AI-driven automation is no longer emerging. It is already integrated and accepted as internet traffic. From AI assistants and crawlers to enterprise automation tools, websites are now routinely accessed by non-human actors operating at scale.  Vulnerabilities or weaknesses in your application infrastructure, including risky APIs, are no longer difficult to find, as agentic AI tools, paired with automation, can observe and test endpoints and access points faster than any human.

AI-aware bot protection is a security approach that detects, classifies, and controls automated traffic generated by AI agents, LLM-powered assistants, and autonomous tools — then applies granular policies based on each bot’s identity, intent, and behavior.

Key Takeaways:

• AI-powered bots now represent a significant and growing share of internet traffic, blending seamlessly into legitimate user sessions.
• Traditional bot detection cannot reliably distinguish between beneficial AI assistants and malicious AI-driven agents.
• Unmanaged AI bots create measurable business risks: analytics distortion, inventory manipulation, API abuse, account takeover, and content scraping.
• Imperva Advanced Bot Protection provides granular visibility and control over AI-driven traffic by tool type, category, behavior, and business function.
• Effective AI bot management in 2026 requires multilayered detection with real-time, policy-based response capabilities.

The challenge for security teams is no longer understanding why automation is increasing, but gaining clear visibility and control over what that automation is doing.

The result is a growing grey zone where distinguishing among human users, legitimate AI agents, and malicious bots becomes significantly more challenging, and where traditional security controls often lack the visibility needed to reliably distinguish among them.

According to Imperva’s 2025 Bad Bot Report, bad bots accounted for 32% of all internet traffic — a 2% increase year-over-year. With AI-powered tools accelerating automation, this figure is expected to grow significantly in 2026, making bot detection and bot management a critical priority for every organization.

How Do AI Bots Blend Into Legitimate Web Traffic?

AI agents and automated tools are improving how people interact with the internet, dramatically enhancing productivity and convenience. For example:

• AI assistants like ChatGPT, Perplexity AI, and Google Gemini retrieve real-time answers from multiple websites to summarise content or compare products
• Travel platforms continuously check flight prices, seat availability, and hotel inventory
• E-commerce monitoring tools track pricing, stock levels, and competitor offers across retailers
• AI-powered shopping assistants help users find deals or complete purchases faster
• Enterprise AI tools query SaaS platforms and APIs to automate workflows like reporting, customer support, and data enrichment
• Search and indexing bots extract and index web content to power AI-driven search experiences

However, the same technological advancements that enable these positive experiences are also empowering cybercriminals. Automation at scale lowers the barrier for malicious activity, putting malicious bots at a significant advantage when automated traffic is the expected baseline. They can blend seamlessly into legitimate traffic patterns, making detection significantly more challenging.

What Are the Business Risks of Unmanaged AI Bot Traffic?

Many organizations still view bot protection as optional. However, with AI agents such as crawler bots and fetch bots, now an accepted part of internet traffic and automation accelerating at scale, bot protection has become a core security requirement. Failing to treat it as such exposes organizations to serious business risks:

Risk Category	Description	Business Impact
Analytics Manipulation	AI bots inflate traffic metrics and distort conversion data	Misinformed decisions, wasted ad spend
Inventory Hoarding	Automated agents reserve or purchase inventory at scale	Revenue loss, customer experience degradation
API Business Logic Abuse	AI agents exploit API endpoints beyond intended use	Infrastructure costs, data exposure
Account Takeover (ATO)	AI-powered credential stuffing at scale	Customer trust erosion, regulatory liability
Data Scraping	AI systems extract proprietary content for training or replication	Competitive disadvantage, IP loss
Customer Experience	Bot traffic degrades site performance and availability	Reputational damage, increased churn

How Does Imperva Deliver AI Bot Detection and Control?

The ability to control which parts of your application functionality are accessible to AI tools is critical to your AI Security Strategy.

How Does Imperva Provide Visibility Into AI Bot Traffic?

Imperva Advanced Bot Protection (ABP) offers granular visibility into AI tools, agents, and crawlers, providing a detailed, real-time view of which AI tools are accessing your websites, applications, and API endpoints.

With ABP, security teams can clearly see which AI tools are hitting their environment, which applications and URLs are being accessed, the volume and frequency of requests, and whether those requests are being allowed, blocked, or challenged

This level of visibility ensures organizations know exactly what is interacting with their digital services and helps identify unintended policy outcomes, such as blocking AI tools they want to allow, or allowing tools they should restrict.

