Home
Developers
How to manage good bots? Difference between good bots and bad bots

How to manage good bots? Difference between good bots and bad bots

By Gcore

February 9, 2023

12 min read

How to manage good bots? Difference between good bots and bad bots

A bot, short for “robot,” is a type of software program that can automatically perform tasks quickly and efficiently. These tasks can range from simple things like getting weather updates and news alerts to more complex ones like data entry and analysis. While bots can be beneficial in our daily lives, they are also associated with malicious activities we’re all too familiar with, such as DDoS attacks and credit card fraud.

In this post, we’ll dive deep into the topic and explore the difference between good bots and bad bots. You’ll learn about bot management, including best practices and available tools to identify and implement them. By the time you finish reading, you’ll have a good grasp on how to properly manage bots on your website or application—and how to keep any bad bots from getting through the door.

What is a good bot?

Good bots, also known as helpful or valuable bots, are software programs that are designed to perform specific tasks that benefit the user or the organization. They are built to improve the user experience on the internet.

For instance, good bots crawl through websites, examining the content to ensure it is safe. Search engines like Google use these crawlers to check web pages and improve search results. Also, good bots can be found performing various tasks such as gathering and organizing information, conducting analytics, sending reminders, and providing basic customer service.

Now that you’re familiar with what a good bot is, let’s take a look at some specific instances of their use “in the wild.”

The following are examples of good bots:

Search engine crawlers. Googlebots and Bingbots are web crawlers that help the search engines Google and Bing, respectively, index and rank web pages. These types of bots comb through the entire internet to find the best content that can enhance search engine results.
Site monitoring bot. This type of bot is used to continuously monitor a website or web application for availability, performance, and functionality. It helps detect (and alert us about) issues that could affect the user experience, such as slow page load times, broken links, or server errors. Some examples of these are Uptime Robot, StatusCake, and Pingdom.
Social media crawlers. Social networking sites use bots like these to make better content recommendations as well as battle spam and fake accounts, all with the intent of presenting an optimal and safe online environment for the site’s users. Examples of such bots are the Facebook crawler and Pinterest crawler.
Chatbot. Facebook’s Messenger and Google Assistant are bots that can automate repetitive tasks like responding to chat messages. They mimic human conversation by replying to specific prompts with predetermined answers. Another example, OpenAI’s ChatGPT, serves as a highly advanced chatbot, utilizing AI/ML technology to simulate human conversation and provide automated responses to individual queries. This can save time and resources for organizations of all sizes, whether it’s a big company, a small business, or even an individual user.
Voice bot. Also referred to as voice-enabled chatbots, these run on AI-powered software that can accept voice commands and respond with voice output. They provide users with a more efficient means of communication when compared to text-based chatbots. Well-known examples of voice bots include Apple’s Siri, Amazon’s Alexa, and the above-mentioned Google Assistant.
Aggregator bot. Like the name implies, this bot vacuums up web data, gathering information on a wide range of topics—weather updates, stock prices, news headlines, etc. It brings all of this information together and presents it in one convenient location. Google News and Feedly are examples of aggregator bots in action.

There are many other fields where good bots are in use—in fintech (making split-second decisions in the stock market), in video games (as automated players), in healthcare (assisting with research tasks and test analysis), and numerous other applications.

We’ve covered the basics of what good bots are and how they are employed for our benefit—now it’s time to start talking about the bad ones.

What is a bad bot?

Bad bots are a type of software application that is created with the intention of causing harm. They are programmed to perform automated tasks such as scraping website content, spamming, hacking, and committing fraud. Unlike good bots that assist users, bad bots have the opposite effect: spreading disinformation, crashing websites, infiltrating social media sites, using fake accounts to spam malicious content, etc.

Imagine the impact on specific individuals or organizations once bad bots target them. The result can be financial loss, reputational damage, even legal issues if sensitive information is stolen or shared—or all of the above. It can also lead to identity theft or other types of cybercrime. The consequences can be severe, and individuals and industries must take necessary precautions to protect themselves from bad bots.

Read on to familiarize yourself with instances of bad bots and how they operate.

Examples of bad bots are the following:

Web content scraper. Initially, there are some positives in using web content scrapers (for ethical purposes), but mostly it’s being used with bad intentions. The intent is to crawl websites and collect confidential data, such as personal details and financial information, which can be used for identity theft, financial fraud and/or data breaches. For instance, a cybercriminal may target an e-commerce website with a scraper designed to extract sensitive information, resulting in financial losses for both individuals and businesses.
Spammer bot. Bots utilized to send spam messages or post spam comments on websites and social media platforms. As per SpamLaws, spam is responsible for 14.5 billion messages globally per day, representing 45% of all emails generated—and the bots are responsible for a significant part of it.
DDoS bot. These bots are used to launch DDoS attacks against websites by overwhelming them with traffic, making those sites unavailable to legitimate users. Cybercriminals are taking advantage of these bad bots, resulting in DDoS attacks that have become more complex than ever before.
Click fraud bot. A bot created specifically to artificially inflate advertising platform revenue by clicking on links or ads. Bad bots generate these fake page views and clicks, distorting the real metrics of ad performance, which in turn defrauds advertisers. According to Statista, digital advertising fraud costs are predicted to rise from $35 billion to $100 billion between 2018 and 2023, potentially causing significant losses for online publishers.

Account takeover bot. This type of bad bot attempts to gain unauthorized access to a user’s online account by automating the process of guessing or cracking login credentials. Once access is gained, the bot can carry out malicious activities, such as credit card fraud or stealing sensitive information.

