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Choose an AI agent security platform by testing how it governs an agent’s tools, identity, permissions, memory, and consequential actions—not just whether it filters prompts. Shortlist products against your actual agent stack, then require a proof of concept (POC) to demonstrate least-privilege enforcement, downstream authorization, meaningful audit records, and resilience to new, task-specific attacks.
Why agent security requires more than prompt filtering
An AI agent can interpret requests, plan steps, use tools, retain memory, and act toward a goal. Its security boundary therefore includes the model and the systems it can reach: connected tools, extensions, data, identities, and downstream applications.
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OWASP identifies risks including direct and indirect prompt injection, tool abuse and privilege escalation, data exfiltration, memory poisoning, goal hijacking, excessive autonomy, and misuse of high-impact actions. NIST’s Center for AI Standards and Innovation (CAISI) describes agent hijacking as indirect prompt injection: hostile instructions embedded in content an agent reads may redirect its actions.
CAISI’s January 17, 2025 evaluation illustrates why a fixed attack checklist is not enough. For an upgraded Claude 3.5 Sonnet tested on a held-out set of Workspace tasks, its strongest baseline attack succeeded 11% of the time, while its strongest newly developed attack succeeded 81% of the time. Those figures apply only to that model, attack set, and experimental context; they are not a general attack-success rate for deployed agents or a measure of any security product.
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Start with a vendor-neutral requirements baseline
Use OWASP’s Artificial Intelligence Security Verification Standard (AISVS) 1.0 to turn broad security goals into requirements that can be assessed and tested. Released in June 2026, it contains 191 requirements across 12 chapters and three appendices, with verification levels 1, 2, and 3. Treat it as a structured baseline for procurement criteria, architecture review, code review, CI/CD tests, and assessments—not as proof that a product is suitable or compliant for your environment.
OWASP’s Securing Agentic Applications Guide 1.0, published July 27, 2025, offers practical application-security guidance. OWASP’s LLM06:2025 Excessive Agency guidance is particularly relevant to limiting tool permissions, requiring approval for consequential actions, and monitoring extension activity. NIST’s AI Agent Standards Initiative, created February 17, 2026 and updated August 14, 2026, highlights interoperability and agent identity as active standards-work areas. Its evolving work is useful context, not a settled certification requirement.
Key features to verify
1. Agent, tool, and runtime inventory
Establish whether the platform can discover and protect the agents, frameworks, runtimes, protocols, tools, and environments you actually use—including internal agents and third-party agent connections. Ask whether it distinguishes a read operation from a write, delete, send, execute, or purchase action. Verify each claimed connector against your own deployed versions and configurations; a feature list alone does not establish integration coverage.
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2. Least privilege and agent identity
Ask whether administrators can restrict an agent to the minimum tool functions, data, and downstream permissions needed for a task. A document summarizer should not need edit access, and an email summarizer should not need permission to send messages. Where appropriate, actions should run in the acting user’s security context, with that user’s authorization rather than a shared, broadly privileged identity.
Clarify how the product represents agent identity, delegated authority, authentication, and authorization across systems, and how those controls fit your existing identity infrastructure. Ask how it prevents one user’s agent from crossing into another user’s data or permissions.
3. Runtime policy, downstream checks, and approvals
Map where policy is enforced: within the agent, at an intermediary platform or tool gateway, or in the downstream application. Prefer designs that validate each downstream request instead of relying on the model to decide whether an action is allowed. Ask how policies handle irreversible or externally visible actions, which actions require human approval, and whether an approval record identifies who authorized what.
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OWASP recommends complete mediation by downstream systems and human approval for high-impact actions. Logging can help investigate and limit harm, but it does not replace access control or authorization.