The AI Tools dashboard provides a centralized view of AI-driven traffic, enabling faster investigation and more informed decision-making.

How Can You Control AI Bots by Tool Type, Category, and Behavior?

Beyond visibility, Imperva enables precise control over how AI tools interact with your applications.

With ABP, security teams can easily:

• Allow, block, or rate-limit specific AI tools
• Apply policies based on categories such as AI crawlers, AI agents, and AI fetch bots
• Quickly adapt policies as new AI tools emerge

This allows organizations to move from reactive blocking to intentional control of automated access.

How Does Imperva Protect Critical Business Functions from AI Bots?

Imperva ABP also provides granular control at the application and business function levels, allowing organizations to define exactly which parts of their applications AI tools are allowed to access. This ensures that:

• Approved tools can only reach intended endpoints
• Sensitive paths, APIs, or business logic remain protected
• Access policies align with business and data governance requirements

This ensures AI tools interact with applications in a controlled, predictable, and secure way.

Why Is Imperva ABP a Leading Bot Management Solution?

ABP protection against AI builds on an already strong foundation of Advanced Bot Protection, combining multilayered detection, intelligent risk scoring, and real-time controls to accurately distinguish between human, legitimate automation, and malicious bots. With deep visibility, rapid decisioning, and expert support, ABP is already a proven solution for managing sophisticated bot threats. It is now further strengthened by the ability to monitor and control AI-driven traffic precisely.

Capability	Traditional Bot Detection	AI-Aware Bot Protection (Imperva ABP)
Detection Method	Signature and rule-based	ML-based behavioral analysis + AI tool fingerprinting
AI Tool Classification	No distinction between AI tools	Granular classification by tool type, category, and identity
Granularity of Control	Block or allow all bots	Allow, block, rate-limit, or challenge per AI tool and per endpoint
Visibility	Limited to known bot signatures	Real-time dashboard of all AI tool activity by type and behavior
Adaptability	Manual rule updates required	Continuous learning with rapid policy adaptation for new AI tools
Business Function Protection	URL-level blocking only	Granular control at the application and business function level

Frequently Asked Questions About AI Bot Protection

Q: What is AI-aware bot protection?

A: AI-aware bot protection is a security approach that detects, classifies, and controls automated traffic from AI agents, LLM-powered assistants, and autonomous tools. Unlike traditional bot detection that relies on static signatures, AI-aware protection uses behavioral analysis and AI tool fingerprinting to distinguish between beneficial AI assistants, legitimate automation, and malicious bots.

Q: What is the difference between traditional bot detection and AI-aware bot management?

A: Traditional bot detection identifies bots using predefined signatures and rules, treating most automated traffic as either good or bad. AI-aware bot management goes further by classifying AI tools by type, category, and behavior — enabling organizations to allow helpful AI agents while blocking or rate-limiting harmful ones with granular policies.

Q: How do AI agents bypass conventional bot defenses?

A: AI agents can mimic human browsing behavior, rotate IP addresses, solve CAPTCHA, and generate realistic session patterns. Because they operate as legitimate AI tools (such as AI assistants and search crawlers), they often pass through conventional defenses that only look for known malicious signatures.

Q: What business risks do AI bots create?

A: Unmanaged AI bots can distort marketing analytics, hoard inventory, abuse API business logic, perform credential stuffing for account takeover, scrape proprietary data and competitive intelligence, and degrade customer experience through increased site latency.

Q: Can businesses allow some AI bots while blocking others?

A: Yes. Solutions like Imperva Advanced Bot Protection enable granular control, allowing organizations to allow specific AI tools (such as approved search crawlers), rate-limit others (such as AI assistants accessing content), and block malicious AI agents — all at the individual tool, category, or endpoint level.

Q: What is agentic AI, and why does it matter for application security?

A: Agentic AI refers to autonomous AI systems that can independently browse the web, interact with APIs, and complete multi-step tasks without human oversight. These agents can probe for vulnerabilities, test endpoints, and access business functions faster than any human, making agentic AI security a critical concern for organizations.

Monitor, Control, and Prevent AI-Driven Bot Threats

Automation is now a permanent and growing part of how the internet operates. The critical challenge is no longer detecting bots alone but understanding and controlling AI-driven interactions at scale.

Organizations need to know exactly which AI tools are accessing their environments, what they are doing, and how to control that access with precision.

Imperva Advanced Bot Protection delivers the visibility, control, and adaptive protection required to operate securely in this new environment.

