AI agents are not a future concern. They are already changing how enterprise systems are accessed, automated, and abused.
And the security implication is clear: the more autonomous systems rely on APIs, the more important it becomes to know exactly which APIs exist, how they are being used, and whether they are being misused.
If your organization cannot answer those questions, you have a visibility problem. And in an environment where AI can accelerate both legitimate automation and malicious abuse, visibility is the first step to control.
Risk accelerating
APIs have always been a target because they expose data and business logic. What has changed is pace.
AI can now help attackers discover endpoints faster, test more abuse paths, and automate attacks that once took much more effort. Meanwhile, AI agents inside the enterprise are generating more API traffic, often with broader privileges than anyone intended.
That means security teams are facing a harder problem: not just more traffic, but more uncertainty and adversaries with improved tools.
What CISOs should be worried about
The biggest risks are not always the loudest ones.
Whether it’s an over-permissioned agent, a forgotten or shadow API, or a “legitimate” request abused to enumerate data or chain unauthorized actions, the risk is real. It’s often compounded by API tokens with broad access and long expiration times.
These are the kinds of issues that can lead to evasive data exfiltration, unauthorized payments, compliance violations, and operational surprises that go undetected far too long.
If your API security program cannot spot abnormal behavior early, the business is exposed.
Continuously discover APIs across the environment.
Classify which ones are sensitive.
Establish baselines for normal behavior.
Detect abnormal or suspicious API activity.
Support least-privilege access for AI agents.
Help revoke risky permissions quickly.
This is how security leaders turn AI agent activity from a blind spot into something measurable and governable.
The board conversation has changed
This is no longer just a technical issue for engineering or operations.
Boards care about risk, control, and business impact. They need to know how many AI agent-facing APIs are being monitored, how many anomalous calls have been detected, and how quickly the business can respond when something looks wrong.
That is the real opportunity for CISOs: to move API security into the center of the AI risk conversation.
Download the guide now
For CISOs, security leaders, and executives, this guide explains the new API security realities emerging with AI agents. We created A CISO’s Guide to API Security in the Age of AI Agentsto help you navigate the shift with clarity and confidence.
Inside, you will learn:
Why AI agents are increasing API risk rather than replacing it.
How to connect API security to business and board-level concerns.
What to look for in a practical CISO playbook for discovery, visibility, and control.
How to govern agent-driven access before it becomes business exposure.
AI agents may change how work gets done. But the organizations that understand their APIs first will be the ones best positioned to stay in control.
A five-level operating model for turning API security visibility into measurable risk reduction, faster remediation, and confident digital growth — without slowing development.
What is API security operationalization?
API security operationalization is the process of converting API discovery and visibility into continuous, measurable risk reduction across discovery, vulnerability identification, prioritization, mitigation, and scaling. It moves API security from a one-time assessment to a repeatable, outcome-driven program, with KPIs such as mean time to remediation (MTTR), high-risk API count, and exposed endpoint reduction.
Operationalization matters because APIs are the fastest-growing attack surface — and most organizations now have visibility into their APIs but cannot act on it consistently. Without operationalization, discovery becomes a catalog instead of a control.
Why most API security programs stall after discovery
Most organizations aren’t struggling to see their APIs anymore. They’re struggling to turn API security visibility into consistent, measurable outcomes. According to the OWASP API Security Top 10, the most damaging API risks — broken object-level authorization (BOLA), broken authentication, and unrestricted resource consumption — all exploit gaps that exist after discovery, not before it.
APIs are the fastest growing attack surface — Imperva research shows API-directed attacks now account for a meaningful share of the application threat landscape (see the 2025 Imperva Bad Bot Report for current bot-driven API abuse data). Yet many security programs stall after discovery: risks are identified but not prioritized. Findings are reported but not operationalized. Controls exist, but don’t scale.
Imperva API Security closes that gap.
It enables organizations to move beyond insight and into action, so API security becomes a repeatable, outcome-driven capability that reduces real risk, improves efficiency, and supports faster innovation.
Here’s how to operationalize it for impact.
Figure 1: The Imperva API Security operational maturity model — five levels from Discover to Optimize.
Level 1: API discovery and classification
Building a complete, continuously updated inventory of every API
API discovery is the continuous process of identifying every API endpoint — managed, unmanaged, shadow, and deprecated — across cloud, on-premises, and hybrid environments, then classifying each one by data sensitivity and business criticality.
You can’t secure what you don’t fully understand, and classifying APIs by data sensitivity helps reduce the scope to a more manageable set. In dynamic environments, APIs are constantly changing, new ones spin up, old ones linger, and many remain undocumented.
Operationalization starts with continuous, accurate discovery and classification:
Identify every API across cloud, on-premises, and hybrid environments — including REST, GraphQL, gRPC, and SOAP endpoints
Uncover shadow APIs, unmanaged endpoints, and deprecated/zombie APIs that bypass change-management controls
Classify APIs by data sensitivity (PII, PHI, PCI, financial), business criticality, and external exposure
Map authentication posture — which endpoints require auth, which use long-lived tokens, which are publicly accessible without auth
How Imperva delivers:
Imperva API Security provides deep, continuous visibility into your API ecosystem, helping you uncover hidden APIs and automatically build a risk-aware inventory. This gives you not just a list of APIs, but the context needed to act on them.
Outcome: Reduced API attack surface, an inventory you trust, and the foundation every later level depends on. Without trustworthy discovery, prioritization is guesswork.