Take note that malicious and harmful bots have become more advanced in recent years because of cybercriminals, making them more challenging to identify and block—the bots have evolved from basic crawlers to more sophisticated programs that mimic human behavior, using advanced techniques to avoid detection.

Let’s now proceed to highlighting some telltale signs—the indicators—that will help inform you if a particular bot is good or evil.

How do you best identify the good bots from bad bots?

We’ve discussed various ways in which bots are utilized today. The difference lies in the intention of the person who created the bot—it can be either useful or harmful. From the perspective of a business owner or a regular user, how can you distinguish between good and bad bots? Even for someone who is new to the subject, there are ways to differentiate between the two.

Approach & methods	How it works	Good bots identification	Bad bots identification
User Agent Analysis	The website owner can check the user-agent strings of incoming traffic to their site. This information is stored in the HTTP header and is easily accessible for analysis.	A bot scans your website to index it for search engines. The official Google bot typically identifies itself by using its user agent ID, such as “Googlebot” or something similar, to let website owners know that it is indeed a bot from Google. The same thing applies for the Bing bot.	Regular users and good bots typically have a recognizable user agent ID, which can identify them and their purpose. On the other hand, if a bot doesn’t include a user agent ID or the ID is unknown, this could indicate that the bot is malicious and should be treated as a potential threat.
Behavior Analysis	This approach is used to identify the bot’s behavior or network. The program looks at the request frequency, IP address, and content of the request.	A good bot is likely to make requests at a consistent rate, with a small number of requests per minute.	A bad bot might make excessive requests, attempting to scrape data or overwhelm the website.
IP address Analysis	A method used to identify the source of incoming traffic on a website or network. Checking the IP address can determine if it belongs to a credible source or not.	Good bots often use static IP addresses, meaning that the same IP address is used consistently for all requests. There’s a known list of IP addresses of confirmed good bots to check and compare.	Bad bots often use dynamic IP addresses, which change frequently, making it more difficult to identify and track their activity.
CAPTCHA Challenge	CAPTCHA is a technique used to distinguish between good and bad bots by presenting a challenge to the user. The most common type of challenge is a distorted text or image that must be solved before accessing a website. Moreover, Google’s reCAPTCHA can be used for free to protect websites from spam and abuse. Unlike traditional CAPTCHAs, reCAPTCHA employs advanced algorithms and machine learning models to analyze user behavior.	Good bots, such as search engine crawlers, are designed to mimic human behavior and solve simple CAPTCHA challenges. With the help of Google’s reCAPTCHA It identifies good bots by analyzing the IP address reputation, browser behavior, device information and cookie usage.	Google’s reCAPTCHA can identify and block malicious bots. It uses various signals to determine if a request is made by a human or a bot, such as the IP address, browser type, and other characteristics. If the system suspects that a request comes from a bad bot, it may ask the user to complete a challenging and complex task or puzzle.

What is bot management and how does it work?

Bot management is necessary for identifying, monitoring, and tracking the behavior of bots on a website or network. It aims to manage good bots, which are beneficial to the website or network, while protecting against bad bots, which can cause harm. The goal is to take advantage of the good bots and eliminate the negative impact of the malicious ones.

For a business/website owner, bot management is of utmost importance, as it plays a vital role in protecting your online assets and maintaining the integrity of your website. Here are a few key reasons why bot management should be on your radar:

Protects against spam and fraud. Bot management can help identify and prevent spam and fraudulent activities on your website. This not only protects your business and its reputation, but it also helps ensure the safety of your customers.
Maintains website performance. Bots in general can consume a significant amount of your website’s resources, slowing down the performance and affecting the user experience. Properly managing bots helps to regulate and control the bot traffic, reduce the load on your servers and maintain the website and SEO performance.
Ensures fair competition. Managing bots also helps prevent the use of bad bots from unethical scraping of a website’s content, ensuring a fair and level playing field for all businesses. For instance, web scraping can be used by your competitor to research and analyze your website—for example, to find out what your best product offerings, features, categories, and bundle deals are. Competitors can also use illegal scraping of SEO strategies, social media presence, and consumer feedback through comments, posts and reviews.
Protects against legal liabilities. Managing bots protects you against legal liabilities and strengthens user privacy. A bot management system could help an organization comply with, for example, the European Union’s General Data Protection Regulation (GDPR). The protocol requires companies to protect the personal data of EU citizens, making sure that the data is processed in a transparent and secure manner.
Compliance with regulations. Certain industries and sectors are subject to regulations that require them to protect user data and prevent malicious activity. Managing bots can help organizations and website owners to comply with these regulations and avoid costly fines.
Protects online advertising revenue. Malicious bots can compromise online advertising systems, leading to lost revenue for publishers and advertisers. You can prevent this by blocking harmful bots from accessing advertising networks.
Preserves the integrity of online data and analytics. Bot management helps to prevent bots from skewing website analytics and distorting the data that businesses rely on to make informed decisions.

In bot management, the process typically involves several technical components. Let’s take a look at how this system works and see some examples.