By enabling organizations to monitor AI agents, control their access at a granular level, and prevent malicious automation from hiding within legitimate traffic, Imperva helps businesses confidently embrace the future of AI-driven digital experiences.

Learn how Imperva Advanced Bot Protection delivers AI-aware bot management for your applications. Explore our bot protection solutions or download the latest Imperva Bad Bot Report for the most current data on AI-driven bot threats.

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Application development has changed dramatically. Enterprises now release software faster, operate more digital services, and deploy applications across a mix of public cloud, private cloud, APIs, containers, and on-premises infrastructure.

As application delivery has accelerated and architectures have become more distributed, a disconnect has emerged between the teams building applications and those responsible for protecting them.

This tension is often described as the Wall of Confusion between DevOps and IT Security.

But the challenge does not stop there.

Over time, organizations have also introduced multiple security tools to protect different parts of the application stack. Each tool is managed separately, often by different teams, through different platforms, policies, and workflows.

The result is an additional layer of complexity. Security teams must navigate multiple vendors and fragmented controls, while DevOps teams experience delays as security becomes harder to integrate into fast-moving development cycles.

Understanding how to break down both the organizational and operational layers of this confusion is essential for organizations that want to maintain innovation while ensuring consistent, scalable security.

Applications Now Run Across Hybrid Environments

Today, around forty percent of enterprise applications run in the public cloud, and that number is expected to rise significantly to 62% over the next two years.

Source: Vanson Bourne Survey, “DevOps vs Security: Breaking Down the Wall of Confusion in Modern Application Delivery”

Yet the shift to cloud does not mean applications live in one place. Most organizations now operate across hybrid and multi-cloud environments where applications run across public cloud platforms, private cloud infrastructure, on-premises systems, Kubernetes clusters, and an expanding network of APIs.

Cloud-agnostic strategies are also becoming more common as organizations seek flexibility and avoid dependence on a single provider. At the same time, many enterprises continue to operate legacy systems alongside modern cloud-native services.

The result is a highly distributed application landscape. Applications now run across multiple environments simultaneously, and security must be able to protect them wherever they operate.

Source: Vanson Bourne Survey, “DevOps vs Security: Breaking Down the Wall of Confusion in Modern Application Delivery”

DevOps and Security Want the Same Outcome

Despite the perception of conflict, DevOps and IT Security teams are largely aligned on the goals of modern application security. Both groups ultimately want the same outcome: applications that are secure, reliable, and able to scale with business demand.

Research conducted with Vanson Bourne reinforces this alignment. 96% of DevOps and 95% of IT Security professionals agree that modern environments require security that is flexible across any architecture.

This global study of 1,500 professionals across the US, Europe, and APAC highlights an important point. Modern application security is not just a technology problem. It is a workflow and collaboration challenge.

Security and DevOps want the same outcome, but they experience different frustrations. These gaps can create delays, bottlenecks, false positives, and friction that undermine the cloud-native innovation organizations are working to achieve.

The Wall of Confusion: Conflicting Priorities, Fragmented Security and Tool Sprawl

The Wall of Confusion is not just about DevOps and Security working in silos. It is also about how security is delivered. Over time, organizations have added more and more security tools. One for web applications, another for APIs, another for cloud, another for containers. Each tool solves a specific problem, but together they create complexity instead of clarity.

Security teams are left navigating multiple vendors, switching between management platforms, and maintaining different policies across environments. This makes it difficult to keep controls aligned and increases operational overhead.

At the same time, gaps begin to appear. As applications move across environments, it is not always clear if they are fully protected. Policies become inconsistent because what is set in one environment does not automatically apply to another.

In fact, based on a 2026 survey of Imperva Application Security customers, 77% of security professionals say operational complexity is their biggest challenge.

For DevOps teams, this complexity shows up as delay. Security becomes a bottleneck not because it is unnecessary, but because it is too difficult to operationalize.

That is the wall and it is what needs to come down.

Why Traditional Security Models Fall Short

When applications operate across multiple environments, security approaches designed for fixed infrastructure quickly become difficult to manage.

Many organizations rely on a mixture of embedded protections, centralized security services, and environment-specific tools to protect different parts of their application landscape. While each solution may address a particular need, together they can create fragmented security architectures. This fragmentation leads to inconsistent policies, duplicated alerts, limited visibility, and increased manual effort.

Security teams must manage multiple tools and workflows, while development teams experience delays when security is applied inconsistently or too late in the process. Both teams are constrained by the same underlying issue: security models that were not designed for modern, distributed application environments.