Level 2: Identifying API vulnerabilities and business-logic abuse
Expose real-world risk, not just theoretical issues
Modern API attacks don’t rely on obvious exploits. They leverage legitimate access in unintended ways — abusing business logic, over-permissioned tokens, and weak authorization. The OWASP API Security Top 10 ranks broken object-level authorization (BOLA) as the #1 API risk: an authenticated user manipulates an object identifier (user ID, account ID, document ID) to access another user’s data the API never intended to expose. Unlike SQL injection, BOLA produces no malformed payloads — every request looks legitimate.
To operationalize security, you need to detect:
Broken object-level authorization (BOLA, OWASP API1:2023) and access-control gaps that grant cross-tenant data access
Excessive data exposure (OWASP API3:2023) — endpoints returning more fields than the client needs
Anomalous usage patterns and behavioral risks (account-takeover, scraping, slow-rate enumeration)
Business-logic abuse — checkout, refund, and gift-card workflows weaponized by legitimate-looking calls
Risky tokens — long-lived credentials, over-permissioned API keys, leaked secrets in client code
How Imperva delivers:
Imperva analyzes API traffic and behavior to surface context-rich risk signals, so you can see not just what’s vulnerable, but how it can be exploited in practice.
Outcome: Shift from static findings to actionable intelligence aligned with real attack paths.
Level 3: Risk-based API prioritization (cutting through alert noise)
Focus on what actually matters to the business
Not all API risks are equal and treating them that way slows teams down.
Operational maturity comes from risk-based prioritization:
Which APIs are business-critical? — handle revenue-generating workflows, customer authentication, or core data
Which expose sensitive data? — return PII, PHI, payment data, or trade secrets
Which are externally accessible? — reachable from the public internet, partner networks, or third-party integrations
What is the real-world impact if exploited? — regulatory penalty, customer trust loss, downtime cost, blast radius
How Imperva delivers:
Imperva brings together visibility, behavioral insight, and business context to help teams focus on the highest-impact risks first, cutting through noise and enabling faster, smarter decisions.
Outcome: Align security effort with business risk, not alert volume.
Level 4: API risk mitigation and measurable outcomes (KPIs that matter)
Turn insight into action, and prove it’s working
Security only delivers value when risk is actively reduced, and that reduction is measurable.
Mitigation should be paired with clear KPIs:
High-risk API count — number of APIs flagged as critical-severity, month over month (direct measure of attack-surface reduction)
Mean time to remediate (MTTR) — days from detection of an API risk to closure (proxy for security engineering velocity)
Exposed/unmanaged endpoint count — public APIs without owner, doc, or auth control (catches drift between deploys)
Protection coverage — % of high-risk APIs with active mitigation policies (shows control density across the surface)
Inline-action rate — % of detected abuse stopped at session level (vs. IP block); differentiator vs. coarse-grained tools
How Imperva delivers:
Imperva enables teams to detect and respond to malicious or risky API activity with precision, using inline actions at the client session level to stop abuse in real time, far more effective than coarse IP-based blocking. This turns API security into a measurable, outcome-driven function.
Outcome: Demonstrate real risk reduction and tangible ROI.
Level 5: Scaling API security through automation and DevOps integration
Embed API security into how your business operates
Manual processes don’t scale in modern API environments. Optimization is about making API security continuous, automated, and integrated.
This means:
Automating API discovery and risk assessment so every new endpoint is inventoried within minutes of deployment
Embedding API security into CI/CD pipelines — schema validation, OWASP-scoped tests, and policy-as-code at PR time
Integrating with the broader stack — SIEM, SOAR, ticketing, IAM, and the Imperva Web Application and API Protection (WAAP) platform
Repeatable remediation playbooks mapped to API risk class (BOLA, broken auth, excessive data exposure, business-logic abuse)
How Imperva delivers:
Imperva helps operationalize API security at scale, reducing manual effort while improving consistency and coverage. It enables security teams to keep pace with development without becoming a bottleneck.
Outcome: Scale protection without scaling complexity.
The right + left operating model: balancing protection and enablement
Sustainable API security is not just about stronger controls. It’s about balance.
Right (Protection): Visibility, detection, and enforcement to reduce risk
Left (Enablement): Automation, scalability, and efficiency to support speed
Too much focus on protection slows the business. Too much focus on speed increases exposure.
Imperva API Security brings both together.
Right + Left = Optimum—where security doesn’t compete with the business; it accelerates it.
Figure 2: Building a Sustainable Strategy – Right + Left = Optimum
Conclusion: Make API Security a Business Enabler
The difference between having API security and operationalizing it is the difference between insight and impact.
With Imperva API Security, organizations can:
Continuously discover and understand their API landscape
Identify and contextualize real-world risks
Prioritize based on business impact
Mitigate and measure outcomes
Scale security through automation and integration
The result is not just better security.
It’s faster innovation, stronger resilience, and confident digital growth.
If your API security program is stuck at visibility, it’s time to take the next step.
Operationalize it. Measure it. Scale it.
See how Imperva API Security can help you turn API security into a strategic advantage,
and start driving real business value from day one.
Frequently asked questions about API security operationalization
What’s the difference between API security and API security operationalization?
API security is the set of controls that protect APIs from abuse. API security operationalization is the practice of running those controls as a continuous, measurable program — with discovery, prioritization, KPIs, and automation rather than one-time scans.
What are the most common API vulnerabilities?
The OWASP API Security Top 10 (2023 edition) ranks broken object-level authorization (BOLA), broken authentication, broken object-property-level authorization, unrestricted resource consumption, and broken function-level authorization as the highest-impact API risks. Most modern attacks combine two or more of these.
How is API discovery different from API documentation?
