Do not decide from a User-Agent string or an IP address alone. Determine three separate things: whether the request is automated, whether the requester can prove the identity it claims, and whether the requested action is authorized and safe in context. Headers and network origin are useful clues. A validated HTTP message signature, checked against a trusted public-key directory, is stronger identity evidence. Neither identity nor a valid signature makes every action harmless: authorization, account state, request sequence, and transaction risk still require separate controls.
The three decisions you must keep separate
“AI agent traffic” describes how a request is produced, not whether it is good or bad. A shopping assistant acting for a customer, a search crawler, an accessibility workflow, and a credential-stuffing tool may all use automation. Treating every automated session as fraud blocks useful activity; treating every self-described agent as trusted creates an easy bypass.
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1. Is the request automated?
Look at request timing, navigation patterns, browser characteristics, session continuity, and endpoint usage. Automation can be obvious, subtle, or mixed with human actions. This classification is about behavior, not identity.
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A claimed product name in a header is not authentication. AWS notes that User-Agent values can be spoofed, while Google treats self-declared or agent-like traffic as suspected unless it has an independently verified identity. A cryptographic signature validated with the publisher’s current public key supplies substantially better evidence of who signed a request and whether the covered message changed.
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3. Is this particular action authorized and safe?
Authentication answers “who signed this?” and message verification answers “was the signed request altered?” They do not answer “may this identity change an account, consume inventory, apply a coupon, or submit payment?” Scope permissions by purpose, resource, account, and action. Visa’s Trusted Agent Protocol separates agent recognition from linked consumer or device identity and payment-container information; participation is not universal.
Why User-Agent and IP checks cannot prove legitimacy
Use User-Agent, IP, TLS characteristics, and reverse-DNS checks for discovery and corroboration, not as a sole allow rule. A malicious client can copy a familiar string, route through a shared cloud address, or rotate addresses faster than a static list can follow. Conversely, legitimate agents may use infrastructure shared with other customers or change their network footprint.
For a known crawler that publishes a network-verification procedure, follow that operator’s current documentation and validate the current addresses or reverse DNS where the procedure calls for it. There is no universal crawler IP registry in the material available here, so a single cross-provider allowlist would be misleading.
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Run a review period before using a new agent classification to deny traffic. Store enough context to reproduce the decision without collecting unnecessary personal data.
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- Claimed identity: User-Agent, signature-agent value, declared organization, and any published agent identifier.
- Verification result: verified, invalid, expired, unknown, missing signature, key-fetch failure, or intermediary failure.
- Request context: timestamp, method, host, path, response status, latency, source network, and proxy or CDN hop.
- Session and account context: session identifier, authentication state, account age, consent or delegation record, and linked consumer or device information where applicable.
- Business events: product views, inventory holds, coupon attempts, account changes, checkout steps, declines, refunds, and chargebacks.
- Policy action: observed, challenged, rate-limited, endpoint-restricted, allowed, or blocked, with the rule version that produced it.
Keep verified and suspected automation as distinct classes in dashboards and alerts. Sample legitimate task completion and false positives during the review period. A rule that lowers bot volume but also prevents real customers from searching or paying is not a successful control.
How signed requests establish stronger identity evidence
Web Bot Authentication (WBA) uses asymmetric cryptography and HTTP Message Signatures. The agent operator publishes a public key in a directory. The agent signs selected request components with the corresponding private key. Your edge or application retrieves the trusted key, validates the signature and its validity window, and exposes the result to policy. AWS describes outcomes such as verified, invalid, expired, and unknown bot in its WAF Bot Control guidance.
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- It can bind a request to the holder of a private key and detect changes to the covered components.
- It depends on the verifier trusting the key directory, correctly implementing canonicalization, and handling key rotation and revocation.
- It does not prove that the signer is acting for the user you expect, that the user consented to this operation, or that the operation is commercially safe.
- It does not protect a server from a compromised legitimate agent account or an authorized agent abusing its permitted scope.
Follow the current RFC 9421 and WBA implementation guidance for covered components, expiry, nonce or replay handling, canonicalization, key rotation, and failure behavior. Do not accept a header merely because it has a plausible name. Verify the signature against the correct key and the exact method, authority, path, query, and other components your policy requires.
Example: signed requests from a cloud browser
OpenAI’s current Cloud browser allowlisting documentation describes requests carrying Signature, Signature-Input, and Signature-Agent. The documented identity is https://chatgpt.com, and its public-key directory is https://chatgpt.com/.well-known/http-message-signatures-directory. Supported edge providers have provider-specific recognition instructions. Preserve these headers through every CDN, WAF, reverse proxy, and service mesh hop; stripping or rewriting them causes verification to fail. The same page states that, at launch, Cloud browser cannot sign in to websites or complete payments, so its presence is not evidence of a completed checkout.