Security Must Move with the Application

Modern applications are no longer tied to a single infrastructure model. They are composed of microservices and APIs, deployed through automated pipelines, and distributed across multiple environments.

Security therefore cannot remain a centralized checkpoint that appears late in the development process. Instead, protection needs to move with the application and operate consistently wherever that application runs.

This means security controls must function across public cloud environments, private infrastructure, hybrid deployments, Kubernetes clusters, APIs, and the traditional systems that many organizations still rely on.

DevOps and IT Security teams increasingly recognize this shift. They are not asking for less security. They are asking for security that works the way modern applications work.

Securing Applications Anywhere with Thales

As application architectures continue to evolve, organizations are no longer dealing with a single security challenge, but with the need to protect applications consistently across every environment they operate in.

The issue is not just distribution. It is how to secure that distribution without adding more tools, more complexity, or more operational overhead.

Security strategies built around isolated environments or disconnected tools are no longer sufficient. What is needed is a unified approach that delivers consistent protection, visibility, and control across the entire application landscape.

Now, the question becomes how to deliver that in practice.

Many vendors talk about flexibility but still require organizations to choose a single deployment model or manage multiple disconnected solutions. Imperva takes a fundamentally different approach. It meets organizations where they are, supporting multiple deployment models while maintaining a single, unified security experience.

This includes protection for internet-facing applications and APIs through Imperva Cloud, native integration for public cloud environments (Imperva for Google Cloud), container-based deployment for Kubernetes and microservices, and gateway deployment for on-premises, hybrid, and air-gapped environments.

The key is that all of these deployment options are powered by the same Imperva Security Engine.

This means one management console, consistent policies across every environment, and unified visibility across the entire application portfolio, regardless of where applications are deployed. Security teams do not need to manage multiple tools or vendors, and DevOps teams do not need to change how they build and deploy applications.

That is what securing applications anywhere really means.

Download the whitepaper: DevOps vs Security: Breaking Down the Wall of Confusion in Modern Application Delivery

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The holiday shopping season is the busiest time of year for online retailers, and increasingly the most dangerous. As traffic surges and customers rush to place orders, cybercriminals use the distraction and volume to blend in. Account Takeover (ATO) attacks spike sharply in November and December, targeting shoppers’ saved payment details, loyalty points, wish-lists, and personal data.

Most retailers focus on keeping sites fast and campaigns running smoothly, but this seasonal pressure creates blind spots in authentication, login flows, and Application Programming Interface API endpoints. Attackers know this and use automated tools and AI-driven bots to slip into accounts with little resistance.

During peak season, it doesn’t take long for an unnoticed credential-stuffing surge, or a burst of suspicious login attempts to translate into real financial loss and customer frustration. For many retailers, the challenge isn’t a dramatic breach, it’s the quiet, persistent account abuse that goes undetected until the damage is already done.

The Escalation of Account Takeover Attacks

According to the 2025 Imperva Bad Bot Report, Account Takeover attacks increased by 40 percent in 2024 and by more than 50 percent since 2022. The rise reflects the expanding attack surface of modern digital businesses and the increasing availability of stolen credentials.

ATO attacks are rarely brute force assaults in the traditional sense. Most rely on automation and intelligence. Attackers use:

• Credential stuffing to test stolen username and password pairs obtained from prior data breaches
• Credential cracking to predict likely passwords using AI or dictionary-based guessing techniques
• Brute force attacks to systematically attempt all possible combinations where no prior credential data exists

Each of these techniques is enhanced by bot networks capable of emulating legitimate traffic and distributing attacks across thousands of IP addresses to avoid detection.

Once an account is compromised, attackers can alter stored payment details, redeem loyalty points, exfiltrate personal data, or pivot into connected systems through single sign on integrations. The damage can be widespread and difficult to undo, making remediation costly, complex, and often too late to fully protect the victim.

The Cost of Compromise

A successful Account Takeover is not just a security failure; it is a business crisis. The consequences cascade across financial, regulatory, and reputational dimensions.

• Financial loss from fraud, chargebacks, and stolen assets
• Operational disruption as security and customer support teams manage lockouts and resets
• Regulatory exposure under privacy and data protection laws such as GDPR, CCPA, and PCI DSS
• Legal costs and compensation claims from affected customers or partners
• Reputational damage leading to customer attrition and reduced trust

Regulators increasingly view inadequate protection of user credentials as a preventable failure. In industries such as financial services, retail, and telecom, where digital identity underpins customer engagement, the stakes are exceptionally high.