API documentation describes what an API is supposed to do. API discovery finds every API that actually exists in your environment — including shadow, deprecated, and undocumented endpoints that documentation misses. Operationalized programs treat discovery as continuous, not one-time.
How do you measure API security effectiveness?
Track high-risk API count, mean time to remediate (MTTR), exposed/unmanaged endpoint count, protection coverage, and inline-action rate. KPI movement over time is the proof that the program — not just the toolset — is working.
Does Imperva API Security work with my existing WAF or WAAP?
Yes. Imperva API Security is part of the Imperva Web Application and API Protection (WAAP) platform and integrates with Imperva WAF, the Imperva CDN, and third-party SIEM/SOAR tooling. The same operational model spans web app and API protection.
For decades, companies have operated on a simple assumption that most internet traffic came from people. That assumption no longer holds.
The latest 2026 Bad Bot Report: Bad Bots in the Agentic Age reinforces a shift that is now impossible to ignore. Automated traffic continues to outpace human activity online, accounting for more than 53% of all web traffic in 2025, up from 51% the year before. Human activity has declined to just 47% and continues to fall.
This is not a short-term spike driven by a specific attack cycle or technology trend. It reflects a structural change in how the internet operates. Increasingly, businesses are not serving customers alone. They are serving machines.
Key Findings From the 2026 Bad Bot Report
Bots now drive 53% of web traffic. Automated activity has officially overtaken humans online, up from 51% in 2024.
27% of bot attacks target APIs. Attackers are bypassing user interfaces entirely to operate directly at machine speed.
Financial services bear the brunt. The sector accounted for 24% of all bot attacks and 46% of account takeover incidents.
AI agents are a new category of internet participant. They no longer just scan websites; they retrieve data, execute workflows, and act on behalf of users.
AI Agents and Bots Are Becoming the Default Internet User
Automation has always existed on the internet in the form of search engine crawlers, scripts, and background processes. What has changed is the scale, sophistication, and purpose of that automation.
AI is accelerating this shift. AI-driven bots have surged dramatically, but more importantly, AI agents are now emerging as a new category of internet participant. These systems don’t just scan websites; they interact with them, retrieve data, execute workflows, and increasingly act on behalf of users.
In practice, this means that what looks like a customer interaction may not be a customer at all. It may be an AI system querying pricing data, completing a transaction, or testing application behavior. For businesses, this blurs a fundamental line. The distinction between legitimate and malicious traffic is becoming harder to define, because both now operate through the same systems, use the same interfaces, and follow the same logic.
The real risk is not the presence of bots, but that much of this automation is unmanaged. In earlier phases of the internet, bot activity was episodic and often easier to identify. Today, automation is persistent. It operates continuously across digital services, often indistinguishable from legitimate use. This creates a new category of risk that many organizations are not yet equipped to handle. Uncontrolled automation can distort business metrics, inflate infrastructure costs, degrade performance, and expose sensitive workflows.
For example, bots can continuously query pricing or availability systems, creating artificial demand signals. They can interact with promotional systems at scale, exploiting business logic in ways that traditional security controls are not designed to detect. Even benign automation, when left unmanaged, can place sustained load on systems that were designed for human behavior.
The result is that companies are increasingly sharing their digital infrastructure with automated agents that they neither fully understand nor control.
APIs and Identity Systems Sit at the Center of Modern Risk
As automation evolves, so do attacker strategies. The traditional model of targeting websites at the surface level is giving way to a more direct approach.
Bots are increasingly interacting with the same APIs that power core business functions, including authentication, payments, search, and inventory systems. In 2025, 27% of bot attacks targeted API endpoints, allowing attackers to bypass user interfaces entirely and operate at machine speed. These interactions often appear legitimate, with well-formed requests and successful authentication, but the difference lies in intent and scale.
This is particularly visible in sectors where digital transactions are tightly linked to revenue. Financial services, for example, accounted for 24% of all bot attacks and 46% of account takeover incidents. The goal is not disruption for its own sake, but direct monetization.
In this environment, identity systems are no longer just a security layer. They are a primary point of exposure.
How AI Agents Are Quietly Rewriting Business Models
The shift toward machine-driven interaction is not only a security issue. It is beginning to reshape how businesses operate.
If a growing share of traffic is automated, then traditional metrics such as user engagement, conversion rates, and demand signals become harder to interpret. A spike in traffic may not indicate customer interest. A drop in performance may not be caused by user behavior.
At the same time, AI-driven systems are creating new forms of demand. Companies are beginning to consider how and whether to allow AI agents to access their services, and under what conditions. This raises questions about access control, pricing, and even monetization.
Some organizations are exploring models where AI-driven access is authenticated, measured, and potentially governed as a distinct channel. While still early, this points to a future in which businesses must actively manage not just who accesses their systems, but what.
From Bot Detection to Automation Control
For years, cybersecurity strategies have focused on detecting and blocking malicious activity. That approach is increasingly insufficient in a world where automation is both pervasive and often legitimate. The more important question is no longer whether traffic is automated, but whether it aligns with business intent.
This shift, from blocking bad bots to governing all automation based on intent, requires a new approach. Organizations must move from viewing bots as anomalies to viewing automation as a fundamental part of their operating environment. That means implementing controls that can distinguish between acceptable and harmful automation, applying governance to how systems are accessed, and designing defenses that can adapt as behavior changes.
In effect, the challenge is becoming one of control rather than detection.
A Machine-Driven Internet
The internet is entering a new phase that’s defined less by human interaction and more by machine-to-machine activity. Automation is no longer a layer on top of digital infrastructure but embedded within it, with significant implications for businesses. Trust, performance, and revenue are increasingly shaped by how well organizations manage automated interaction.