Component	Description	Example
Bot Detection	This is the first step in the bot management process. It involves identifying bots that are accessing your website or application. It can be done by different approaches such as user-agent analysis, IP address analysis and behavioral analysis.	A website admin uses IP address analysis as an approach to determine if the incoming request is from a known good bot, such as Googlebot, or a known bad bot, such as botnet.
Bot Classification	Once bots have been detected, the next step is to classify them into good bots and bad bots. This is done based on the information gathered during bot detection.	After classifying if it’s a good bot—let’s say it’s a search engine crawler—the website admin then lets these bots crawl through the website. If it’s a bad bot, the admin blocks traffic from it.
Bot Filtering	This is the process of blocking or limiting the access of bad bots to your website or application. This can be done using various methods, such as rate limiting, IP blocking, and CAPTCHA challenges.	For example, the website admin can use rate limiting, which involves setting a maximum number of requests that a bot can make to your website or application within a given time period.
Bot Monitoring	Bot monitoring is the process of keeping track of a bot’s activities such as automated programs that perform various tasks online. This is important because bots can be used for both good and bad purposes. Without proper monitoring, they can cause security risks, harm businesses, or negatively impact consumers.	An ecommerce website’s administrator can utilize bot monitoring to track the quantity of requests made by each bot to the site and compare it to their past data. This helps identify any abrupt increases in activity that might suggest malicious behavior. If the monitoring system detects any harmful bots, it may automatically block them or notify the administrator for closer examination.
Bot Reporting	A process of generating reports on bot activity. These reports include the number of bots detected, the types of bots, and the actions taken to manage the bots. They can be used to track the effectiveness of your bot management system and make informed decisions about future bot management strategies.	For instance, using bot reporting like log analysis, dashboards and alerts. These practices can generate daily or weekly reports on the activity of bots on the website, including the number of bots detected, the types of bots detected, and the actions taken to manage the bots.

These are a few examples of some of the technical components in bot management. Apart from the ones mentioned above, there are some specific components and tools used depending on the unique needs and requirements of your website and application. This may include bot management solutions that are a paid service and can be purchased online.

Within the market, there are complex, third party solutions designed to protect websites and apps from malicious bots. They’re designed to detect bots, distinguish between good and bad ones, block malicious activities, gather logs, and continuously evolve to stay ahead of the rising threat of bad bots. These solutions make it easier for website/app owners, as the owners don’t need to build their own protection—simply activate a third-party service and enjoy the protection it provides. One such service is Gcore Protection, and we will discuss how it works and helps fight against bad bots.

How does Gcore protection work against bad bots?

Gcore offers a comprehensive web security solution that includes robust bot protection. We understand the growing concern surrounding bad bots and our solution tackles this challenge through a three-level approach.

DDoS Protection. Our first level offers protection against common L3/L4 volumetric attacks, which are often used in DDoS attacks. This reduces the risk of service outages and prevents website performance degradation.

Discover more details about Gcore’s DDoS protection.
Web Application Firewall. Our WAF employs a combination of real-time monitoring and advanced machine learning techniques to protect user information and prevent the loss of valuable digital assets. The DDoS protection system at Gcore functions by continuously evaluating incoming traffic in real-time, checking it against set rules, calculating request features based on assigned weights, and blocking requests that exceed the defined threshold score.
Bot Protection. By using Gcore’s Bot Protection, you can safeguard your online services from overloading and ensure a seamless business workflow. This level of protection utilizes a set of algorithms designed to remove any unwanted traffic that has already entered the perimeter. As a result, it mitigates website fraud attacks, eliminates request form spamming, and prevents brute-force attacks.

Our bot protection guarantees defense against these malicious bot activities:

Web content scraping
Account takeover
Form submission abuse
API data scraping
TLS session attacks

At Gcore, our users enjoy complete protection from both typical invasive approaches, such as botnet attacks, as well as those that can be disguised or mixed in with legitimate traffic from real users or good bots like search engine crawlers. This, combined with the ability to integrate with a WAF, empowers our clients to effectively manage the impact of attacks across the network, transport, and application layer. Here are the key benefits and security features you can expect with Gcore’s all in one web security against DDoS attacks (L3, L4, L7), hacking threats and malicious bot activities.

Key benefits	Security features
Maintain uninterrupted service during intense attacks	Global traffic filtering with a widespread network
Focus on running your business instead of fortifying web security	DDoS attack resistance with growing network capacity
Secure your application against various attack types while preserving performance	Early detection of low-rate attacks and precise threat detection with low false positive rate
Cut costs by eliminating the need for expensive web filtering and network hardware	Session blocking for enhanced security

In addition to this, our multilevel security system keeps a close eye on all incoming requests. If it sees that a lot of requests are coming from the same IP address for a specific URL, it will flag it and block the session. Our system is smart enough to know what’s normal and what’s not. It can detect any excessive requests and respond automatically. This helps us ensure that only legitimate traffic is allowed to pass through to your website, while blocking any volumetric attacks that may come your way.

Conclusion

Bot management is crucial when it comes to websites and applications. As we discussed in this article, there are two types of bots—good bots and bad bots. Good bots bring in valuable traffic, while bad bots can cause harm and create security threats. That’s why it’s important to have proper bot management in place. By managing the different bots that access your website or application, you can keep your business safe from spam and fraud, protect your customers’ privacy and security, and make sure everyone has a good experience on your website. And by being proactive about bot management, you’ll be taking steps to keep your online presence secure and trustworthy.

Alongside utilizing the bot management strategies we’ve outlined today, Gcore adds an additional layer by offering comprehensive protection against bad bots and other types of attacks, allowing website owners to effectively manage the impact of attacks and ensure the smooth operation of their website or application. This allows businesses and individuals running websites to confidently protect their online assets and ensure their networks are secure.

Keep your website or application secure from malicious bots with Gcore’s web application security solutions. Utilizing advanced technology and staying up-to-date with the latest threats, Gcore offers peace of mind for businesses seeking top-notch security. Connect with our experts to learn more.

