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This skill acts as a central router for configuring AWS WAF to secure web applications and APIs. It provides structured procedures for creating web ACLs, managing rule sets, implementing bot and fraud control, and configuring logging. The skill emphasizes a secure-by-design approach, requiring logging to be enabled before tuning and enforcing strict header-stripping to prevent spoofing. It covers the full lifecycle of WAF management, from initial setup and association with resources like CloudFront and ALB to advanced mitigation strategies for volumetric abuse and credential stuffing.
What it does
- Creates and associates web ACLs with CloudFront, ALB, API Gateway, and AppSync.
- Configures AWS Managed Rules, rate-based rules, and custom IP or geographic match rules.
- Implements Bot Control and Fraud Control to prevent account takeover and fake-account creation.
- Provides workflows for logging, request sampling, and tuning rules in Count mode.
- Enforces security best practices like header stripping and least-privilege IAM.
- Routes users to specific, self-contained procedures for complex WAF tasks.
When to use it
- When you need to protect a web application or API from layer 7 exploits and HTTP floods.
- When implementing bot detection or fraud prevention for login and signup endpoints.
- When you need to tune managed rules to reduce false positives without blocking legitimate traffic.
- When you need to recover the real client IP or secure forwarded headers behind a CDN.
- When you need to manage AI and LLM crawler traffic.
Advantages
- Reduces risk of misconfiguration by enforcing a logical, step-by-step tuning workflow.
- Prevents accidental blocking of legitimate traffic through mandatory Count-mode tuning.
- Ensures security consistency by mandating header-stripping when forwarding signals.
- Provides clear guidance on WCU budget management and rule group selection.
- Centralizes complex WAF procedures into a single, reliable reference source.
Usage examples
- “How do I set up AWS WAF to block HTTP floods on my Application Load Balancer?”
- The agent will guide you through creating a regional web ACL, associating it with your ALB, and configuring a rate-based rule to throttle requests based on IP or session token.
- “I am seeing false positives from the Core Rule Set. How do I fix this?”
- The agent will instruct you to check your WAF logs to identify the specific rule ID triggering the block, then use the RuleActionOverrides feature to set that specific rule to Count mode.
- “How can I protect my login page from credential stuffing?”
- The agent will guide you through enabling Fraud Control (Account Takeover Prevention) and configuring the necessary logging and signal-forwarding rules.
- “I need to allow traffic only from specific countries. What is the procedure?”
- The agent will provide the steps to create a geographic match rule and configure the web ACL's default action to block traffic outside of your allowed list.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/aws/waf/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip waf.zip -d .agents/skills
Documentation by AWS
AWS WAF
Overview
Domain expertise for configuring AWS WAF, the web application firewall that filters HTTP and HTTPS traffic to CloudFront distributions, Application Load Balancers, API Gateway REST APIs, and AppSync GraphQL APIs. Covers web ACL creation and association, AWS Managed Rules, rate-based rules, match rules (IP set and geographic), Bot Control and the signal-forwarding workflows built on top of it, Fraud Control for logins and signups, AI and LLM crawler management, and the logging that every tuning workflow depends on.
This skill is a router. Each customer task maps to a procedure file under references/. Read the
matching reference in full before acting, then follow its constraints and steps. The reference
files are self-contained: each carries its own decision tables, constraints, procedure, and
troubleshooting.
Execute commands using the AWS MCP server when connected (sandboxed execution, audit logging,
observability). Fall back to the AWS CLI otherwise. A web ACL's scope is fixed at creation: a
CloudFront web ACL must be created in us-east-1 with CLOUDFRONT scope, while a regional web ACL
(Application Load Balancer, API Gateway, AppSync) is created in the resource's Region with
REGIONAL scope.
Which WAF task do you need?
Routing notes
Logging comes before tuning. Every Count-mode tuning workflow assumes logging and request sampling are on. If the customer has not set up logging, run that reference first; otherwise Count-mode tuning has nothing to read.
Web ACL scope is fixed at creation. A CloudFront web ACL is
CLOUDFRONTscope inus-east-1; a regional resource needs aREGIONALweb ACL in its own Region. Scope cannot be changed later, so the creating reference settles it before anything is built.Bot Control is a chain, not one task. Protecting against bots is the on-ramp (turn on, choose Common vs Targeted, observe). Turning labels into a confidence signal, forwarding that signal, and deciding what the application does with it are three separate references that build on it in that order. The header-stripping reference is the mandatory safety companion whenever a signal is forwarded to the origin.
Common vs Targeted is not a soft choice. Common only catches self-identifying bots and known-bad IPs. For login, checkout, or any high-value endpoint facing evasive bots, Targeted with the application integration SDK is required. The bots reference pushes Targeted for real bot threats rather than presenting it as optional.
Rate limiting vs Fraud Control. Rate-based rules blunt volumetric HTTP floods. Credential stuffing and fake-account creation are account-based abuse that rate limiting misses; those go to the Fraud Control reference (ATP and ACFP), not the rate-based reference.
