Good bots vs bad bots: Understanding helpful automation and harmful attacks

What are WAF policies and how do they protect web applications?

A WAF policy is a set of rules that defines how a Web Application Firewall inspects incoming web traffic and what actions to take (allow, block, challenge, or log) based on detected threats or patterns. Over 80% of web applications are vulnerable to at least one of the OWASP Top 10 security risks. These policies are crucial for protecting against common exploits, such as SQL injection, cross-site scripting (XSS), and cross-site request forgery (CSRF).WAF policies work by filtering HTTP/HTTPS traffic to and from web applications and APIs. They act as a reverse proxy between users and web servers. The firewall examines each request against configured rules to identify malicious behavior, such as known attack signatures or abnormal request sizes and frequencies.When properly configured, modern WAFs can reduce successful web attacks by up to 90%.WAF policy rules fall into three main categories that determine their security approach. Blocklist rules (negative security model) block known malicious traffic patterns. Allowlist rules (positive security model) only permit pre-approved traffic. Hybrid models combine both approaches to balance security and flexibility, giving you more control over how traffic is filtered.Creating a WAF policy involves selecting deployment options and configuring rule sets for your specific needs.You can deploy WAFs as network-based, host-based, or cloud-based solutions. Each option offers different benefits for traffic inspection and filtering. You'll need to define which rules to apply, set thresholds for anomaly detection, and determine response actions for different threat types.WAF adoption in enterprises increased by approximately 25% from 2023 to 2025. This reflects the growing importance of web application security. As web-based attacks continue to grow in volume and complexity, implementing effective WAF policies has become a core requirement for protecting business-critical applications and sensitive data.What is a WAF policy?A WAF policy is a set of rules that defines how a Web Application Firewall inspects incoming HTTP/HTTPS traffic and determines what actions to take, such as allowing, blocking, challenging, or logging requests based on detected threats or patterns. These policies analyze web requests against configured rules to identify malicious behavior, such as SQL injection, cross-site scripting (XSS), or abnormal request patterns. They then enforce security actions to protect your applications. Modern WAF policies employ three primary approaches: blocklist rules that deny known malicious traffic, allowlist rules that permit only pre-approved traffic, or hybrid models that combine both methods for balanced protection.How does a WAF policy work?A WAF policy works by defining a set of rules that analyze incoming HTTP/HTTPS requests and determine whether to allow, block, challenge, or log each request based on detected threat patterns. When traffic reaches the WAF, it inspects request elements, such as headers, query strings, request bodies, and HTTP methods, against configured rules. The policy compares this data to known attack signatures and behavioral patterns to identify threats, such as SQL injection, cross-site scripting (XSS), and cross-site request forgery (CSRF).WAF policies work through three main rule types.Blocklist rules (negative security model) deny traffic matching known malicious patterns, such as specific SQL injection strings or suspicious user agents. Allowlist rules (positive security model) only permit pre-approved traffic that meets exact criteria, blocking all other traffic by default. Hybrid models combine both approaches. They use allowlists for critical application paths while applying blocklists to detect new threats.The WAF typically sits as a reverse proxy between users and your web servers, inspecting every request before it reaches the application.When a request matches a rule, the policy executes the defined action immediately. Modern WAFs can process these checks in milliseconds, analyzing multiple rule sets simultaneously without noticeable latency. You can customize policies by adding exceptions for legitimate traffic that triggers false positives, adjusting sensitivity levels, and creating custom rules specific to your application's security needs.What are the main types of WAF policy rules?WAF policy rules define how a Web Application Firewall inspects, filters, and responds to incoming web traffic based on your security requirements. Here are the main types you'll encounter.Blocklist rules: These follow a negative security model by identifying and blocking known malicious traffic patterns. The WAF maintains a database of harmful requests (like SQL injection attempts or cross-site scripting payloads) and denies any traffic matching these patterns.Allowlist rules: These implement a positive security model that only permits pre-approved, legitimate traffic to reach your web application. All requests must match specific criteria such as approved IP addresses, user agents, or request formats. The WAF blocks everything else by default.Hybrid rules: These combine both blocklist and allowlist approaches to balance security and usability. You can block known threats while allowing verified legitimate traffic, providing flexible protection that adapts to different application needs.Rate limiting rules: These monitor and control the frequency of requests from specific sources to prevent abuse and