Flexible DDoS mitigation with BGP Flowspec

For customers who understand their own network traffic patterns, rigid DDoS protection can be more of a limitation than a safeguard. That’s why Gcore supports BGP Flowspec: a flexible, standards-based method for defining granular filters that block or rate-limit malicious traffic in real time…before it reaches your infrastructure.In this article, we’ll walk through:What Flowspec is and how it worksThe specific filters and actions Gcore supportsCommon use cases, with example rule definitionsHow to activate and monitor Flowspec in your environmentWhat is the BGP Flowspec?BGP Flowspec (RFC 8955) extends Border Gateway Protocol to distribute traffic filtering rules alongside routing updates. Instead of static ACLs or reactive blackholing, Flowspec enables near-instantaneous propagation of mitigation rules across networks.BGP tells routers how to reach IP prefixes across the internet. With Flowspec, those same BGP announcements can now carry rules, not just routes. Each rule describes a pattern of traffic (e.g., TCP SYN packets >1000 bytes from a specific subnet) and what action to take (drop, rate-limit, mark, or redirect).What are the benefits of the BGP Flowspec?Most traditional DDoS protection services react to threats after they start, whether by blackholing traffic to a target IP, redirecting flows to a scrubbing center, or applying rigid, static filters. These approaches can block legitimate traffic, introduce latency, or be too slow to respond to fast-evolving attacks.Flowspec offers a more flexible alternative.Proactive mitigation: Instead of waiting for attacks, you can define known-bad traffic patterns ahead of time and block them instantly. Flowspec lets experienced operators prevent incidents before they start.Granular filtering: You’re not limited to blocking by IP or port. With Flowspec, you can match on packet size, TCP flags, ICMP codes, and more, enabling fine-tuned control that traditional ACLs or RTBH don’t support.Edge offloading: Filtering happens directly on Gcore’s routers, offloading your infrastructure and avoiding scrubbing latency.Real-time updates: Changes to rules are distributed across the network via BGP and take effect immediately, faster than manual intervention or standard blackholing.You still have the option to block traffic during an active attack, but with Flowspec, you gain the flexibility to protect services with minimal disruption and greater precision than conventional tools allow.Which parts of the Flowspec does Gcore implement?Gcore supports twelve filter types and four actions of the Flowspec.Supported filter typesGcore supports all 12 standard Flowspec match components.Filter FieldDescriptionDestination prefixTarget subnet (usually your service or app)Source prefixSource of traffic (e.g., attacker IP range)IP protocolTCP, UDP, ICMP, etc.Port / Source portMatch specific client or server portsDestination portMatch destination-side service portsICMP type/codeFilter echo requests, errors, etc.TCP flagsFilter packets by SYN, ACK, RST, FIN, combinationsPacket lengthFilter based on payload sizeDSCPQuality of service code pointFragmentMatch on packet fragmentation characteristicsSupported actionsGcore DDoS Protection supports the following Flowspec actions, which can be triggered when traffic matches a specific filter:ActionDescriptionTraffic-rate (0x8006)Throttle/rate limit traffic by byte-per-second rateredirectRedirect traffic to alternate location (e.g., scrubbing)traffic-markingApply DSCP marks for downstream classificationno-action (drop)Drop packets (rate-limit 0)Rule orderingRFC 5575 defines the implicit order of Flowspec rules. The crucial point is that more specific announcements take preference, not the order in which the rules are propagated.Gcore also respects Flowspec rule ordering per RFC 5575. More specific filters override broader ones. Future support for Flowspec v2 (with explicit ordering) is under consideration, pending vendor adoption.Blackholing and extended blackholing (eBH)Remote-triggered blackhole (RTBH) is a standardized protection method that the client manages via BGP by analyzing traffic, identifying the direction of the attack (i.e., the destination IP address). This method protects against volumetric attacks.Customers using Gcore IP Transit can trigger immediate blackholing for attacked prefixes via BGP, using the well-known blackhole community tag 65000:666. All traffic to that destination IP is dropped at Gcore’s edge.The list of supported BGP communities is available here.BGP extended blackholeExtended blackhole (eBH) allows for more granular blackholing that does not affect legitimate traffic. For customers unable to implement Flowspec directly, Gcore supports eBH. You announce target prefixes with pre-agreed BGP communities, and Gcore translates them into Flowspec mitigations.To configure this option, contact our NOC at noc@gcore.lu.Monitoring and limitationsGcore can support several logging transports, including mail and Slack.If the number of Flowspec prefixes exceeds the configured limit, Gcore DDoS Protection stops accepting new announcements, but BGP sessions and existing prefixes will stay active. Gcore will receive a notification that you reached the limit.How to activateActivation takes just two steps:Define rules on your edge router using Flowspec NLRI formatAnnounce rules via BGP to Gcore’s intermediate control planeThen, Gcore validates and propagates the filters to border routers. Filters are installed on edge devices and take effect immediately.If attack patterns are unknown, you’ll first need to detect anomalies using your existing monitoring stack, then define the appropriate Flowspec rules.Need help activating Flowspec? Get in touch via our 24/7 support channels and our experts will be glad to assist.Set up GRE and benefit from Flowspec today