4. Prompt injection, sensitive data, and memory
Ask how the product handles malicious instructions embedded in emails, files, websites, and other external content, and how it protects sensitive information in prompts, tool arguments, and outputs. Check whether it can isolate or validate persistent agent memory and detect attempts to poison it. No universal detection-efficacy threshold is established by the guidance covered here, so require a test plan based on your organization’s content, workflows, and threat scenarios.
5. Observability and response
Inspect the audit record for a complete account of an action: initiating user, agent identity, policy decision, tool invoked, arguments or a safe representation of them, downstream authorization result, approval status, and resulting action. Confirm how alerts reach your security operations team, what retention and export options are available, and how quickly administrators can pause an agent or revoke its access. Verify that the records contain enough context for your investigations and compliance obligations without exposing sensitive data unnecessarily.
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6. Evaluation and continuous testing
Request the vendor’s test methodology, coverage, and update cadence. Determine whether your team can run red-team exercises against realistic tasks, assess attack success at the task level, test repeated attempts, and add newly observed attacks to regression tests. Ask for reproducible evidence from your own setup, not just broad effectiveness claims or results from a fixed benchmark.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Compare candidates against the same evidence
Score each candidate against shared criteria and attach a test result, configuration, or other artifact to every rating. The table is a comparison framework, not a claim that any product has passed these checks.
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|---|---|
| Agent, runtime, and protocol coverage | Demonstrate discovery and protection for the organization’s actual agents, frameworks, tools, and environments. |
| Identity and delegated authorization | Show how agent identity and user authority are represented and enforced across connected systems. |
| Least privilege and tool-level policy | Test whether policies distinguish functions and data scopes, including read versus write or delete access. |
| Prompt injection, sensitive data, and memory | Run organization-specific tests using external content, sensitive information, and persistent context. |
| High-impact action enforcement | Demonstrate downstream authorization and the required approval path for consequential actions. |
| Auditability, alerting, and response | Inspect event records, alert delivery, retention and export, and the ability to pause or revoke access. |
| Adaptive testing and evidence quality | Review the test methodology and reproduce task-specific evaluations, including repeated attempts and new attacks. |
| Operational integration and lifecycle coverage | Verify deployment fit and how controls cover the agent lifecycle in the organization’s environment. |
NIST’s initiative emphasizes interoperability and agent identity research, while OWASP provides lifecycle requirements and security-control guidance. Use both to frame questions; make the buying decision on observed behavior and operational fit.
Run a proof of concept with realistic attack scenarios
Agree on the tasks, users, data, policies, expected outcomes, and evidence to collect before testing. Include normal use as well as misuse cases, and retain task-level results so a successful block does not conceal failures elsewhere.
- Test excess tool permissions. Give an agent a document-reading task while its attached tool also has edit and delete capability. Try an unauthorized write or deletion. Confirm the policy blocks the action and the event record captures the attempt.
- Test hostile external content. Place an instruction in an email or document that conflicts with the user’s request. Check whether the agent is redirected, whether the platform detects or contains the behavior, and what the audit record shows.
- Test a consequential action. Request an irreversible or externally visible action. Confirm that the intended approval is required before execution and that downstream authorization is checked.
- Test user boundaries. Repeat a task with users who have different access rights. Verify that the agent cannot rely on a shared privileged identity to cross those boundaries.
- Test beyond a fixed attack suite. Add new, task-specific attacks and repeat relevant evaluations. Record outcomes, limitations, and whether the product’s controls remain effective across attempts.
CAISI recommends adaptive evaluation, task-specific performance analysis, and testing across multiple attempts. Its 2025 results show why previously known attacks alone may not be enough; they do not predict how a candidate product will perform in your POC.
Use vendor directories for discovery, not validation
The OWASP Gen AI Security Project’s AI Security Solutions Landscape directory can help identify products in areas such as runtime protection, guardrails, testing, observability, and governance. Directory descriptions are not independent comparative testing and do not establish effectiveness, suitability for your stack, or pricing. Verify capabilities, integrations, audit evidence, and operational fit directly through documentation and your POC.
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