denial-of-service attacks. The WAF tracks request rates per IP address or user session and blocks or throttles traffic exceeding your defined thresholds.Geolocation rules: These filter traffic based on the geographic origin of requests. You can block or allow access from specific countries or regions, which helps prevent attacks from known malicious locations while maintaining access for legitimate users.Custom signature rules: These define organization-specific patterns and conditions tailored to protect unique application vulnerabilities or business logic. Security teams create custom detection patterns that address threats specific to their web applications, going beyond standard managed rules.Behavioral analysis rules: These examine traffic patterns and user behavior over time to detect anomalies that might indicate attacks or unauthorized access. The WAF establishes a baseline behavior and flags deviations, such as unusual request sequences or abnormal data access patterns.How to create a WAF policyYou create a WAF policy by defining security rules that determine how your WAF inspects incoming web traffic and responds to potential threats.Assess your web application's architecture. Identify the components that require protection, including APIs, login pages, payment forms, and data submission endpoints. Document the HTTP methods your application uses (GET, POST, PUT, DELETE) and any custom headers or parameters.Select your base ruleset. Choose between three security models: blocklist rules that deny known malicious patterns, such as SQL injection signatures; allowlist rules that permit only pre-approved traffic sources and patterns; or a hybrid approach combining both. Most organizations begin with managed rule sets covering OWASP Top 10 vulnerabilities.Configure rule actions for different threat levels. Set responses like block (reject the request), allow (permit the traffic), challenge (require CAPTCHA verification), or log (record for analysis without blocking). Assign stricter actions to high-risk endpoints such as admin panels.Add custom rules tailored to your application. Examples include rate limiting to prevent brute force attacks (limit login attempts to 5 per minute per IP), geographic restrictions to block traffic from regions you don't serve, or pattern matching for application-specific attack vectors.Define exclusions for legitimate traffic. Some valid requests might trigger false positives. Allow large file uploads for authenticated users or permit specific API clients to bypass certain inspection rules. Test these exclusions carefully to avoid creating security gaps.Configure logging and monitoring settings. Capture blocked requests, suspicious patterns, and policy violations. Set alert thresholds for unusual traffic spikes or attack patterns that exceed normal baselines by 200% or more.Test your WAF policy in detection-only mode. Run it for 7 to 14 days before enabling blocking actions. Review logs daily during this period to identify false positives and adjust rules to strike a balance between security and application availability.Start with managed rulesets and add custom rules gradually. Base your configuration on your application's traffic patterns and security requirements rather than trying to configure everything at once.How to configure WAF policy protectionsYou configure WAF policy protections by defining security rules that analyze incoming web traffic, setting appropriate actions for detected threats, and tailoring protections to match your application's specific security needs.First, access your WAF management interface and create a new policy by specifying its name, scope, and enforcement mode (detection only or prevention). Start in detection mode to monitor traffic patterns for 7-14 days without blocking requests. This helps identify legitimate traffic and reduces the number of false positives.Next, enable managed rule sets that provide pre-configured protections against common web attacks, such as SQL injection, cross-site scripting (XSS), and remote file inclusion. Security experts maintain and update these rules regularly to address new threats, automatically covering most OWASP Top 10 vulnerabilities.Then, configure your security model by choosing between blocklist rules that deny known malicious patterns, allowlist rules that permit only approved traffic sources, or a hybrid approach combining both methods. Blocklist works well for public-facing sites. Allowlist suits applications with predictable user behavior.After that, set specific rule actions for different threat levels: block high-severity attacks immediately, challenge medium-severity requests with CAPTCHA verification, and log low-severity events for review. This tiered approach strikes a balance between security and user experience, preventing legitimate users from being blocked unnecessarily.Create custom rules to address application-specific vulnerabilities or business logic requirements that managed rules don't cover. For example, you might block requests exceeding certain parameter lengths, restrict access to admin endpoints by IP address, or enforce rate limits on API calls.Configure rule exclusions for legitimate traffic that triggers false positives, such as rich text editors that submit HTML content or file upload features that send large POST requests. Document each exclusion with a clear business justification to maintain security visibility and transparency.Finally, enable logging and monitoring to track blocked requests, review security events, and analyze attack patterns. Set up alerts for unusual