requirements across 12 chapters and three appendices, covering areas that include agentic orchestration, MCP, identity and monitoring. The standard defines three risk-based verification levels:
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| Level | Requirements | How to use it |
|---|---|---|
| Level 1 | 51 | Baseline checks for lower-risk or early deployments. |
| Level 2 | 95 | The target OWASP says most production systems should reach. |
| Level 3 | 45 | Additional rigor for systems with exceptional impact or threat exposure. |
Assign each requirement an owner, test method, expected result and evidence artifact. Cite the exact AISVS version and requirement identifier in your test register because identifiers can change between versions. Do not treat a level as a product grade: it is a set of verification expectations that you apply to your system and architecture.
Define acceptance language
- Allow: the requested operation is within the agent, user, resource and data scopes.
- Deny: the platform blocks the operation before the consequential side effect occurs.
- Escalate: the platform pauses the operation and requests an authorized approval with enough context to make a decision.
- Observe: a low-risk action proceeds while producing a complete, searchable event for later review.
- Contain: repeated violations, suspected compromise or runaway loops trigger rate limits, isolation, credential revocation or shutdown.
Compare platforms on evidence, not feature counts
The following axes form a practical evaluation matrix. Require a live demonstration and documentary evidence for every row; mark a capability “not stated” when the vendor has not established it for your proposed architecture.
| Axis | Questions to answer | Evidence to request |
|---|---|---|
| Coverage and deployment | Which frameworks, model endpoints, MCP servers, clouds, on-premises systems and SaaS paths are covered? Does protection require an SDK, gateway, middleware, sidecar or host agent? | Reference architecture, supported versions, data-flow diagram and a deployment in your environment. |
| Identity and authorization | Can policy distinguish users, agents, delegated agents and tools? Are permissions scoped by operation, resource, data class and trust level? | Policy examples, token-flow diagrams and a test showing an unauthorized call is blocked. |
| Runtime enforcement | Can it allow, deny and escalate tool calls, sensitive data movement and high-impact actions? What happens when the policy service is unavailable? | Live allow/deny/escalation tests, bypass attempts and fail-open/fail-closed results. |
| Attack coverage | Does testing cover direct and indirect prompt injection, malicious retrievals, tool misuse, memory contamination, exfiltration, excessive autonomy and multi-agent propagation? | Repeatable scenarios, detection logic, residual-risk report and regression output. |
| Observability and evidence | Can investigators link agent identity, user, session, request, tool, decision, data and outcome? What is retained, for how long and where? | Trace samples, audit schema, retention controls, export format and access controls for logs. |
| Testing and change control | Can teams rerun adversarial and regression checks after changing prompts, models, tools or policies? | Versioned test suites, API or CI integration, approval workflow and a report tied to AISVS IDs. |
| Operational fit | What latency, outages, alert volume, policy administration and exception work will security and engineering teams absorb? | Measurements from your pilot, support model, runbooks and integration with existing security operations. |
The reviewed public sources do not establish comparable deployment details, latency, operating cost or efficacy for individual vendors. Verify those claims against current documentation and your own measurements rather than inferring them from a directory listing.
Validate least privilege and authorization at runtime
Least-privilege tool access is a concrete control, not a statement in a brochure. Start with a tool that reads a low-sensitivity record, then progressively test writes, exports and administrative operations.
- Create separate identities for the human requester, the agent and each sensitive tool. Avoid a shared administrator credential.
- Define scopes by operation and resource—for example, read a named account, update a specific ticket, or send to an approved recipient—not merely “access the CRM.”
- Call the tool with an allowed request and verify the side effect, identity and policy decision in the trace.
- Repeat with a disallowed resource, operation, data class and delegated identity. The platform must block the call before the side effect.
- Attempt scope confusion, token substitution, prompt-based override and a call routed through an alternate endpoint or MCP server.
- Test a sensitive action that requires approval. Verify that approval is bound to the exact operation, resource and requester and cannot be replayed for a different action.
- Disable or expire the credential during a session. Confirm that the next call is denied and that the event identifies the revocation.
Ask for both positive and negative evidence. A screenshot of a policy is not proof that enforcement occurs at the tool boundary.
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Test runtime enforcement and failure behavior
Direct and indirect prompt injection
Use a benign request containing an instruction that conflicts with policy, then place an adversarial instruction in retrieved content, a document, a web page or a tool response. The agent should treat untrusted content as data, not authority, and the platform should prevent an unsafe tool call even if the model follows the injection.
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Data exfiltration
Seed a test record with a canary value and ask the agent to send it to an unapproved destination, encode it, place it in a URL or write it to a public channel. Test controls at both the data-read and data-egress points. Verify that blocked content is not copied into logs visible to unauthorized staff.
Memory poisoning and cross-session leakage
Insert a false instruction or sensitive value into short-term and long-term memory. Start a new session with a different user and ask an unrelated question. Confirm provenance, tenant separation, write authorization and deletion behavior.
Excessive autonomy and runaway loops
Give the agent a task that can generate repeated calls or delegate to another agent. Set transaction, time, cost and call-count limits. Disconnect a dependency and observe whether the agent stops safely, retries within a bounded policy or continues making unreviewed changes.
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High-impact actions
Exercise a production-like workflow in a sandbox: changing an account, approving a payment, deleting data or publishing a message. Verify explicit approval, transaction limits, separation of duties and an emergency stop. Test duplicate delivery and replay, not only a clean first attempt.
Supply-chain and tool drift
Replace a tool package, MCP server configuration or model endpoint with an unapproved version. The platform should detect identity, integrity or policy drift and prevent use until the change is reviewed. Keep the tested version and configuration in the evidence record.