Authorize by purpose and least privilege
After identity verification, map the agent to the smallest useful permission set. Keep public reading, personalized browsing, account operations, and payment authorization on separate paths with separate controls.
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| Purpose | Typical permitted scope | Additional decision |
|---|---|---|
| Public crawler | Read-only public pages, robots and rate policies | Verify identity where available; prevent access to private records and mutation endpoints. |
| Product or availability agent | Catalog, price, stock, shipping estimates | Apply per-session and per-account quotas; watch for bulk extraction and inventory hoarding. |
| Signed-in assistant | Only the user-delegated account resources | Require an explicit delegation record, step-up checks for sensitive changes, and normal session protections. |
| Checkout or payment workflow | Only the exact order and payment operation authorized by the user | Run fraud, velocity, device, payment, and confirmation controls independently of agent identity. |
Visa’s Trusted Agent Protocol specifications describe signed agent recognition together with linked consumer or device identity and payment information. They are a protocol framework and Visa implementation, not proof that every merchant or agent supports the model.
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Assess behavior across sessions, accounts, and transactions
Fraud often appears as a distributed pattern rather than a single spectacular request. Evaluate the sequence and business effect of actions, not just requests per second.
- Credential abuse: many login attempts, password resets, or new-device challenges across accounts.
- Data extraction: systematic traversal of catalog, customer, or policy endpoints beyond what a normal task requires.
- Inventory and coupon probing: repeated holds, releases, coupon permutations, or checkout attempts without completed orders.
- Low-and-slow distribution: small volumes spread across many accounts, IPs, sessions, or merchants that evade one-origin thresholds.
- Synthetic identity or business material: apparently plausible but inconsistent registration, tax, shipping, or payment information.
- Outcome mismatch: high declines, refunds, chargebacks, abandoned carts, or repeated policy challenges after apparently valid identity checks.
These signals are investigative leads, not proof of fraud individually. Correlate them over an appropriate time window and across the entities your privacy and retention policies permit.
Visa’s Fall 2025 Biannual Threats Report says underground-forum mentions of “AI Agent” increased 477% as criminals discussed automating social engineering, data extraction, and transaction execution. The figure is a report-specific underground-forum measure, not a percentage of web traffic. The same report attributes a 25% increase in malicious bot-initiated transactions over the prior six months, including a 40% increase in the United States. Those are Visa threat-intelligence findings for the stated period, not independent estimates of every site’s current fraud rate. No source establishes a universal legitimate-versus-fraudulent percentage for AI-agent traffic.
Use a graduated response instead of a binary allowlist
| Stage | When to use it | Controls |
|---|---|---|
| Observe | Identity is unknown or newly detected, with no harmful behavior | Log, sample, and compare task completion; do not grant sensitive access. |
| Rate-limit | Automation is useful but volume or repetition is excessive | Apply per-agent, session, account, endpoint, and transaction quotas; return clear retry behavior. |
| Restrict | Risk concentrates on sensitive operations | Allow public reads while requiring stronger checks for login, inventory holds, coupon use, or account changes. |
| Challenge | Identity or behavior needs additional assurance | Require user confirmation, step-up authentication, device or payment checks, or delegated-consent proof. |
| Block | Evidence shows abuse, replay, invalid signatures, or policy evasion | Deny the narrowest scope possible, preserve evidence, and provide an appeal or recovery path for false positives. |
Do not allow every request from a claimed vendor identity. Do not block every session absent from a recognized-agent directory. Re-evaluate rules as recognized identities, key directories, edge integrations, and agent behavior change.
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A practical implementation sequence
- Map the actions. List public reads, account mutations, inventory operations, checkout, payment, and administrative endpoints. Mark which ones can cause financial, privacy, or availability harm.
- Instrument before enforcement. Add structured fields for claimed identity, signature status, source context, account or session, business outcome, and policy action. Confirm that logs survive proxy and CDN routing.
- Classify automation. Use behavior and conventional headers to identify likely automated sessions, but label the result as a suspicion or observation, not authentication.
- Publish or consume keys safely. For supported WBA identities, use the operator’s documented directory and cache keys according to its freshness guidance. Monitor retrieval errors, expiry, rotation, and revocation.
- Verify the complete message. Check the signature algorithm, key identity, covered components, timestamp or expiry, nonce or replay protections, and the exact request received by the policy layer.
- Test intermediary paths. Send representative requests through each CDN, WAF, reverse proxy, and origin route. Confirm that signature headers and covered values are unchanged and that failures are observable.
- Attach permissions to purpose. Give a public crawler read-only access; give a shopping workflow only the catalog or availability scope it needs; require independent authorization for account and payment actions.
- Correlate business risk. Join request telemetry with login, inventory, coupon, order, payment, refund, and chargeback events. Look for distributed and low-velocity patterns.