activity spikes or repeated attack attempts from specific sources so your team can respond quickly.Test your WAF policy in staging environments with realistic traffic before applying it to production. Review security logs weekly during the first month to fine-tune rules and reduce false positives.What are WAF policy best practices?WAF policy best practices refer to the recommended methods and strategies for configuring and managing Web Application Firewall rules to maximize security effectiveness while minimizing operational disruption. Here are the key WAF policy best practices.Start with managed rules: Managed rule sets provide pre-configured protections against OWASP Top 10 vulnerabilities and common attack patterns. You don't need deep security expertise to use them. These rules receive regular updates from security vendors to address emerging threats. Most organizations can block 70-80% of attacks using managed rules alone.Implement logging before blocking: Deploy new WAF rules in detection or log-only mode first. This lets you monitor their impact on legitimate traffic before enforcing blocks. You'll identify false positives and fine-tune rules without disrupting user access. After 7-14 days of monitoring, you can switch to blocking mode with confidence.Create custom rules for your application: Build application-specific rules that address unique security requirements and business logic vulnerabilities that generic rules can't protect. Custom rules can target specific URL paths, API endpoints, or user behaviors unique to your application. These tailored protections often catch threats that managed rules miss.Use rate limiting strategically: Configure rate limits on login pages, API endpoints, and resource-intensive operations to prevent brute force attacks and DDoS attempts. Set thresholds based on normal traffic patterns, such as 100 requests per minute per IP address. Rate limiting protects application availability without blocking legitimate users.Tune rules to reduce false positives: Regularly review blocked requests to identify legitimate traffic incorrectly flagged as malicious, then adjust rules or add exceptions. High false positive rates create security team fatigue and may lead to turning off important protections. Aim to keep false positive rates below 5% through continuous tuning.Apply the principle of least privilege: Configure allowlist rules for known good traffic sources and user agents when possible, blocking all other traffic by default. This positive security model provides stronger protection than blocklist approaches for high-security applications. It's particularly effective for internal applications with predictable access patterns.Monitor and update policies regularly: Review WAF logs weekly to identify attack trends, rule effectiveness, and potential policy gaps. Update rules monthly or when new vulnerabilities emerge in your application stack. Regular maintenance ensures that protections remain aligned with evolving threats and changes to applications.How to troubleshoot common WAF policy issuesTroubleshoot common WAF policy issues by checking rule configurations, analyzing traffic logs, adjusting sensitivity settings, and testing policies in monitor mode before enforcing blocks.Start by reviewing your WAF logs to identify false positives or blocked legitimate traffic. Look for patterns in blocked requests, like specific IP addresses, user agents, or request paths that shouldn't trigger blocks. Most false positives happen when legitimate requests match overly strict rule patterns.Verify that your WAF rules do not conflict with your application's normal behavior. Test API calls, form submissions, and file uploads in a staging environment to identify which rules are triggered incorrectly. Common issues include blocking legitimate POST requests with large payloads or flagging standard authentication headers.Adjust rule sensitivity by creating custom exclusions for specific application paths or parameters. If a rule blocks legitimate traffic to /api/upload, add an exclusion for that endpoint while keeping protection active elsewhere. This maintains security without disrupting functionality.Verify that your allowlist and blocklist rules don't contradict each other. A common mistake is having an allowlist rule that permits traffic, while a blocklist rule blocks, creating unpredictable behavior. Review rule priority and execution order to ensure the most specific rules process first.Test policy changes in monitor mode before switching to block mode. Monitor mode logs potential threats without blocking them, letting you validate that new rules won't disrupt legitimate traffic. Run monitor mode for 24 to 48 hours to capture typical traffic patterns across different time zones.Check if geographic restrictions or rate-limiting rules are too aggressive. If users from specific regions report access issues, verify your geo-blocking rules. If legitimate users hit rate limits, increase thresholds, or implement more granular rate limiting per endpoint rather than globally.Review managed rule sets for recent updates that might affect your application. WAF providers regularly update managed rules to address new threats, but these updates can sometimes flag previously allowed traffic. Roll back recent rule changes if issues started after an update.Keep detailed documentation of all policy changes and their effects. This speeds up future troubleshooting and helps your team understand why specific exclusions are in place.What are the differences between WAF policy deployment options?Organizations