Securing AI from the ground up: defense across the lifecycle

As more AI workloads shift to the edge for lower latency and localized processing, the attack surface expands. Defending a data center is old news. Now, you’re securing distributed training pipelines, mobile inference APIs, and storage environments that may operate independently of centralized infrastructure, especially in edge or federated learning contexts. Every stage introduces unique risks. Each one needs its own defenses.Let’s walk through the key security challenges across each phase of the AI lifecycle, and the hardening strategies that actually work.PhaseTop threatsHardening stepsTrainingData poisoning, leaksValidation, dataset integrity tracking, RBAC, adversarial trainingDevelopmentModel extraction, inversionRate limits, obfuscation, watermarking, penetration testingInferenceAdversarial inputs, spoofed accessInput filtering, endpoint auth, encryption, TEEsStorage and deploymentModel theft, tamperingEncrypted containers, signed builds, MFA, anomaly monitoringTraining: your model is only as good as its dataThe training phase sets the foundation. If the data going in is poisoned, biased, or tampered with, the model will learn all the wrong lessons and carry those flaws into production.Why it mattersData poisoning is subtle. You won’t see a red flag during training logs or a catastrophic failure at launch. These attacks don’t break training, they bend it.A poisoned model may appear functional, but behaves unpredictably, embeds logic triggers, or amplifies harmful bias. The impact is serious later in the AI workflow: compromised outputs, unexpected behavior, or regulatory non-compliance…not due to drift, but due to training-time manipulation.How to protect itValidate datasets with schema checks, label audits, and outlier detection.Version, sign, and hash all training data to verify integrity and trace changes.Apply RBAC and identity-aware proxies (like OPA or SPIFFE) to limit who can alter or inject data.Use adversarial training to improve model robustness against manipulated inputs.Development and testing: guard the logicOnce you’ve got a trained model, the next challenge is protecting the logic itself: what it knows and how it works. The goal here is to make attacks economically unfeasible.Why it mattersModels encode proprietary logic. When exposed via poorly secured APIs or unprotected inference endpoints, they’re vulnerable to:Model inversion: Extracting training dataExtraction: Reconstructing logicMembership inference: Revealing whether a datapoint was in trainingHow to protect itApply rate limits, logging, and anomaly detection to monitor usage patterns.Disable model export by default. Only enable with approval and logging.Use quantization, pruning, or graph obfuscation to reduce extractability.Explore output fingerprinting or watermarking to trace unauthorized use in high-value inference scenarios.Run white-box and black-box adversarial evaluations during testing.Integrate these security checks into your CI/CD pipeline as part of your MLOps workflow.Inference: real-time, real riskInference doesn’t get a free pass because it’s fast. Security needs to be just as real-time as the insights your AI delivers.Why it mattersAdversarial attacks exploit the way models generalize. A single pixel change or word swap can flip the classification.When inference powers fraud detection or autonomous systems, a small change can have a big impact.How to protect itSanitize input using JPEG compression, denoising, or frequency filtering.Train on adversarial examples to improve robustness.Enforce authentication and access control for all inference APIs—no open ports.Encrypt inference traffic with TLS. For added privacy, use trusted execution environments (TEEs).For highly sensitive cases, consider homomorphic encryption or SMPC—strong but compute-intensive solutions.Check out our free white paper on inference optimization.Storage and deployment: don’t let your model leakOnce your model’s trained and tested, you’ve still got to deploy and store it securely—often across multiple locations.Why it mattersUnsecured storage is a goldmine for attackers. With access to the model binary, they can reverse-engineer, clone, or rehost your IP.How to protect itStore models on encrypted volumes or within enclaves.Sign and verify builds before deployment.Enforce MFA, RBAC, and immutable logging on deployment pipelines.Monitor for anomalous access patterns—rate, volume, or source-based.Edge strategy: security that moves with your AIAs AI moves to the edge, centralized security breaks down. You need protection that operates as close to the data as your inference does.That’s why we at Gcore integrate protection into AI workflows from start to finish:WAAP and DDoS mitigation at edge nodes—not just centralized DCs.Encrypted transport (TLS 1.3) and in-node processing reduce exposure.Inline detection of API abuse and L7 attacks with auto-mitigation.180+ global PoPs to maintain consistency across regions.AI security is lifecycle securityNo single firewall, model tweak, or security plugin can secure AI workloads in isolation. You need defense in depth: layered, lifecycle-wide protections that work at the data layer, the API surface, and the edge.Ready to secure your AI stack from data to edge inference?Talk to our AI security experts