Companies that continue to operate under the assumption that users are human risk misreading their own systems. Those that adapt by understanding, governing, and controlling automation will be better positioned to compete in an internet where machines are not just participants, but the majority.
The shift is already underway. The question for businesses is not whether it will happen, but how they will respond.
The Imperva Bad Bot Report is an annual industry research report analyzing global automated bot traffic, attack trends, and the impact of malicious bots on websites, APIs, and applications. The 2026 edition focuses on the rise of AI agents and agentic automation.
How much of internet traffic is bots in 2025?
According to Imperva’s 2026 Bad Bot Report, automated bot traffic accounted for more than 53% of all web traffic in 2025, up from 51% the year before. Human traffic has fallen to 47% and continues to decline.
Why are AI agents a cybersecurity concern?
AI agents act on behalf of users, retrieving data, executing workflows, and completing transactions through the same interfaces as humans. This blurs the line between legitimate and malicious traffic, makes traditional bot detection insufficient, and exposes APIs and identity systems to automation that organizations cannot easily distinguish from real users.
Which industries are most affected by bot attacks?
Financial services experience the highest impact, accounting for 24% of all bot attacks and 46% of account takeover incidents in 2025. APIs are the dominant attack surface, with 27% of bot attacks targeting API endpoints across all industries.
When evaluating cloud security platforms, one question comes up again and again:
“How many Points of Presence do you have?”
At first glance, the logic seems sound. More locations should mean lower latency, faster response times, and better protection. The assumption is simple: if security is delivered at the edge, then more edge locations must automatically translate into stronger application security.
That assumption, however, is largely inherited from the content delivery world — and it does not hold up when applied to real‑time application and API protection.
The Common Assumption: More PoPs Means Better Security
In content delivery networks (CDNs), PoP count is a meaningful metric. Static content benefits directly from being cached as close as possible to end users. The more locations you have, the more likely content can be served locally, reducing latency and improving page load times.
Application security operates under a very different set of constraints.
Web Application and API Protection (WAAP) platforms are not simply delivering content. They must inspect every request, enforce security policies, analyze behavior, detect abuse, and mitigate attacks in real time — all while maintaining visibility across global traffic flows.
In this context, proximity alone is not the primary driver of security effectiveness.
Not All PoPs Are Created Equal
A Point of Presence is a physical location where traffic is processed — but PoPs vary widely in capability.
Some platforms emphasize deploying a very large number of small, highly distributed PoPs optimized for caching and proximity. Others prioritize fewer, high‑capacity PoPs placed at major internet exchange points and backbone hubs.
These high‑connectivity locations sit directly on global networks, allowing traffic to reach them efficiently from broad geographic regions. In practice, users are often only a few milliseconds away from a well‑connected PoP, even if it is not located in the same city or country.
For security workloads, network connectivity, inspection depth, and capacity matter far more than raw geographic density.
Anycast Routing Changes the Equation
Modern security platforms rely on Anycast routing, which automatically directs traffic to the optimal PoP based on real‑time network conditions rather than simple physical distance.
With Anycast routing:
Traffic follows the most efficient network path
Performance remains consistent even during outages
Failover happens automatically without user intervention
A well‑architected Anycast network can deliver predictable performance and resilience without requiring a PoP in every location where users reside.
Security Is Not the Same as Content Delivery
The most important distinction to understand is this:
CDNs scale by distributing copies of static content.
Security platforms scale by performing stateful inspection and coordinated decision‑making on live traffic.
Security inspection is computationally intensive and context‑dependent. Every request must be evaluated against behavioral models, threat intelligence, and policy logic. This work is fundamentally different from serving cached files.
As PoP counts increase, security platforms must make architectural trade‑offs around:
How much inspection can be performed locally
How much capacity is available per location
How security intelligence is synchronized globally
How attacks spanning regions are detected and mitigated
These trade‑offs define security outcomes far more than the number of locations alone.
What “Security in Every PoP” Really Means
Some modern platforms advertise that they run security services in every PoP, enabling them to deliver cached content and secure application traffic in the same location.
This approach offers clear advantages for latency‑sensitive use cases and environments where performance and security must be tightly coupled at the edge.
However, delivering security everywhere requires security capabilities to be highly distributed and lightweight by design. As PoP counts grow into the hundreds or thousands, platforms must balance:
Inspection depth versus per‑location footprint
Local decision‑making versus global coordination
Uniformity of protection versus operational complexity
In practice, “security in every PoP” often prioritizes speed and proximity over inspection depth, per‑location capacity, and attack absorption strength. While this model performs well under normal traffic conditions, it does not inherently guarantee stronger protection during large, sustained, or highly coordinated attacks.
Concentrated Capacity vs. Distributed Presence
Highly distributed security architectures excel at minimizing latency and handling everyday traffic efficiently.
Security‑first architectures, by contrast, are designed to concentrate capacity, intelligence, and mitigation power at strategically connected locations.
This concentration enables:
Immediate absorption of large volumetric attacks without traffic redirection
Deep, stateful inspection even under extreme load
Faster detection of coordinated attack patterns
Predictable performance during worst‑case scenarios
For application and API security, the most critical moments are not normal operations, but peak attack conditions. It is during these moments that per‑PoP capacity and global visibility matter more than sheer geographic density.
When PoP Density Does Matter
PoP count does play an important role in specific scenarios:
Global delivery of static content
Ultra‑low‑latency applications such as gaming or live streaming
Environments heavily reliant on edge caching
Many enterprises address this by separating concerns — using one platform optimized for content delivery and another purpose‑built for inline application and API security.