can implement Web Application Firewall solutions in several distinct ways, each with its own unique hosting and deployment characteristics. Here are the main WAF policy deployment options.Network-based WAF: Hardware appliances installed on-premises within your data center or network perimeter. The appliance sits between external users and web servers as a reverse proxy, inspecting all HTTP/HTTPS traffic before it reaches your applications. This option delivers low latency and high performance. However, it requires significant upfront capital investment and ongoing maintenance.Host-based WAF: WAF software installed directly on the web server or application server hosting your protected application. The WAF runs as a module or service on the same machine, inspecting traffic at the application layer without separate hardware. This approach offers deep integration with your application, but it consumes server resources and requires individual configuration for each host.Cloud-based WAF: WAF protection delivered as a service through cloud infrastructure, with traffic routing through the provider's edge network before reaching your origin servers. You'll configure policies through a web interface, eliminating the need to manage physical or virtual appliances. Cloud-based WAFs offer rapid deployment, automatic updates, and elastic scaling. The tradeoff is that all traffic routes through external infrastructure.Hybrid deployment: This approach combines multiple deployment models. For example, you might use cloud-based WAF for public-facing applications while maintaining network-based appliances for internal or legacy systems. Organizations can balance performance, security, and cost requirements across different application environments. Hybrid models provide flexibility but increase management complexity across multiple platforms.API-integrated WAF: WAF protection connected through API gateways or service mesh architectures in microservices environments. The WAF inspects API calls and responses at the gateway layer, applying policies specific to REST, GraphQL, or SOAP protocols. This deployment works well for modern application architectures but requires careful configuration to avoid breaking legitimate API functionality.Container-based WAF: WAF protection deployed as containerized workloads within Kubernetes or similar orchestration platforms. The WAF runs as a sidecar container alongside application containers, inspecting traffic within the cluster. Container-based deployments offer portability and integration with DevOps workflows. You'll need container expertise and proper resource allocation to implement this option effectively.Frequently asked questionsWhat's the difference between a WAF policy and a security policy?A WAF policy defines the complete ruleset that governs how a Web Application Firewall inspects and responds to web traffic. A security policy is broader. It's an organizational framework that covers all security controls and procedures.WAF policies contain specific technical rules (blocklist, allowlist, or hybrid) that detect attack patterns, such as SQL injection or XSS. Security policies work differently. They document high-level requirements, compliance standards, and access controls across your entire infrastructure.How many rules should a WAF policy contain?There's no fixed number of WAF policy rules. The right amount depends on the complexity of your application, its traffic patterns, and your security needs.Most organizations begin with 10-20 managed rules that cover OWASP Top 10 threats, then add 5-15 custom rules for application-specific protections.Can I use multiple WAF policies simultaneously?No, you can't apply multiple WAF policies to a single web application or endpoint at once. Each resource accepts only one active policy at a time.However, you can build a single comprehensive policy that combines multiple rule sets, managed rules, and custom rules. This approach provides layered protection without requiring multiple policies.What happens when a WAF policy blocks legitimate traffic?When a WAF policy blocks legitimate traffic (known as a false positive), users are unable to access your web application or specific features. This means your security team needs to step in and adjust the rules.To address false positives, you typically create exceptions or adjust sensitivity thresholds. Most organizations maintain detailed logs to spot these issues quickly. You can then refine your WAF policies through allowlist rules or custom exclusions that permit known safe traffic patterns.How often should I update my WAF policy?Review your WAF policy at least once a month to ensure it remains effective. Update it immediately when new vulnerabilities emerge, your application changes, or you notice shifting attack patterns. Audit rule effectiveness every quarter and adjust false positive thresholds based on traffic analysis. This keeps your protection strong without blocking legitimate users.Does a WAF policy impact website performance?Yes, a WAF policy typically adds minimal latency, ranging from 1 to 5 milliseconds per request. This overhead is negligible compared to the security benefits it provides.What's the difference between detection mode and prevention mode?Detection mode monitors and logs suspicious traffic without blocking it. Prevention mode actively blocks threats in real-time.We recommend using detection mode when you're testing WAF rules before enforcement. This approach helps you avoid accidentally disrupting legitimate traffic while you fine-tune your security configuration.