Forwarded headers need the strip rule. Any time the customer forwards a signal or the client IP to the origin in
x-amzn-waf-*headers, the inbound-header-stripping reference is required to prevent spoofing. The confidence-signal, interpolation, and client-IP references all point at it.What lives in other skills. L3/L4 DDoS protection and Shield cost-protection credits are the shieldadvanced skill. Multi-account WAF rollout is the firewallmanager skill. CloudFront and Application Load Balancer configuration are their own skills. This skill builds the WAF rules; it does not configure the resources it protects.
Security Considerations
AWS WAF is itself a security control, so misconfiguration directly weakens an application's defenses. Apply these across every reference:
Least-privilege IAM. You MUST grant only the specific
wafv2:actions a task needs (for examplewafv2:CreateWebACL,wafv2:GetWebACL,wafv2:UpdateWebACL,wafv2:AssociateWebACL,wafv2:PutLoggingConfiguration) rather thanwafv2:*or theAWSWAFFullAccessmanaged policy.Ephemeral credentials. You MUST use IAM roles with temporary credentials (such as an EC2 instance profile, SSO session, or
aws sts assume-role) rather than long-lived IAM user access keys when running these WAF CLI commands.Monitor configuration changes. You SHOULD enable AWS CloudTrail on
wafv2management events and set CloudWatch alarms on critical web ACL configuration changes (such asDeleteWebACLandUpdateWebACLrule removals) and on the web ACL'sBlockedRequestsandCountedRequestsmetrics, so rule changes and sudden spikes in blocked or counted traffic are detected.Misconfiguration opens access. A web ACL that is created but never associated, or one whose default action is left at
Allowwith no enforcing rules, filters nothing. You MUST confirm the web ACL is associated and that its posture matches the intended default (block vs allow) before reporting setup complete.Protect log destinations. Logs can capture credentials and session data. You MUST redact sensitive fields (such as the
authorizationheader andcookie) and MUST enable encryption at rest on the log destination (CloudWatch Logs, Amazon S3, or Amazon Data Firehose).Header-spoofing risk. Any
x-amzn-waf-*signal forwarded to the origin can be forged inbound. You MUST add the inbound-header-stripping rule whenever a signal or client IP is forwarded (see stripping-inbound-waf-headers-before-trusting-them).
Additional Resources
Files
- ATTRIBUTION.mdAdded by AutoGineer917 B
- LICENSELicence file added by AutoGineer9.9 KiB
- NOTICELicence file added by AutoGineer67 B
- SKILL.md8.6 KiB
- references/adaptive-mitigation-playbook-for-forwarded-signals.md8.9 KiB
- references/adding-managed-rules-and-tuning-with-count-mode.md10.1 KiB
- references/adding-rate-based-rules.md10.5 KiB
- references/creating-a-web-acl-and-associating-it-with-a-resource.md9.3 KiB
- references/forwarding-signals-with-dynamic-label-interpolation.md9.5 KiB
- references/protecting-against-bots-with-bot-control.md9.9 KiB
- references/protecting-logins-and-signups-with-fraud-control.md9.2 KiB
- references/recovering-the-real-client-ip-behind-a-cdn.md9.4 KiB
- references/seeing-and-managing-ai-crawler-traffic.md7.3 KiB
- references/setting-up-logging-and-request-sampling.md9.2 KiB
- references/stripping-inbound-waf-headers-before-trusting-them.md7.5 KiB
- references/turning-bot-control-labels-into-a-confidence-signal.md11.0 KiB
- references/using-ip-sets-and-geographic-match-rules.md8.5 KiB
references/seeing-and-managing-ai-crawler-traffic.md
Seeing and Managing AI and LLM Crawler Traffic
Overview
Domain expertise for deciding, per AI scraper, whether to allow or block it in AWS WAF. Covers the AI activity visibility surface, the AI and large language model (LLM) bot labels Bot Control applies, category-based handling, and composing the AI labels into the existing bot confidence signal.
Does not cover turning Bot Control on (the protecting-against-bots reference) or the confidence signal chain in depth (its own references). This reference depends on Bot Control being enabled.
Execute commands using the AWS MCP server when connected (sandboxed execution, audit logging, observability). Fall back to the AWS CLI otherwise.
Table of Contents
Overview
Workflow
See the AI traffic first
Handle AI traffic by category
Compose into the confidence signal
Troubleshooting
Procedure
Security Considerations
Additional Resources
Workflow
To see and manage AI crawler traffic end to end, follow the procedure exactly. See the Procedure section below.
The procedure covers:
Using the AI activity surface to see which AI and LLM crawlers are arriving
Reading the AI and LLM bot labels
Handling that traffic by category (allow wanted crawlers, block or challenge unwanted ones)
Optionally composing the AI labels into the existing confidence signal
See the AI traffic first
Customers want to allow some AI crawlers and block others but cannot see the AI traffic, so they cannot make the decision.
Constraints:
You MUST surface the AI activity view and the AI and LLM bot labels so the customer can see which crawlers arrive before deciding on each
You SHOULD confirm Bot Control is enabled, since the AI labels come from it
Handle AI traffic by category
Customers treat all AI crawler traffic as one block-or-allow decision when they want different handling per crawler.