Architecture Over Optics
PoP count makes for an impressive slide, but it does not tell the full story.
The true measure of an application security platform lies in its network design, routing intelligence, inspection depth, per‑location capacity, and ability to perform under attack — not in how many dots appear on a map.
Some platforms optimize for being everywhere.
Others optimize for being strong where it matters most.
PoP count measures proximity.
Security performance measures resilience.
In application security, architecture — not optics — determines outcomes.
In today’s dynamic digital environment, the pressure to innovate has never been greater. Development teams are pushing for native cloud tools to maximize performance and cost-efficiency, while security teams require best-of-breed, enterprise-grade protection to defend against an ever-evolving threat landscape. This often creates a point of friction, forcing organizations into a difficult trade-off: sacrifice performance for security, or accept weaker protections for the sake of speed.
To resolve this challenge, Thales Imperva is collaborating with Google Cloud to deliver a solution that helps bridge this gap. We are proud to introduce Imperva for Google Cloud (IGC), an integrated security solution that offers the best of both worlds: enterprise-grade application security with the cloud-native performance you expect from Google Cloud.
Imperva for Google Cloud: A Holistic, Integrated Solution
Imperva for Google Cloud is not just another security layer; it is a fully managed, best-in-class Web Application and API Protection (WAAP) solution built directly into the fabric of Google Cloud. This integration, available now on Google Cloud Marketplace, provides robust protection without disrupting your existing infrastructure or workflows.
Cloud-Native Performance Without Compromise: Imperva for Google Cloud uses Google Cloud’s native Service Extension and Private Service Connect to inspect traffic within the Google Cloud network. This means all traffic analysis happens without your data ever leaving Google Cloud infrastructure, preserving optimal latency, performance, and data residency.
Quick Deployment: Forget complex re-architecture. Imperva for Google Cloud can be deployed quickly using familiar tools like Terraform, Google Cloud CLI (gCloud CLI), or the Google Cloud console UI. There are no disruptive DNS, SSL, or network routing changes required, allowing you to achieve production-ready protection almost immediately.
Enterprise-Grade Protection Out of the Box: Imperva for Google Cloud is powered by Imperva’s industry-leading security engine, delivering comprehensive WAF, advanced API Security, and Account Bot Protection. Backed by 24/7 threat research, the Imperva solution provides near-zero false positives, with 97% of customers successfully using default policies and 95% running in blocking mode from day one. This dramatically reduces the operational overhead of constant rule tuning.
Real-World Impact: Securely Accelerating Your Business
By eliminating the trade-offs between security and performance, Imperva for Google Cloud helps organizations achieve key business outcomes:
Accelerate Lift-and-Shift Migrations: Migrate workloads to Google Cloud confidently with security that adapts to your applications, not the other way around. Eliminate migration delays caused by complex security re-architecture.
Unleash DevOps-Friendly Security: Empower development teams to innovate at speed. IGC closes the security gaps in built-in tools without slowing down deployment velocity or requiring developers to become security experts.
Protect Modern Cloud-Native Applications: Secure your Kubernetes and microservices architectures with best-in-class defenses optimized for low-latency environments.
Achieve Unified Multi-Cloud Governance: Manage security for all your Imperva-protected environments from a single, unified dashboard, providing consistent policy management and visibility across your entire multi-cloud estate.
“Bringing Thales Imperva to Google Cloud Marketplace will help customers quickly deploy, manage, and grow the company’s integrated security solution on Google Cloud’s trusted, global infrastructure,” said Dai Vu, Managing Director, Marketplace & ISV GTM Programs at Google Cloud. “Thales can now securely scale and support organizations that want to use its Imperva for Google Cloud solution to increase protection for their cloud-native applications, APIs, microservices and more.”
Join Us on the Journey to More Seamless Cloud Security
As we approach key industry events like our exclusive Executive Briefing Center (EBC) meeting in late March and Google Cloud Next 2026 in April, the conversation around integrated security has never been more relevant. The launch of Imperva for Google Cloud marks a pivotal moment in our relationship with Google, providing a clear path for customers to secure their digital assets without compromise.
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.
For years, a lot of risky APIs survived simply because they were hard to find. They weren’t documented. Only a handful of engineers knew the endpoints. And if an attacker wanted to abuse them, they had to spend real time reverse‑engineering traffic and guessing how things worked.
That “security by obscurity” was never a security strategy, but it did create friction.
AI removes that friction.
Today, coding assistants and agentic tools can observe patterns in traffic, infer undocumented endpoints, generate proof‑of‑concept exploits, and test thousands of permutations faster than any human. We’ve already seen what happens when exposed APIs meet automation at scale: a hobbyist was able to gain control of thousands of robot vacuums due to exposed APIs and an over‑privileged token, something that simply wouldn’t have scaled without automation on the attacker side.
The takeaway is straightforward: if you don’t know where your APIs are, what they expose, and who can talk to them, AI will find those gaps for you, either in the hands of your developers or your attackers.
Why has API security become critical in the age of AI agents?
API security is the foundation of protecting applications against automated, AI-driven threats. In the past, attackers relied on manual reverse-engineering to discover undocumented API endpoints. Today, AI agents and coding assistants can autonomously map traffic patterns, infer hidden endpoints, and test thousands of exploit permutations in seconds. Furthermore, AI agents can bypass traditional web application firewalls (WAFs) by executing perfectly formatted, syntactically correct requests that abuse business logic—such as chaining legitimate calls to perform a Broken Object Level Authorization (BOLA) attack.