What is an HTTP flood attack?

An HTTP flood attack is a type of Distributed Denial of Service (DDoS) attack that overwhelms a web server or application with a massive volume of seemingly legitimate HTTP requests, rendering it unresponsive to real users. Layer 7 (application layer) DDoS attacks, including HTTP floods, accounted for over 40% of all DDoS attacks in 2024.HTTP flood attacks work at the application layer (Layer 7 of the OSI model). This makes them harder to detect than lower-layer DDoS attacks. Attackers typically use botnets (networks of compromised devices) to generate the massive volume of requests needed for an effective HTTP flood.Botnet-powered HTTP flood attacks can generate over 1 million requests per second. That's enough to overwhelm even strong cloud infrastructure without proper mitigation.Recognizing an HTTP flood attack early is critical for minimizing damage. Signs include sudden spikes in traffic from unusual sources, degraded application performance, and server resource exhaustion despite normal network bandwidth. These indicators help security teams distinguish between legitimate traffic surges and coordinated attacks.HTTP flood attacks come in two main types: GET floods and POST floods.GET floods request data from the server. POST floods send data to the server, which is often more resource-intensive and more challenging to filter. Both types exploit the stateless nature of the HTTP protocol, enabling attackers to easily forge and amplify requests.The average cost of a DDoS attack to a business in 2024 was estimated at $120,000 per incident, with application-layer attacks, such as HTTP floods, contributing significantly to downtime and recovery costs. Understanding how these attacks work and how to defend against them is essential for protecting web infrastructure and maintaining service availability.What is an HTTP flood attack?An HTTP flood attack is a type of Distributed Denial of Service (DoS) attack that overwhelms a web server or application with massive volumes of seemingly legitimate HTTP requests, making it unresponsive to real users. Attackers operate at the application layer (Layer 7 of the OSI model), making these attacks more complex and more challenging to detect than lower-layer DDoS attacks. They typically use botnets (networks of compromised devices) to generate the millions of requests necessary to exhaust server resources, such as CPU, memory, and bandwidth.The attack exploits the stateless nature of the HTTP protocol.Each request forces the server to allocate resources for processing, even if the request is malicious. HTTP flood attacks utilize standard, valid HTTP requests that mimic normal user behavior, making them difficult to distinguish from legitimate traffic. This makes detection and mitigation particularly challenging compared to other types of DDoS attacks.HTTP floods come in two main variants.GET floods repeatedly request data from the server, often targeting resource-intensive pages or large files. POST floods send data to the server, which is typically more resource-intensive because the server must process and store the incoming data before responding. Both methods can bring down even robust cloud infrastructure without proper protection in place.How does an HTTP flood attack work?An HTTP flood attack works by overwhelming a web server or application with a massive volume of seemingly legitimate HTTP requests, until it is unable to respond to real users. Attackers typically deploy botnets (networks of compromised devices) to generate millions of requests simultaneously, targeting the application layer (Layer 7) where web services process user interactions. The attack exploits how web servers must allocate resources to handle each incoming request, even if it's malicious.These attacks use two primary methods: GET floods and POST floods.GET floods repeatedly request data from the server, like loading a homepage thousands of times per second. POST floods send data to the server, which is more resource-intensive because the server must process incoming information. Think of repeatedly submitting forms or uploading files. Both methods use standard, valid HTTP protocol, so they're difficult to distinguish from regular traffic.The stateless nature of HTTP makes these attacks particularly effective. Each request appears independent and legitimate. This forces the server to process it fully before determining if it's malicious. Attackers often rotate IP addresses, spoof headers, and mimic real user behavior patterns to avoid detection. When the server's resources (CPU, memory, or bandwidth) reach capacity, it slows down or crashes completely, blocking access for legitimate users.What are the signs of an HTTP flood attack?Signs of an HTTP flood attack refer to the observable indicators that a web server or application is being targeted by a flood of malicious HTTP requests designed to exhaust resources and deny service to legitimate users. The signs of an HTTP flood attack are listed below.Sudden traffic spike: Server logs indicate an abrupt increase in HTTP requests that doesn't align with standard usage patterns or expected traffic growth. This spike often occurs without corresponding increases in legitimate user activity or marketing campaigns.Slow server response: Web pages load significantly slower than usual, or the server becomes completely unresponsive as resources get consumed by processing malicious requests. Response times can jump from milliseconds to several seconds or result in timeouts.Single URL patterns: Attack traffic concentrates on specific endpoints, particularly resource-intensive pages such as search functions, login pages, or