The AI Advantage for Attackers

Artificial intelligence is amplifying both the scale and sophistication of ATO campaigns. Where brute force once relied purely on volume, AI brings adaptive learning and behavioural mimicry.

Modern credential stuffing bots now simulate human navigation, introduce artificial pauses, and mirror typing patterns to bypass rate limits and behavioural detection systems. Machine learning

models trained on breached data can predict likely password sequences based on language, demographics, and prior password resets.

This capability turns traditional defences into speed bumps rather than barriers. The result is faster, more evasive attacks that require intelligent, context aware countermeasures.

The Expanding API Attack Surface

As organizations modernize applications, APIs have become both essential and exposed. They connect services, mobile clients, and third-party integrations, and they now represent a primary conduit for identity and data access.

According to Imperva telemetry, around 12 percent of all API attacks in 2024 were Account Takeovers. Many of these attacks are low volume and high value, designed to evade detection. Attackers harvest sensitive information in small increments such as user identifiers, loyalty balances, and payment tokens, and use that data later for large scale fraud or identity theft.

During the holiday shopping season, attackers take advantage of the fact that retail systems are under more pressure and handling far more automated traffic than usual. Bots are designed to blend seamlessly into this activity. They mimic real customers using legitimate browsers, realistic headers, and correctly formatted API calls, which makes them difficult to distinguish from genuine shoppers.

Instead of triggering obvious high-volume spikes, attackers quietly test stolen credentials across login APIs, probe authentication flows, and map out which accounts are valid. They reuse tokens, exploit weak session handling, and launch credential stuffing campaigns at a pace that fits naturally within peak season traffic. Because the requests look structurally correct, they often bypass volumetric detection and slip past basic rate limits.

Once inside an account, automated scripts extract loyalty balances, change delivery addresses, modify stored payment methods, or pivot through single sign on to gain access to additional services. For many retailers, these subtle API driven attacks are now the fastest growing source of credential-based compromise, and they reach their highest risk in November and December.

Thales recommends:

1. Improve visibility across login traffic this holiday season

During peak shopping periods, login volumes surge and attackers use the noise to hide. Monitor login attempts, unusual session behaviour, device changes, and repeated failures so you can spot suspicious activity early.

2. Strengthen authentication without slowing real customers

Shoppers expect fast checkout experiences, especially during sales events. Use smarter authentication controls that react to risk signals such as new devices or sudden spikes in login attempts, while keeping the journey seamless for genuine users.

3. Protect high value pages such as login and checkout

These are the most heavily targeted points during the holiday rush. Account Takeover attacks often begin on the login page and escalate at checkout. Ensure these flows have the strongest monitoring and protection in place to detect unusual behaviour before accounts are compromised.

4. Secure all APIs involved in customer accounts and orders

Retailers rely on APIs for login, checkout, loyalty, order history, and account management. These endpoints see huge traffic increases in November and December, making them prime targets for automated abuse. Apply full visibility and security controls across them.

5. Deploy Advanced Bot Protection to stop automated ATO attempts

Bots spike dramatically during holiday promotions. Advanced bot protection identifies and blocks automated credential testing, scripted login attempts, and account probing in real time without adding friction for real shoppers. This is critical for preventing ATO during your busiest weeks.

Visit Imperva.com Account Takeover Protection.

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Every November and December, online retailers gear up for their biggest revenue surge of the year. But while the traffic and transactions climb, so does the threat level. Cybercriminals know exactly when customer activity (and the pressure on retail systems) is at its highest and they’re automating their attacks to exploit it.

Why retailers are especially vulnerable during peak season

Large-scale bot attacks thrive in seasonal retail: high traffic, elevated checkout volume, heavy promotional activity, and a short window for disruptions. It’s precisely when your monitoring may be stretched. According to the 2025 Thales Bad Bot Report, Retail was the second most attacked industry in 2024 (15% of all bot attacks). 33% of web traffic to retail sites was driven by bad bots. But the most recent data shows that now an astounding 53% of web traffic to retail sites is bots!

Key Findings relevant for eCommerce and Online Retail

• 53% – the percentage of bot traffic (good and bad) to retail websites in 2025.
• 39% – the percentage of bad bot traffic to online retail in 2025
• 64% – the percentage of bot attacks on retail sites targeting business logic.
• 283% – The increase in Account Takeover attacks (ATO) on Black Friday 2024
• 18,813 – The number of hours of downtime prevented by Thales in November and December 2024
• 71 Million – The number of requests per day from AI tools in 2025

Chart based on data from November 2024 to November 2025

Retailers going into peak retail season without strong bot- and account-abuse defences are exposing a key part of their business to automated fraud and exploitation.