3 ways to safeguard your website against DDoS attacks—and why it matters

DDoS (distributed denial-of-service) attacks are a type of cyberattack in which a hacker overwhelms a server with an excessive number of requests, causing the server to stop functioning correctly and denying access to legitimate users. The volume of these types of attacks is increasing, with a 56% year-on-year rise recorded in late 2024, driven by factors including the growing availability of AI-powered tools, poorly secured IoT devices, and geopolitical tensions worldwide.Fortunately, there are effective ways to defend against DDoS attacks. Because these threats can target different layers of your network, a single tool isn’t enough, and a multi-layered approach is necessary. Businesses need to protect both the website itself and the infrastructure behind it. This article explores the three key security solutions that work together to protect your website—and the costly consequences of failing to prepare.The consequences of not protecting your website against DDoS attacksIf your website isn’t sufficiently protected, DDoS attacks can have severe and far-reaching impacts on your website, business, and reputation. They not only disrupt the user experience but can spiral into complex, costly recovery efforts. Safeguarding your website against DDoS attacks is essential to preventing the following serious outcomes:Downtime: DDoS attacks can exhaust server resources (CPU, RAM, throughput), taking websites offline and making them unavailable to end users.Loss of business/customers: Frustrated users will leave, and many won’t return after failed checkouts or broken sessions.Financial losses: By obstructing online sales, DDoS attacks can cause businesses to suffer substantial loss of revenue.Reputational damage: Websites or businesses that suffer repeated unmitigated DDoS attacks may cause customers to lose trust in them.Loss of SEO rankings: A website could lose its hard-won SEO ranking if it experiences extended downtime due to DDoS attacks.Disaster recovery costs: DDoS disaster recovery costs can escalate quickly, encompassing hardware replacement, software upgrades, and the need to hire external specialists.Solution #1: Implement dedicated DDoS protection to safeguard your infrastructureAdvanced DDoS protection measures are customized solutions designed to protect your servers and infrastructure against DDoS attacks. DDoS protection helps defend against malicious traffic designed to crash servers and interrupt service.Solutions like Gcore DDoS Protection continuously monitor incoming traffic for suspicious patterns, allowing them to automatically detect and mitigate attacks in real time. If your resources are attacked, the system filters out harmful traffic before it reaches your servers. This means that real users can access your website without interruption, even during an attack.For example, a financial services provider could be targeted by cybercriminals attempting to disrupt services with a large-scale volumetric DDoS attack. With dedicated DDoS protection, the provider can automatically detect and filter out malicious traffic before it impacts users. Customers can continue to log in, check balances, and complete transactions, while the system adapts to the evolving nature of the attack in the background, maintaining uninterrupted service.The protection scales with your business needs, automatically adapting to higher traffic loads or more complex attacks. Up-to-date reports and round-the-clock technical support allow you to keep track of your website status at all times.Solution #2: Enable WAAP to protect your websiteGcore WAAP (web application and API protection) is a comprehensive solution that monitors, detects, and mitigates cyber threats, including DDoS layer 7 attacks. WAAP uses AI-driven algorithms to monitor, detect, and mitigate threats in real time, offering an additional layer of defense against sophisticated attackers. Once set up, the system provides powerful tools to create custom rules and set specific triggers. For example, you can specify the conditions under which certain requests should be blocked, such as sudden spikes in API calls or specific malicious patterns common in DDoS attacks.For instance, an e-commerce platform during a major sale like Black Friday could be targeted by bots attempting to flood the site with fake login or checkout requests. WAAP can differentiate between genuine users and malicious bots by analyzing traffic patterns, rate of requests, and attack behaviors. It blocks malicious requests so that real customers can continue to complete transactions without disruption.Solution #3: Connect to a CDN to strengthen defenses furtherA trustworthy content delivery network (CDN) is another valuable addition to your security stack. A CDN is a globally distributed server network that ensures efficient content delivery. CDNs spread traffic across multiple global edge servers, reducing the load on the origin server. During a DDoS attack, a CDN with DDoS protection can protect servers and end users. It filters traffic at the edge, blocking threats before they ever reach your infrastructure. Caching servers within the CDN network then deliver the requested content to legitimate users, preventing network congestion and denial of service to end users.For instance, a gaming company launching a highly anticipated multiplayer title could face a massive surge in traffic as players around the world attempt to download and access the game simultaneously. This critical moment also makes the platform a prime target for DDoS attacks aimed at disrupting the launch. A CDN with integrated DDoS protection can absorb and filter out malicious traffic at the edge before it reaches the core infrastructure. Legitimate players continue to enjoy fast downloads and seamless gameplay, while the origin servers remain stable and protected from overload or downtime.In addition, Super Transit intelligently routes your traffic via Gcore’s 180+ point-of-presence global network, proactively detecting, mitigating, and filtering DDoS attacks. Even mid-attack, users experience seamless access with no interruptions. They also benefit from an enhanced end-user experience, thanks to shorter routes between users and servers that reduce latency.Taking the next steps to protect your websiteDDoS attacks pose significant threats to websites, but a proactive approach is the best way to keep your site online, secure, and resilient. Regardless of your industry or location, it’s crucial to take action to safeguard your website and maintain its uninterrupted availability.Enabling Gcore DDoS protection is a simple and proven way to boost your digital infrastructure’s resiliency against different types of DDoS attacks. Gcore DDoS protection also integrates with other security solutions, including Gcore WAAP, which protects your website and CDNs. These tools work seamlessly together to provide advanced website protection, offering improved security and performance in one intuitive platform.If you’re ready to try Gcore Edge Security, fill in the form below and one of our security experts will be in touch for a personalized consultation.