database queries. Attackers target these URLs because they require more server processing power than static content.Geographic anomalies: Traffic originates from unusual locations or countries where you typically do not have users. You'll see requests flooding in from regions you've never served before, indicating botnet activity.Unusual user agents: Server logs reveal suspicious or repetitive user agent strings that don't match legitimate browsers or devices. Attackers often use automated tools that leave distinctive fingerprints in request headers.Failed authentication attempts: Login pages experience a surge in failed authentication requests as attackers send POST requests with random credentials. This variant specifically targets authentication systems to consume processing resources.Identical request patterns: Multiple requests arrive with nearly identical characteristics (same headers, same parameters, same timing intervals), suggesting automated bot activity rather than human users. Legitimate traffic shows natural variation in request patterns.What are the main types of HTTP flood attacks?The main types of HTTP flood attacks refer to the different methods attackers use to overwhelm web servers with malicious HTTP requests at the application layer. The main types of HTTP flood attacks are listed below.HTTP GET flood: Attackers send massive volumes of GET requests to retrieve web pages, images, or files from the target server. This exhausts server resources by forcing it to process and respond to thousands or millions of seemingly legitimate requests. GET floods often target resource-heavy pages or large files to amplify the impact.HTTP POST flood: This attack sends numerous POST requests that submit data to the server, such as form submissions or file uploads. POST floods are more resource-intensive than GET attacks because the server must process the incoming data, not just retrieve content. Attackers can overwhelm database connections and backend processing systems with relatively fewer requests.HTTP HEAD flood: Attackers request only the HTTP headers of a web page without downloading the full content. These requests appear lightweight, but they still require the server to process each request and generate a response. This method can be harder to detect because it generates less network traffic than GET or POST floods.Slowloris attack: This technique maintains multiple connections to the target server by sending partial HTTP requests over time, gradually opening them. The server waits for each request to complete, tying up connection slots until no new legitimate users can connect. A single machine can take down a server without using much bandwidth.Slow POST attack: Similar to Slowloris attacks, this method sends POST requests with a declared large content length but transmits the data extremely slowly. The server keeps the connection open, waiting for the complete data, which can exhaust available connections. This attack is particularly effective against servers with limited connection pools.Cache-busting attack: Attackers add random query strings or parameters to URLs in their requests to bypass caching mechanisms. Each request appears unique to the server, forcing it to generate fresh responses instead of serving cached content. This puts maximum strain on origin servers and databases.WordPress XML-RPC flood: This targets the XML-RPC interface in WordPress sites by sending authentication requests or pingback commands. A single XML-RPC request can trigger multiple internal operations, making it an efficient way to exhaust server resources. Many WordPress sites leave this interface exposed and unprotected.How do HTTP flood attacks impact businesses?HTTP flood attacks overwhelm web servers and applications with massive volumes of seemingly legitimate HTTP requests. These application-layer attacks exhaust critical server resources (CPU, memory, and bandwidth), making websites and online services unavailable to real customers. The result? Service outages, revenue loss, and reputational damage.The financial toll is substantial. Organizations face direct costs from lost sales during downtime. E-commerce platforms suffer most during peak shopping periods.For example, a major European e-commerce site lost millions in revenue during a multi-hour outage caused by an HTTP POST flood targeting its checkout API during a critical sales event. Service disruptions also trigger indirect costs: emergency response teams, forensic analysis, infrastructure upgrades, and potential regulatory fines for service level agreement violations.Operational impacts extend beyond immediate downtime. IT teams must divert resources from planned projects to incident response and recovery.Customer support departments face increased ticket volumes from frustrated users who are unable to access services. For businesses relying on online transactions (such as banking, retail, and travel booking), even brief outages can create cascading effects that persist long after the attack ends.Brand reputation suffers when customers can't access your services. Repeated attacks erode customer trust and drive users to competitors.Media coverage of successful attacks can amplify the damage, particularly for organizations that handle sensitive data or critical services. Recovery requires more than technical fixes. You'll need to invest significant time and resources in customer communication and trust rebuilding efforts.How to detect HTTP flood attacksYou detect HTTP flood attacks by monitoring traffic patterns for anomalies that distinguish malicious requests from legitimate user behavior.First, establish baseline metrics for normal traffic patterns