Because AI agents use APIs as their primary control plane, securing these interfaces is no longer just about preventing data breaches; it is about establishing the necessary guardrails to ensure AI tools operate safely and within their intended scope.
How AI Agents Change the Threat Model
AI doesn’t just make attackers faster. It changes what “attack” looks like, because agents can behave like normal users while still doing abnormal things.
1) Business Logic is the New Frontline
Traditional API protections – gateways, WAFs, basic input validation, are good at stopping obviously bad traffic: missing tokens, malformed payloads, suspicious content types.
But agents don’t have to look suspicious. They can follow every syntactic rule and still abuse your business logic.
Imagine an agent that:
Uses a valid user token and calmly walks the edges of a pricing API until it discovers discount combinations you never intended to allow.
Chains perfectly legitimate calls to pivot from one customer data to another customer’s data. This effectively executes a Broken Object Level Authorization (BOLA) attack – a critical vulnerability highlighted in the OWASP API Security Top 10 – without brute‑forcing raw IDs.
Nothing in those requests’ screams “attack.” The danger is in the sequence, the intent, and the scale, the exact things many baseline controls don’t reason about.
2) Agent-Specific Protocols Expand the Attack Surface
Agents aren’t only calling the same APIs as your mobile app calls. They’re increasingly using agent‑first toolchains and protocols that wrap platforms behind “tool” interfaces, making discovery and invocation easier than ever.
Look at what’s happening across major SaaS ecosystems: new CLIs and frameworks are designed so an agent can discover capabilities, understand schemas, and call dozens of APIs through a single control surface. Under the hood it’s still JSON over HTTP but packaged in protocols and workflows many security tools don’t meaningfully parse or recognize.
If your security stack doesn’t understand what it’s looking at, it can’t apply real policy. It just sees “some JSON” and hopes for the best.
The Thales Vision: API Security as the AI Agents’ Control Plane
At Thales, we see API Security evolving into the control plane for AI agents: the place where you get a coherent view of what agents are doing, which APIs they’re touching, and how to govern that behavior, consistently and at scale.
1) Start with ruthless visibility
You can’t protect what you can’t see, and AI moves too fast for spreadsheets and tribal knowledge.
We’re focused on:
Finding every API: Discovering shadow, zombie, and newly created APIs across clouds and data centers, then mapping the data they expose and the business functions they support.
Making agent traffic visible: Identifying traffic that comes from agents and agent toolchains, tying it back to the human or system they’re acting for, and surfacing suspicious patterns early.
The goal: when your CISO asks, “Which agents can touch customer PII today?” you can answer with confidence instead of guesswork.
2) Speak the same language as AI agents
We’re extending the API Security engine, so it doesn’t just see “JSON over HTTP ” but understands the agent protocols layered on top, things like MCP (Model Context Protocol) style streams and backend API calls from an agent-oriented CLI.
Once we can parse and normalize that traffic, we can:
Apply the same validation and anomaly detection we already use for REST and GraphQL.
Correlate what an agent is doing across back‑end services, rather than treating every request as an isolated event.
In practice, that means the security brain becomes protocol‑aware. Whether an action comes from a mobile app, a browser, or an AI agent using a modern toolchain, the same set of eyes is watching.
3) Put real guardrails around tokens and delegation
Agents run on delegation. They act on behalf of users and services using tokens, keys, and temporary credentials. When those credentials are over‑privileged or long‑lived, you get “quiet catastrophe” scenarios, like a single token shared among thousands of agents.
We’re building on our existing token visibility to:
Score token risk: Evaluate scope, lifetime, usage patterns, and anomalies like sudden geography changes or volume spikes.
Create policies specifically for agent delegation: For example, “This support agent’s token can only read billing data for the current customer, up to N requests per hour, and never export full datasets.”
Catch replay and abuse: Detect when tokens are cloned, reused from odd locations, or used by unexpected agent identities.
If an AI agent starts stretching beyond the intent of its access, querying too broadly, too often, or in the wrong context, the platform should be able to flag, throttle, or cut it off in real time.
4) Defend the messy middle: business logic and BOLA
Agents follow natural‑language prompts, not carefully designed UI flows. That makes them unusually good at stumbling into the “negative space” of your application: edge paths nobody documented, but your back end still accepts.
Our approach anchors security in behavior and intent:
Model sequences of calls as workflows and look for patterns that don’t match real user behavior, for example, moving from one customer account to another without a corresponding permission to change.
Treat BOLA as more than “did you increment an ID,” and start reasoning about what resource the agent is effectively asking for when it requests “all internal reports” or “all projects in the system.”
The endgame is business‑level guardrails you can express clearly, and enforce across all agents, regardless of how clever the prompts are.
Meeting you where you already are
None of this works if it requires an exotic, parallel deployment just for AI. That’s why we’re embedding agent controls into the places customers already rely on Imperva today:
Imperva WAF Gateway for on-prem and hybrid environment
Imperva eWAF for cloud-native and microservices workloads
In each case, it’s the same security engine doing heavy lifting, discovering APIs, understanding protocols, analyzing behavior, and enforcing policy inline on every agent’s call.
Where we’re heading
AI agents are already inside organizations, helping engineers, answering customers, and automating operations. The real question is whether they’re operating inside guardrails you actually understand.
Our view is simple:
You don’t secure AI by bolting something onto the model.
You secure AI by controlling the APIs and data the model can reach.
By turning API Security into the shared control plane for AI agents, across discovery, protocol understanding, token governance, and business‑logic protection, we want to help teams say “yes” to AI without crossing their fingers behind their back.
If you can see every agent, every call, and every token, you can turn AI from a wild card into an engineered advantage. That’s the future we’re building toward.