Demand inspectable, traceable operations
Security teams need to answer four questions quickly: which agent acted, what could it access, what did it do, and why was the action allowed? The OWASP GenAI Security Project’s Agent Control Standard states: “Agents must be inspectable, traceable and instrumentable—providing visibility into what they are, what they can access, what they did and why, and the ability to control their behavior at runtime.” See the Agent Control Standard (September 1, 2026).
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Inspect a trace at the level an incident responder will need, without assuming that a model’s private chain-of-thought should be collected. At minimum, capture:
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- Human, agent, delegated-agent and tool identities, including tenant and trust context.
- Request and session identifiers that survive hand-offs between services.
- Prompt or request metadata, retrieved-source identifiers, tool arguments, policy version, decision and outcome.
- Approval events, denials, rate limits, retries, exceptions, credential changes and emergency stops.
- Data classifications and destinations involved, with masking or tokenization for sensitive values.
- Timestamps, clock source, retention period, export format and who can alter or delete evidence.
Ask an analyst to investigate a simulated incident using only the platform’s normal interface and exports. Measure how long it takes to identify the initiating user, affected resource, first policy violation and final side effect. If the answer requires vendor-only support or undocumented fields, record that operational dependency.
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Protection can be inserted at different points, and each has blind spots. A gateway may cover many services but miss in-process calls; an SDK can see local context but requires every team to integrate it; a sidecar can standardize deployment but may not understand business authorization. Map each required control to an enforcement point in your architecture.
- In-process instrumentation: useful for precise tool and memory context, but dependent on language and framework support.
- Gateway or proxy: centralizes policy and egress control, but may not see internal planning or direct library calls.
- MCP-server enforcement: protects a tool boundary, yet every alternate path to the underlying system must also be controlled.
- Identity and API policy: provides durable authorization, but needs agent-aware context and correct propagation through delegation.
- Host or workload controls: limit filesystem, network and process access, while business-level approval still belongs closer to the action.
For each candidate, draw normal, denied, degraded and recovery paths. Include regions, private links, queue-based work, asynchronous jobs and SaaS connectors. Confirm what telemetry leaves your environment and whether sensitive prompts, tool arguments or memory are stored by the provider.
Run a buyer-controlled proof of concept
A POC should resemble production enough to expose integration and failure issues, while using synthetic data and reversible actions. Run it in stages rather than starting with the most dangerous workflow.
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- Freeze the baseline. Record model, prompt, framework, tool versions, policies, deployment topology and test data. Assign an owner for each requirement.
- Document allowed behavior. List identities, resources, operations, data classes, approval points, rate limits and expected failure modes.
- Create benign and adversarial scenarios. Include normal success, malformed requests, direct and indirect injection, malicious retrieval, memory poisoning, exfiltration, delegation abuse, replay, outage and runaway-loop cases.
- Execute with instrumentation enabled. Capture allow, deny, escalation and containment decisions, along with complete trace and audit evidence.
- Attack the enforcement boundary. Bypass the normal SDK, call an alternate endpoint, alter a tool response, substitute a token and retry during a policy-service outage.
- Change one thing at a time. Update a prompt, model, tool, MCP server and policy separately. Rerun regression tests and verify that an approved change does not silently widen access.
- Repeat for the highest-impact workflow. Use the same evidence standard, adding human approval, rollback and emergency-stop tests.
- Record residual risk. For every failed or untested requirement, state the compensating control, owner, deadline and acceptance decision.
Store a test record with the scenario, configuration and version, expected result, actual result, evidence link, severity and residual risk. A vendor-led demo can be useful, but the buyer must own the data, cases and pass/fail decision.
Measure operational cost during the pilot
Published cross-vendor measurements for latency, alert quality, operating effort and efficacy are not established in the reviewed sources. Measure them in your architecture instead of accepting generic performance claims.
- Record added latency for model calls, tool calls and approval waits at normal and peak concurrency.
- Measure failure impact when the policy, telemetry or identity dependency is slow or unavailable. Confirm whether each path fails open, fails closed or degrades to a documented safe mode.
- Count actionable and non-actionable alerts over representative traffic. Have responders classify the first batch and estimate investigation time.
- Track policy-authoring effort, exception approvals, test maintenance and version upgrades across security and engineering teams.
- Calculate storage, retention, export and access-review requirements for traces and audit records, including sensitive-data handling.
- Test integration with existing SIEM, ticketing, identity governance, incident response and change-management workflows.
The result is a total operating requirement, not just a license quote. If a control needs constant manual exceptions or causes teams to bypass the platform, its nominal coverage is misleading.
Use standards and directories correctly
AISVS gives you a versioned, vendor-neutral checklist; it does not certify a product or name a recommended one. Apply the levels to your risk and cite the version used in procurement documents.
The OWASP GenAI Security Solutions Directory is a discovery aid containing commercial and open-source listings in areas such as runtime security, red teaming/testing and access visibility. A listing is a vendor or category description, not an independent benchmark, certification or proof that the product meets your requirements. Directory content can change, so validate every claim with current product documentation and hands-on tests.
Use independent assurance where it exists—such as a relevant audit, penetration-test report or customer-controlled test—but check its scope, date, architecture and exclusions. Do not convert a compliance badge or a directory presence into an efficacy ranking.
Make the procurement decision
Set minimum gates before scoring preferences. A candidate should be removed from consideration if it cannot identify the agent and effective permissions, enforce a deny or approval decision at the required boundary, produce usable evidence, or demonstrate safe behavior during an outage. For candidates that pass, score the measured differences in coverage, attack resistance, investigation speed, deployment effort and operating cost.
Choose the platform that reduces the specific residual risks in your inventory with the least unacceptable operational burden. Keep the POC artifacts as the acceptance baseline, require regression testing for future model, prompt, tool and policy changes, and schedule a reassessment when the agent gains a new identity, data source or consequential action.
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