- Roll out the policy ladder. Start with observation, then introduce narrow rate limits or challenges. Measure legitimate completion, customer support contacts, false positives, and fraud outcomes before expanding enforcement.
- Review continuously. Version rules, rotate trusted keys, revisit provider documentation, and investigate new verified or suspected identities rather than assuming the initial inventory is complete.
How the documented approaches differ
The available documentation covers complementary capabilities rather than a head-to-head accuracy test.
| Approach | Identity evidence | Operational strengths | Limits to plan for |
|---|---|---|---|
| User-Agent and IP | Self-claim and network clues | Simple discovery and broad compatibility | Spoofing, shared infrastructure, address changes; not sufficient for allow decisions. |
| Google agent monitoring | Verified and suspected categories in its dashboard | Visibility into recognized and suspected sessions; inventory expands over time | Product-specific coverage; an unrecognized result is not proof of absence. |
| AWS WAF Bot Control WBA | Public-key directory and signed requests | Verification labels can feed WAF policy; AWS says WBA support was available in Bot Control from November 2025 | Requires correct key lifecycle, signature handling, and WAF integration. |
| Visa Trusted Agent Protocol | Signed agent recognition plus consumer, device, and payment context | Useful framework for merchant and payment interactions | Participation and support are not universal; protocol recognition does not replace fraud controls. |
| Provider-specific signed traffic | Published identity and HTTP Message Signatures | Lets an edge distinguish a documented agent from an impersonator | Headers may be lost in transit; provider identities, directories, and capabilities can change. |
Provider examples and what they mean
Google Cloud Fraud Defense
Google’s documentation explains verified and suspected agent sessions and an Agent overview dashboard. Use those categories as visibility inputs to your own authorization and rate policies, not as a universal fraud verdict. The recognized-agent infrastructure is described as expanding, so schedule periodic reviews.
AWS WAF Bot Control
AWS describes WBA verification with public keys, signed requests, and WAF labels that can be used in policy. Its November 2025 availability statement is an implementation detail of AWS Bot Control, not a claim that every edge service recognizes every agent.
Visa Trusted Agent Protocol
Visa’s specifications focus on merchant interactions in agentic commerce and define how agent identity can be linked to consumer, device, and payment information. Treat the framework as a way to structure these exchanges; confirm which counterparties actually implement it.
NIST’s standards work
The NIST AI Agent Standards Initiative, updated August 14, 2026, describes ongoing work on standards, open protocols, agent identity, and authorization. It is an initiative, not a finalized universal deployment standard or a ready-made allowlist.
Common implementation failures and their fixes
Trusting a header because it looks official
Failure: an allow rule matches a vendor name in User-Agent or Signature-Agent. Fix: require a valid signature where supported, then apply purpose and behavior controls.
Verifying a signature but skipping authorization
Failure: every verified request receives account or checkout privileges. Fix: map permissions to delegated purpose and require independent user, payment, and fraud checks for sensitive actions.
Breaking signatures at the edge
Failure: a proxy strips headers, normalizes the path, or rewrites the host before verification. Fix: test every hop, preserve covered components, and distinguish missing, invalid, expired, and unknown results.
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Using one global rate threshold
Failure: low-and-slow activity distributed across accounts remains invisible, while legitimate bursts are blocked. Fix: combine per-session, per-account, per-endpoint, and transaction-level signals over time.
Assuming an unknown agent is malicious
Failure: newly recognized or legitimate automation is denied solely because a directory has not listed it. Fix: observe first, limit sensitive scope, and challenge when risk warrants it.
Assuming a verified agent is benign
Failure: a compromised key, delegated account, or abusive but valid workflow passes every identity check. Fix: monitor outcomes, rotate and revoke keys, and retain normal fraud and authorization controls.
What to review before changing an allow rule
- Is the identity verified cryptographically, or merely self-declared?
- Which exact key directory, identity, and covered request components does the verifier trust?
- Did every intermediary preserve the signature headers and canonical request values?
- What resource and action is being requested, and what user or merchant authorization supports it?
- Could the same pattern be distributed across accounts, sessions, addresses, or merchants?
- What happens when the signature is missing, expired, invalid, unknown, or temporarily unverifiable?
- Can you measure legitimate completion and false positives after the rule changes?
- When were the provider documentation, key directory, and recognized-agent inventory last checked?
Bottom line
Build a layered decision, not a bot-name list. Use headers and IP data to find candidates, cryptographic signatures and trusted key directories to strengthen attribution, least-privilege authorization to limit what an identified agent may do, and cross-session business telemetry to detect fraud. Keep verified, suspected, and unknown traffic separate; start with observation and graduated controls; and treat provider documentation, keys, and recognized identities as moving parts that require ongoing review.
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