on your web servers and applications. Track typical request rates, geographic distribution of users, session durations, and resource consumption during peak and off-peak hours. This creates your reference point for comparison.Next, monitor sudden spikes in HTTP request volume that exceed your baseline by 200-300% or more. Pay special attention to rapid increases from specific IP addresses, geographic regions, or user agents that deviate from your normal traffic profile.Then, analyze request patterns for repetitive behavior that legitimate users wouldn't exhibit. Look for identical GET requests to the same URLs repeated hundreds of times per minute, or POST requests with similar payloads hitting resource-intensive endpoints, such as search functions or checkout pages.Check for suspicious client characteristics in your access logs. These include outdated or mismatched user agents, missing referrer headers, or requests from known proxy services and data centers. Legitimate users typically show consistent browser fingerprints and natural navigation patterns.Monitor server resource consumption for unusual strain on CPU, memory, and database connections. HTTP floods often result in disproportionate resource usage compared to the request volume, especially when targeting complex queries or API endpoints.Examine session behavior for anomalies like missing cookies, rapid-fire requests without normal page load sequences, or connections that skip JavaScript rendering. Bots often can't execute client-side code that legitimate browsers handle automatically.Finally, track changes in geographic distribution of your traffic sources. A sudden influx of requests from regions where you have few legitimate users, or from multiple countries simultaneously, often indicates a botnet-powered attack. Set up automated alerts that trigger when multiple indicators appear together. Single anomalies might be false positives, but combined signals typically confirm an attack in progress.How to prevent HTTP flood attacksYou prevent HTTP flood attacks by combining rate limiting, traffic analysis, and multi-layered security controls to identify and block malicious requests before they overwhelm your servers.Rate limiting: Deploy rate limiting at both the network edge and application level to cap the number of requests each IP address or user session can make within a set timeframe. Set thresholds based on your normal traffic patterns. For example, limit individual IP addresses to 100 requests per minute for standard web pages and 20 requests per minute for resource-intensive endpoints, such as search or checkout.Behavioral analysis: Set up tools that establish baseline traffic patterns and flag anomalies in real-time. Monitor for suspicious indicators, such as identical request patterns from multiple IPs, unusually high request rates from specific geographic regions, or requests that bypass normal user navigation flows.CAPTCHA challenges: Configure CAPTCHA or JavaScript verification for suspicious traffic sources to distinguish human users from bots. Trigger them selectively based on abnormal request behavior, rather than for every visitor.IP reputation filtering: Maintain blocklists of known malicious sources and automatically drop traffic from them at your network perimeter. Combine threat intelligence feeds with historical attack data, and use automatic expiration rules (30–90 days) to avoid blocking legitimate users.Connection limits and timeouts: Set maximum concurrent connections per IP (typically 10–50), reduce timeout values for idle connections to 5–10 seconds, and drop incomplete requests that exceed reasonable timeframes.Web application firewall (WAF): Use a WAAP service or cloud-based DDoS protection service like Gcore to filter malicious traffic before it reaches your servers. WAFs can absorb attacks and detect patterns that manual rules might miss.Regular testing: Conduct controlled load testing simulating attacks and maintain an incident response plan with clear procedures and thresholds.How to mitigate an active HTTP flood attackYou mitigate an active HTTP flood attack by implementing rate limiting, deploying traffic filtering, and activating cloud-based DDoS protection to block malicious requests while preserving legitimate user access.Rate limiting: Enable rate limiting on your web server or load balancer to restrict requests from individual IP addresses. For example, 100 per minute per IP for standard pages, or 20 per minute for resource-intensive endpoints.Web application firewall: Activate your WAF to filter suspicious patterns, such as unusual user-agent strings, missing headers, or repetitive request behavior indicative of bots.CAPTCHA challenges: Apply CAPTCHAs on critical pages like login forms or checkout processes to stop automated attack tools while maintaining minimal friction for legitimate users.Geographic filtering: Block or limit traffic from regions where you don't serve customers. Monitor carefully to avoid affecting legitimate international users.Cloud-based DDoS protection: Deploy services that absorb and filter attack traffic before it reaches your origin servers. These can handle millions of requests per second and detect HTTP flood patterns automatically. For example, use Gcore's DDoS protection services.Real-time log analysis: Track attack signatures such as repeated requests to specific URLs or abnormal spikes from particular IP ranges. Use this data to create targeted blocking rules.Connection limiting: Restrict the number of simultaneous connections per IP at the load balancer to prevent attackers from exhausting resources while maintaining legitimate sessions.Continuous monitoring: Adjust