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.
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.
Most organisations assume DDoS (Distributed denial of service) protection is a box they’ve already ticked. If traffic spikes or an attack starts, the thinking goes, their provider will absorb it and move on.
But in the real world it can be a different story. Many incidents aren’t caused by the scale of an attack alone, they happen because their protection isn’t designed to act fast enough, distinguish legitimate traffic or stay active without disruption for normal traffic. Or slows the legitimate traffic down, degrading performance when under an attack.
In this blog, we look at why DDoS resilience is really about continuity, not just mitigation, and what teams often miss when they assume they’re already protected.
The DDoS Protection Gap: Why Performance Breaks Under Pressure.
Modern DDoS attacks rarely look like blunt floods now; they utilize multi-vector strategies targeting the application layer (Layer 7) to blend in. They overwhelm specific application paths or quietly degrade performance until frustrated users give up.
When protection isn’t built to handle this kind of attack, organisations often see:
Delays between detection and mitigation
Legitimate users are blocked or challenged during peak moments
Performance degradation that’s dismissed as ‘normal slowing’
Downtime that occurs despite having DDoS controls in place
The result is widespread impact, disrupting not just infrastructure, but revenue, brand reputation and most importantly, trust.
Why Modern DDoS Protection is a BusinessContinuity Challenge
Effective DDoS protection isn’t about surviving the largest possible attack on paper. It’s about ensuring users can continue to access applications, complete transactions and rely on important services, even when an attack is ongoing.
To do that organisations need protection that is:
Not dependent on manual activation
Fast, with mitigation measured in seconds, not minutes or hours
Accurate, so legitimate users aren’t caught in the crossfire
Edge-based mitigation using a global Anycast network, stopping attacks before they put internal systems under pressure
Without these characteristics, DDoS defences can become part of the problem rather than the solution.
The Oversight: What Security Teams Miss About Resilience
Many organisations unknowingly accept risk because they:
Assume any DDoS protection will do the job
Focus on volumetric capacity but overlook detection accuracy, time to mitigate, mitigation efficacy and stealth attacks to the application layer
Rely on reactive or hybrid approaches that leave a mitigation gap
Accept user friction as an acceptable side effect of defence activity
Accept operational complexity as “the nature of the beast”
Often, these gaps only become visible during critical moments such as launches, seasonal peaks or high-traffic events, when resilience matters most.
The Solution: Supporting Continuity with Always-On Mitigation
Thales’s Imperva DDoS Protection is designed to preserve availability and user experience, even during sustained or sophisticated attacks.
Behind the scenes, this means:
Continuous and detailed profiling of peace-time traffic for fast identification of anomalies and potential DDoS attacks.
Always- on mitigation at the edge, eliminating delays in response with an industry-leading 3–second time-to-mitigation SLA for network-layer attacks.
Versatile set of techniques for minimising disruption to legitimate users, including signatures, behavioural patterns and challenges.
Attack isolation for avoiding potential collateral damage.
Global scale and distribution, absorbing attacks close to the source.
The Impact: Why True Resilience Matters for Revenue
DDoS attacks don’t just test security controls; they test business resilience. When protection fails, the impact is immediate, abandoned sessions, lost transactions, frustrated customers and operational pressure at exactly the wrong moment.
DDoS resilience isn’t defined by how large an attack you can withstand, but by how consistently your services remain available while it’s happening.
By aligning always-on mitigation, rapid response and accurate traffic, classification, organisations can reduce risk without compromising user experience and ensure that availability isn’t dependent on perfect timing or manual intervention.
Because the true test of DDoS protection is whether services remain available.
To discuss DDoS protection with a member of the team, get in touch.
Since the headline-grabbing outages of 2021, we’ve had recurring conversations with large enterprises asking some version of the same question.
Do we really want our CDN, security, and routing control to live in the same place?
This issue of control has become more urgent after a series of well‑publicized, multi‑hour outages across major cloud‑based DDoS protection and security platforms. These incidents are rare but appear to be increasing in frequency. And when they happen, they expose architectural decisions many organisations haven’t revisited in years. The fact is that architectures assumed providers would never fail. Reality proved them wrong.
The concern isn’t whether cloud DDoS mitigation works. At scale, it does. The issue is control: whether customers retain the ability to reroute traffic independently if the provider itself goes down.
Many DDoS protection services simplify onboarding by originating customer prefixes and returning traffic via static paths. Under normal conditions, this works. During a provider outage, especially one affecting routing or orchestration, customers may lose the ability to reroute traffic
independently. Recovery depends on provider‑side changes at the worst possible moment.
That’s when a DDoS mitigation service can become a single point of failure.
Protection and control are different problems
One thing we consistently hear from network and security teams is that DDoS attack mitigation and traffic control are often treated as the same problem. They aren’t.
Resilient architectures separate them:
Function
Who Should Control It
Attack mitigation
DDoS provider
Traffic routing decisions
Customer network
The Internet already provides a mechanism to enforce this separation: the Border Gateway Protocol (BGP). This is the Internet’s routing protocol; it determines how traffic is directed between the networks.
So, the real question isn’t whether to use cloud‑based DDoS protection. It’s whether that protection operates with your routing policy, or instead of it.
Resilient architectures treat attack mitigation and traffic control as separate concerns. Providers absorb DDoS attacks. Customers retain routing authority using BGP, enabling them to decide how traffic flows during failures.
When customers control BGP, outages take on a different character. They become routing events, not service outages. Traffic can be redirected faster, the blast radius is reduced, and network teams respond using familiar controls instead of escalation paths.