Constraints:
You MUST handle AI traffic by category using the bot labels, so the customer can allow wanted crawlers and block or challenge unwanted ones, rather than a single blanket decision
Compose into the confidence signal
A customer already forwarding a bot confidence signal can feed AI labels into the same chain rather than building a separate path.
Constraints:
You SHOULD compose the AI labels into the existing confidence signal (see turning-bot-control-labels-into-a-confidence-signal) rather than building a separate AI path
You MUST NOT duplicate the forwarding mechanism for AI traffic when a confidence signal already exists
Troubleshooting
The customer cannot see which AI crawlers are arriving
The AI activity surface or AI labels are not in view, or Bot Control is not enabled. Enable Bot Control and use the AI activity view (See the AI traffic first).
AI handling is all-or-nothing
The customer is making one blanket decision. Handle by category using the labels (Handle AI traffic by category).
Procedure
Overview
This procedure surfaces AI crawler traffic, handles it by category, optionally composes it into the confidence signal, and surfaces the console link.
Parameters
web_acl_name, web_acl_id, scope (required): Identify the web ACL.
category_handling (required): Which AI or LLM categories to allow, block, or challenge.
Constraints for parameter acquisition:
You MUST ask for all required parameters upfront in a single prompt
You MUST confirm Bot Control is enabled and producing AI labels
Steps
1. Verify dependencies
Constraints:
You MUST confirm credentials with
aws sts get-caller-identityYou MUST confirm Bot Control is enabled and AI labels are present
2. Review AI traffic and add category handling
Constraints:
You MUST review the AI activity and labels before deciding
You MUST add label-match rules handling the AI categories per the customer's decision, fetching the current
LockTokenbeforeupdate-web-acland passing the full rule setYou MUST preserve the web ACL's existing
DefaultActionfrom theget-web-aclresponse and pass it back as{default_action}; do not assumeAllow={}, since that would silently open all unmatched traffic on a web ACL whose default action isBlock. For example, a Block rule on an unwanted AI crawler label:aws wafv2 get-web-acl --name {web_acl_name} --scope {scope} --id {web_acl_id} --region {region} aws wafv2 update-web-acl --name {web_acl_name} --scope {scope} --id {web_acl_id} \ --lock-token {lock_token} --default-action {default_action} \ --rules '[{"Name":"BlockUnwantedAICrawler","Priority":1,"Action":{"Block":{}},"Statement":{"LabelMatchStatement":{"Scope":"LABEL","Key":"awswaf:managed:aws:bot-control:bot:category:ai"}},"VisibilityConfig":{"SampledRequestsEnabled":true,"CloudWatchMetricsEnabled":true,"MetricName":"BlockUnwantedAICrawler"}}]' \ --visibility-config SampledRequestsEnabled=true,CloudWatchMetricsEnabled=true,MetricName={web_acl_name} \ --region {region}
3. Optionally compose into the confidence signal and surface the console link
Constraints:
You SHOULD feed the AI labels into the existing confidence signal rather than a separate path
You MUST present the web ACL console link and tell the customer to confirm the AI handling rules:
https://us-east-1.console.aws.amazon.com/wafv2/homev2/web-acls?region={region}
Example
Example input
{
"web_acl_name": "example-webacl",
"web_acl_id": "abc",
"scope": "REGIONAL",
"category_handling": {"allow": ["wanted search AI"], "block": ["unwanted scraper AI"]}
}Example output
Reviewed AI crawler labels in the AI activity view.
Allowed the wanted crawler category, blocked the unwanted one, and fed the labels into the existing confidence signal.
Open the web ACL and confirm the AI handling rules:
https://us-east-1.console.aws.amazon.com/wafv2/homev2/web-acls?region=us-east-1Troubleshooting
Cannot see AI crawlers
Enable Bot Control and use the AI activity view (Step 1).
Handling is all-or-nothing
Add per-category label-match rules (Step 2).
Security Considerations
This procedure modifies a security control, so misconfiguration directly weakens the application's defenses.
Least-privilege IAM. You MUST grant only the specific
wafv2:actions a task needs (for examplewafv2:GetWebACLandwafv2:UpdateWebACL) rather thanwafv2:*or theAWSWAFFullAccessmanaged policy.Ephemeral credentials. You MUST use IAM roles with temporary credentials (such as an EC2 instance profile, SSO session, or
aws sts assume-role) rather than long-lived IAM user access keys when running these WAF CLI commands.Monitor configuration changes. You SHOULD enable AWS CloudTrail on
wafv2management events and set CloudWatch alarms on critical web ACL configuration changes (such asDeleteWebACLandUpdateWebACLrule removals) and on the web ACL'sBlockedRequestsandCountedRequestsmetrics, so rule changes and sudden spikes in blocked or counted traffic are detected.
Additional Resources
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs an MCP server
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- AWS
- Publisher
- AWS (Official)
- Source
- aws/agent-toolkit-for-aws · skills/specialized-skills/networking-and-content-delivery-skills/waf · commit 0a218f8
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- NOTICE (added by AutoGineer from NOTICE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by AWS.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download waf.zip