From reactive to proactive: how AI is transforming WAF cybersecurity solutions

While digital transformation in recent years has driven great innovation, cyber threats have changed in parallel, evolving to target the very applications businesses rely on to thrive. Traditional web application security measures, foundational as they may be, are no longer effective in combating sophisticated attacks in time. Enter the next generation of WAFs (web application firewalls) powered by artificial intelligence.Next-generation WAFs, often incorporated into WAAP solutions, do much more than respond to threats; instead, they will use AI and ML-powered techniques to predict and neutralize threats in real time. This helps businesses to stay ahead of bad actors by securing applications, keeping valuable data safe, and protecting hard-earned brand reputations against ever-present dangers in an expanding digital world.From static to AI-powered web application firewallsTraditional WAFs were relied on to protect web applications against known threats, such as SQL injection and cross-site scripting. They’ve done a great job as the first line of defense, but their reliance on static rules and signature-based detection means they struggle to keep up with today’s fast-evolving cyber threats. To understand in depth why traditional WAFs are no longer sufficient in today’s threat landscape, read our ebook.AI and ML have already revolutionized what a WAF can do. AI/ML-driven WAFs can examine vast streams of traffic data and detect patterns, including new threats, right at the emergence stage. The real-time adaptability that this allows is effective even against zero-day attacks and complex new hacking techniques.How AI-powered WAP proactively stops threatsOne of the most significant advantages of AI/ML-powered WAFs is proactive identification and prevention capabilities. Here's how this works:Traffic pattern analysis: AI systems monitor both incoming and outgoing traffic to set up baselines for normal behavior. This can then allow for the detection of anomalies that could show a zero-day attack or malicious activity.Real-time decision making: Machine learning models keep learning from live traffic and detect suspicious activities on the go sans waiting for any updates in the rule set. This proactive approach ensures that businesses are guarded from emerging threats before they escalate.Heuristic tagging and behavioral insights: Advanced heuristics used by AI-driven systems tag everything from sessionless clients to unusual request frequencies. It helps administrators classify potential bots or automated attacks much faster.Ability to counter zero-day attacks: Traditional WAF solutions can only mitigate attacks that are already in the process of accessing sensitive areas. AI/ML-powered WAFs, on the other hand, can use data to identify and detect patterns indicative of future attacks, stopping attackers in their tracks and preventing future damage.Intelligent policy management: Adaptive WAFs detect suspicious activity and alert users to misconfigured security policies accordingly. They reduce the need for manual configuration while assuring better protection.Integrated defense layers: One of the strongest features of AI/ML-powered systems is the ease with which they integrate other layers of security, including bot protection and DDoS mitigation, into a connected architecture that protects several attack surfaces.User experience and operational impactAI-driven WAFs improve the day-to-day operations of security teams by transforming how they approach threat management. With intuitive dashboards and clearly presented analytics, as offered by Gcore WAAP, these tools empower security professionals to quickly interpret complex data, streamline decision-making, and respond proactively to threats.Instead of manually analyzing vast amounts of traffic data, teams now receive immediate alerts highlighting critical security events, such as abnormal IP behaviors or unusual session activity. Each alert includes actionable recommendations, enabling rapid adjustments to security policies without guesswork or delay.By automating the identification of sophisticated threats such as credential stuffing, scraping, and DDoS attacks, AI-powered solutions significantly reduce manual workloads. Advanced behavioral profiling and heuristic tagging pinpoint genuine threats with high accuracy, allowing security teams to concentrate their efforts where they're most needed.Embracing intelligent security with Gcore’s AI-driven WAAPOur AI-powered WAAP solution provides intelligent, interrelated protection to empower companies to actively outperform even the most sophisticated, ever-changing threats by applying advanced traffic analysis, heuristic tagging, and adaptive learning. With its cross-domain functionality and actionable security insights, this solution stands out as an invaluable tool for both security architects and strategic decision-makers. It combines innovation and practicality to address the needs of modern businesses.Curious to learn more about WAAP? Check out our ebook for cybersecurity best practices, the most common threats to look out for, and how WAAP can safeguard your businesses’ digital assets. Or, get in touch with our team to learn more about Gcore WAAP.Learn why WAAP is essential for modern businesses with a free ebook

How AI helps prevent API attacks

APIs have become an integral part of modern digital infrastructure, and it can be easy to take their security for granted. But, unfortunately, APIs are a popular target for attackers. Hackers can use APIs to access crucial data and services, and breaching APIs allows attackers to bypass traditional security controls.Most companies focus on speed of development and deployment ahead of security when crafting APIs, making them vulnerable to issues like insecure authentication, poor validation, or misconfigured endpoints, which attackers can abuse. Additionally, the interconnected nature of APIs creates multiple endpoints, widening the attack surface and creating additional points of entry that attackers can exploit.As threats evolve and the attack surface grows to include more API endpoints, integrating AI threat detection and mitigation is an absolute must for businesses to take serious, deliberate action against API cyberattacks. Let’s find out why.Staying ahead of zero-day API attacksOf all the cyber attacks that commonly threaten APIs, zero-day attacks, leveraging unknown vulnerabilities, are probably the toughest to defeat. Traditional solutions rely more on the existence of preconfigured rules or signatures along with human interference to detect and block such attacks. This approach often fails against novel threats and can block legitimate traffic, leaving applications vulnerable and making APIs inaccessible to users.APIs must balance between allowing legitimate users access and maintaining security. AI and ML technologies excel at identifying zero-day attacks based on pattern and behavior analysis rather than known signatures. For instance, heuristic algorithms can detect anomalies, such as sudden spikes in unusual traffic or behaviors indicative of malicious intent.Consider the following example: A certain IP address makes an abnormally large number of requests to a rarely accessed endpoint. Even without prior knowledge of the IP or attack vector, an AI/ML-enhanced solution can flag the activity as suspicious and block it proactively. Using minimal indicators, such as frequency patterns or traffic anomalies, AI can stop attackers before they fully exploit vulnerabilities. Additionally, this means that only suspicious IPs are blocked, and legitimate users can continue to access APIs unimpeded.The risks of shadow APIsOne of the biggest risks is shadow APIs, which are endpoints that exist but aren't documented or monitored. These can arise from configuration mistakes, forgotten updates, or even rogue development practices. These unknown APIs are the ideal target for Layer 7 attacks, as they are often left undefended, making them easy targets.AI-powered API discovery tools map both known and unknown API endpoints, enabling the grouping and management of these endpoints so sensitive APIs can be properly secured. This level of visibility is critical to securing systems against API-targeting attacks; without it, businesses are left in the dark.API discovery as a critical security practiceWAAP with AI/ML capabilities excels in API security because it accurately checks and analyzes API traffic. The Gcore API discovery engine offers 97 to 99 percent accuracy, mapping APIs in users’ domains and using data to recommend policies to help secure APIs.How heuristics enhance WAAP AI capabilities to protect APIsWhile AI and ML form the backbone of modern WAAPs, heuristic methods complement them in enhancing detection accuracy. Heuristics allow the system to inspect granular behaviors, such as mouse clicks or scrolling patterns, which distinguish legitimate users from bots.For example, most scraping attacks involve automated scripts that interact with APIs in predictable and repetitive manners. In those cases, WAAP can use request patterns or user action monitoring to identify the script with high accuracy. Heuristics may define bots by checking how users interact with page elements, such as buttons or forms, and flagging those that behave unnaturally.This layered approach ensures that the most sophisticated automated attack attempts are caught in the net and mitigated without affecting legitimate traffic.Protect your APIs with the click of a button using Gcore WAAPAI offers proactive, intelligent solutions that can address the modern complexities of cybersecurity. These technologies empower organizations to secure APIs against even the most sophisticated threats, including zero-day vulnerabilities and undiscovered APIs.Interested in protecting your APIs with WAAP? Download our ebook to discover cybersecurity best practices, the most prevalent threats, and how WAAP can protect your business’s digital infrastructure, including APIs. Or, reach out to our team to learn more about Gcore WAAP.Discover why WAAP is a must-have for API protection