How bad bots target Online Retailers

Retailers often focus on obvious fraud vectors (payment fraud, card testing), but bots bring subtler, higher-volume risks that can erode margins, trust, and availability:

• Account Takeover (ATO). Attackers leverage stolen credentials or credential-stuffing campaigns to hijack customer accounts — often right before a major shopping event when accounts have stored payment details, loyalty points, or wish-lists. According to the 2025 Thales Bad Bot Report Account takeover (ATO) attacks increased by around 40% in 2024, a surge attributed to improved automation and AI-driven tools.
• Price Scraping. Bots scrape pricing, and product data at scale (often just before or during promotions), enabling grey-market resale, and competitive undercutting.
• Automated Checkout Abuse / Scalper Bots. Limited-release items (sneakers, consoles, luxury goods) are bought by bots in seconds, creating inventory hoarding or resale markets.
• API & Business Logic Attacks. As retailers expose more APIs (for checkout, loyalty, account management), bots attack those endpoints rather than just classic web pages. In 2024 API attacks shifted: 44 % of advanced bot traffic targeted APIs while in 2025, 64% of all bot attacks on the retail sector targeted API business logic.

These are not threats to be taken lightly. Modern bots imitate human behaviour (headless browsers, residential proxies, AI/cloud-driven automation) and can bypass many legacy defences.

Why holiday shopping season means a high return for cybercriminals

There are a few compounding factors that intensify the risk for retailers during peak season, making it easier for attackers to exploit traffic spikes and harder for security teams to keep up:

• Timing & value. As account histories build up (wish-lists, stored cards, loyalty points), the value of each account rises. Attackers know that e-commerce traffic surges around major events like Black Friday, Cyber Monday, and year-end deals.
• Promotion & checkout complexity. Retailers often deploy lots of new scripts or micro-services for promotions giving more surface area for bot abuse or skimming.
• Availability expectations. Customers expect 24/7 performance during peak season; disruptions (even small) risk damaging brand trust and revenue. A bot-driven DDoS or checkout-flow abuse during these days can have outsized impact.
• Compliance & customer data. With peak volumes, stored-card payments, cross-border activity and new flows, the risk of data breach or regulation (e.g., PCI-DSS, GDPR) becomes more acute.

What online retail security teams should prioritise now

1. Gain visibility into automated traffic

   You cannot protect what you cannot see. Modern bot behaviour includes leveraging headless browsers, residential proxy networks to mimic normal web traffic behaviors and AI has only served to increase the effectiveness of automated abuse making it easier for cyber criminals to repeat their abuse until they infiltrate their target. Ensure you have full visibility of your entire application and API infrastructure.

2. Prioritize high-value endpoints (login, APIs, checkout)

   Ensure your bot protection covers more than just the homepage. High-value targets such as Login pages and account flows, checkout APIs, and loyalty endpoints are prime targets for attack.

3. Protect customer accounts proactively

   Credential-stuffing and Account Takeover attacks will increase during peak shopping season. Traditional security measures such as good password hygiene and MFA are effective, but they are not enough for today’s AI-empowered attackers. True Account Takeover protection will immediately and accurately detect and block attacks at the edge. Always-on Account Takeover Protection will deter attackers by lowering their return on investment.

4. Secure APIs and microservices

   Retail platforms increasingly rely on APIs which is why an Advanced Bot Protection and Advanced API Security solution is recommended to offer full visibility of all your APIs and to ensure your most risky APIs are protected.

Peak-season eCommerce is a double-edged sword: while it presents huge revenue upside, the risk of bot-driven fraud, ATO and automation abuse is also at its highest. If you treat bot threats as an afterthought, you’re leaving the door wide open for attackers who already know your calendar, traffic patterns and the weakest links in your stack.

By integrating our full application security stack from Advanced Bot Protection and API security to Client-Side Protection and WAAP visibility, retailers shift from reactive detection to proactive prevention, turning the holiday surge into a secure growth opportunity instead of a season of risk.

Our application security suite delivers best-of-breed protection in a single platform, offering superior performance with lower latency, unified visibility through Attack Analytics to uncover coordinated campaigns, and with the backing of our world-class Threat Research team.

Learn more about our Application Security products today.

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