thresholds during the attack as attackers change tactics, ensuring mitigation measures remain effective.What are the best practices for HTTP flood protection?Best practices for HTTP flood protection refer to the proven methods and strategies organizations use to defend their web servers and applications against volumetric HTTP-based attacks. The best practices for HTTP flood protection are listed below.Rate limiting: Configure rate limits to restrict the number of requests a single IP address or user can make within a specific timeframe. Set different thresholds for authenticated versus anonymous users to balance security with user experience.Traffic analysis: Monitor incoming HTTP requests for unusual patterns, such as repeated requests for the same resource, abnormal request frequencies, or suspicious user agent strings. Real-time analysis helps identify attacks before they cause significant damage.CAPTCHA challenges: Deploy CAPTCHA or JavaScript challenges when suspicious activity is detected to verify that requests come from real users rather than bots. Apply these selectively to avoid frustrating legitimate visitors.IP reputation filtering: Block or challenge requests from IPs with poor reputations or known associations with botnets and malicious activity. Maintain updated blocklists and use threat intelligence feeds to identify risky sources.Web application firewall: Install a WAF to inspect HTTP traffic at the application layer and filter malicious requests based on rules and behavioral patterns. WAFs distinguish between legitimate and malicious POST requests by analyzing payload content and request structure.Connection limits: Set maximum concurrent connection limits per IP address to prevent single sources from monopolizing server resources. Configure these limits based on typical user behavior patterns.Geographic filtering: Block traffic from regions where you don't conduct business or where attacks commonly originate. Combine with allowlisting for known legitimate international users.Caching strategies: Implement aggressive caching for static and semi-static content to reduce the load on origin servers during an attack. Cached content can be served from edge locations, reducing backend strain.Frequently asked questionsWhat's the difference between HTTP flood attacks and other DDoS attacks?HTTP flood attacks target the application layer (Layer 7) using valid HTTP requests to exhaust server resources. Most other DDoS attacks operate at lower network layers (3–4), overwhelming bandwidth with malformed packets or connection floods. HTTP floods are harder to detect because the traffic looks legitimate, while volumetric attacks generate obvious traffic spikes.How much does HTTP flood protection cost?Costs range from free basic mitigation to over $5,000 per month for enterprise solutions, depending on traffic volume, attack complexity, and response speed. Most cloud-based DDoS services use bandwidth-based pricing. Small to mid-sized businesses typically pay $200–$2,000 per month for baseline protection, plus overage fees when actively under attack.Can HTTP flood attacks bypass CDN protection?No, HTTP flood attacks can't entirely bypass CDN protection, but they can strain it if the CDN lacks advanced Layer 7 filtering, rate limiting, and bot detection. Modern CDNs combine edge-based request analysis, behavioral monitoring, and distributed traffic absorption to block malicious requests before they reach origin servers. Sophisticated distributed botnet attacks may still cause problems, so advanced machine learning and threat intelligence are recommended.What's the difference between HTTP GET and POST flood attacks?GET requests data from the server, such as loading pages or images. POST requests send data to the server, such as form submissions. POST attacks typically consume more server resources per request. GET floods are simpler to execute but easier to cache. POST floods target dynamic processing and are harder to mitigate.How long do HTTP flood attacks typically last?HTTP flood attacks usually last from a few minutes to several hours. More sophisticated campaigns can persist for days with intermittent bursts. Duration depends on the attacker's resources, motivation, and the speed of detection and mitigation.Are small websites vulnerable to HTTP flood attacks?Yes, small websites are vulnerable. Attackers often target them because they have fewer resources and weaker defenses than enterprise sites. Small sites can't absorb high-volume request floods as easily, making them quicker to overwhelm and cheaper targets for botnet testing.What is the difference between HTTP flood and SYN flood attacks?HTTP flood attacks target the application layer (Layer 7) using valid HTTP requests. SYN flood attacks target the transport layer (Layers 3–4) by overwhelming TCP connection resources. HTTP floods mimic legitimate traffic, making them harder to detect than SYN floods, which often show abnormal connection patterns.

Good bots vs Bad Bots

What is a bot?

What are good bots?

What are bad bots?

What are the main differences between good bots and bad bots?

What are the types of bad bot attacks?

How can you detect bot traffic?

How to protect your website from bad bots

What are the best bot management solutions?

Frequently asked questions

How can you tell if a bot is good or bad?

Do good bots ever cause problems for websites?

What happens if you block good bots accidentally?

Can bad bots bypass CAPTCHA verification?

How much internet traffic is from bad bots?

What is the difference between bot management and WAF?

Are all web scrapers considered bad bots?

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