11 simple tips for securing your APIs

A vast 84% of organizations have experienced API security incidents in the past year. APIs (application programming interfaces) are the backbone of modern technology, allowing seamless interaction between diverse software platforms. However, this increased connectivity comes with a downside: a higher risk of security breaches, which can include injection attacks, credential stuffing, and L7 DDoS attacks, as well as the ever-growing threat of AI-based attacks.Fortunately, developers and IT teams can implement DIY API protection. Mitigating vulnerabilities involves using secure coding techniques, conducting thorough testing, and applying strong security protocols and frameworks. Alternatively, you can simply use a WAAP (web application and API protection) solution for specialized, one-click, robust API protection.This article explains 11 practical tips that can help protect your APIs from security threats and hacking attempts, with examples of commands and sample outputs to provide API security.#1 Implement authentication and authorizationUse robust authentication mechanisms to verify user identity and authorization strategies like OAuth 2.0 to manage access to resources. Using OAuth 2.0, you can set up a token-based authentication system where clients request access tokens using credentials. # Requesting an access token curl -X POST https://yourapi.com/oauth/token \ -d "grant_type=client_credentials" \ -d "client_id=your_client_id" \ -d "client_secret=your_client_secret" Sample output: { "access_token": "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9...", "token_type": "bearer", "expires_in": 3600 } #2 Secure communication with HTTPSEncrypting data in transit using HTTPS can help prevent eavesdropping and man-in-the-middle attacks. Enabling HTTPS may involve configuring your web server with SSL/TLS certificates, such as Let’s Encrypt with nginx. sudo certbot --nginx -d yourapi.com #3 Validate and sanitize inputValidating and sanitizing all user inputs protects against injection and other attacks. For a Node.js API, use express-validator middleware to validate incoming data. app.post('/api/user', [ body('email').isEmail(), body('password').isLength({ min: 5 }) ], (req, res) => { const errors = validationResult(req); if (!errors.isEmpty()) { return res.status(400).json({ errors: errors.array() }); } // Proceed with user registration }); #4 Use rate limitingLimit the number of requests a client can make within a specified time frame to prevent abuse. The express-rate-limit library implements rate limiting in Express.js. const rateLimit = require('express-rate-limit'); const apiLimiter = rateLimit({ windowMs: 15 * 60 * 1000, // 15 minutes max: 100 }); app.use('/api/', apiLimiter); #5 Undertake regular security auditsRegularly audit your API and its dependencies for vulnerabilities. Runnpm auditin your Node.js project to detect known vulnerabilities in your dependencies. npm audit Sample output: found 0 vulnerabilities in 1050 scanned packages #6 Implement access controlsImplement configurations so that users can only access resources they are authorized to view or edit, typically through roles or permissions. The two more common systems are Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) for a more granular approach.You might also consider applying zero-trust security measures such as the principle of least privilege (PoLP), which gives users the minimal permissions necessary to perform their tasks. Multi-factor authentication (MFA) adds an extra layer of security beyond usernames and passwords.#7 Monitor and log activityMaintain comprehensive logs of API activity with a focus on both performance and security. By treating logging as a critical security measure—not just an operational tool—organizations can gain deeper visibility into potential threats, detect anomalies more effectively, and accelerate incident response.#8 Keep dependencies up-to-dateRegularly update all libraries, frameworks, and other dependencies to mitigate known vulnerabilities. For a Node.js project, updating all dependencies to their latest versions is vital. npm update #9 Secure API keysIf your API uses keys for access, we recommend that you make sure that they are securely stored and managed. Modern systems often utilize dynamic key generation techniques, leveraging algorithms to automatically produce unique and unpredictable keys. This approach enhances security by reducing the risk of brute-force attacks and improving efficiency.#10 Conduct penetration testingRegularly test your API with penetration testing to identify and fix security vulnerabilities. By simulating real-world attack scenarios, your organizations can systematically identify vulnerabilities within various API components. This proactive approach enables the timely mitigation of security risks, reducing the likelihood of discovering such issues through post-incident reports and enhancing overall cybersecurity resilience.#11 Simply implement WAAPIn addition to taking the above steps to secure your APIs, a WAAP (web application and API protection) solution can defend your system against known and unknown threats by consistently monitoring, detecting, and mitigating risks. With advanced algorithms and machine learning, WAAP safeguards your system from attacks like SQL injection, DDoS, and bot traffic, which can compromise the integrity of your APIs.Take your API protection to the next levelThese steps will help protect your APIs against common threats—but security is never one-and-done. Regular reviews and updates are essential to stay ahead of evolving vulnerabilities. To keep on top of the latest trends, we encourage you to read more of our top cybersecurity tips or download our ultimate guide to WAAP.Implementing specialized cybersecurity solutions such as WAAP, which combines web application firewall (WAF), bot management, Layer 7 DDoS protection, and API security, is the best way to protect your assets. Designed to tackle the complex challenges of API threats in the age of AI, Gcore WAAP is an advanced solution that keeps you ahead of security threats.Discover why WAAP is a non-negotiable with our free ebook