Designing for the inevitable
No provider is immune to failure. CDNs, hyperscalers, and DDoS mitigation services all operate complex, global control planes.
Resilience doesn’t come from assuming outages won’t happen. It comes from designing so that when they do, customers still control the outcome.
That’s why more organizations are adopting architectures where:
DDoS protection is cloud‑delivered
Routing authority remains customer‑owned
BGP is the final decision layer for traffic steering
This approach preserves the benefits of cloud‑scale mitigation while avoiding the creation of new single points of failure.
A practical next step
If you’re rethinking your DDoS architecture, your best starting point isn’t a product demo; it’s an architectural review. Here are some questions to ask yourself:
Who originates your prefixes today?
How quickly can you reroute traffic if a provider is unavailable?
What dependencies exist between mitigation availability and network availability?
Those answers usually reveal more than any outage postmortem.
On the Internet, control of routing is control of availability, and we think that control should always remain in customer’s hands.
Want to discuss what customer‑controlled DDoS protection looks like in practice? Get in touch with Thales to review your architecture.
As APIs power the majority of modern web applications, implementing robust API security is no longer optional – it’s a critical necessity for data protection. This guide explores how to seamlessly integrate API gateway security into your Imperva on-premises environment to mitigate OWASP Top 10 threats, ensuring both web application and business logic threats are effectively managed.
The Need for API Security Integration
APIs not only enable communication between systems but also expose vulnerabilities that can be exploited by attackers. A strong API security solution safeguards your applications against threats ranging from SQL injections and cross-site scripting to more nuanced business logic attacks. With Imperva’s security capabilities integrated into your gateway, you benefit from:
Comprehensive API Protection: Defend against the OWASP API Top 10 risks, including BOLA and Broken Authentication, by stopping malicious traffic at the gateway.
Operational Simplicity: Leverages the powerful capabilities of the Imperva gateway without adding unnecessary complexity.
Flexibility and Scalability: Supports on-premises, cloud-native, and Kubernetes environments, adapting to your organization’s evolving needs.
Key Technical Aspects of the Integration
Dynamic Profiling and Application Insight
Imperva’s patented Dynamic Profiling technology is at the core of this integration. It automatically learns the structure and usage of your web applications by monitoring every URL, parameter, cookie, and HTTP method. This continuous learning process helps to:
Automatically Adjust Security Profiles: Minimal manual tuning is required as the system adapts to your application’s normal behavior.
Detect Anomalies: By comparing real-time data against expected usage models, the solution quickly identifies suspicious activities that could indicate an attack.
Protocol Validation and Attack Signatures
The integration offers a dual-layer defense strategy:
Protocol Validation: Every API request is checked to ensure compliance with HTTP protocol standards, filtering out malformed or malicious requests.
Attack Signatures: With a comprehensive database of over 6,500 attack signatures that are regularly updated by expert teams, the WAF GW swiftly identifies and blocks known threats.
Diagram: Imperva Security Layer Architecture – This diagram illustrates the layered approach of Imperva’s security, showing how protocol validation, signature matching, and dynamic profiling work together to secure API traffic.
Application Profiling and the Correlation Engine
Understanding your application’s normal behavior is key to spotting potential threats. By profiling real-time usage and employing a sophisticated correlation engine, the solution:
Detects Business Logic Attacks: Identifies vulnerabilities such as Broken Object Level Authorization (BOLA) and Broken Function Level Authorization (BFLA).
Enhances Threat Verification: Integrates data analysis with vertical integration to validate and remediate suspicious activities effectively.
Seamless Integration with Leading API Management Tools
Imperva’s API-Anywhere solution provides a gateway-agnostic approach, integrating leading tools like Kong API Gateway via a dedicated plugin. This gateway-agnostic approach ensures:
Selective Traffic Handling: Only validated, non-malicious traffic is forwarded to the API controller, maintaining optimal performance.
Automated API Discovery: The system continuously identifies, classifies, and monitors API endpoints, including deprecated and unauthenticated ones, reducing manual effort and accelerating the development cycle.
Flexibility in deployment is a key benefit of the Imperva API security solution. Whether your infrastructure is based on cloud-native technologies like Kubernetes or traditional hypervisors like VMware, integration is straightforward.
Generate the Installation Package:
Use the provided HELM chart to generate configuration files and prepare the console.
Impv-a-console-x.x.x.tgz (This Package includes the Helm Chart of the Console)
Values.yaml (This file contains the configuration)
Deploy the Console:
Install the console in your environment. This can be managed either via the Imperva Cloud Console or a local self-managed option.helm install impv-apisec-console -f values.yaml -n impv-anywhere –create-namespace
Enable the API-Security Policy on Your Gateways:
With the console active, enable the API security policy on your gateways. The gateway begins populating data to the Imperva Unified Management Console (UMC) either in the cloud or on premises, based on your configuration.
Ongoing API Discovery and Verification:
Continuous API discovery and Swagger file verification ensure that all endpoints are monitored, classified, and secured, significantly reducing the risk of overlooked vulnerabilities.
Benefits and Added Value
Integrating API security with the Imperva gateway delivers tangible benefits:
Streamlined Security Operations: Automated profiling and centralized management reduce the operational burden on your security teams.
Enhanced Developer Productivity: Automated API discovery and inventory management expedite the development cycle.
Robust Protection Across Environments: Whether your APIs are public-facing or internal, legacy or cloud-native, the solution offers comprehensive security without compromising performance.
Actionable Insights and Compliance: Gain granular visibility into traffic to support GDPR, PCI DSS, and HIPAA data governance and protect sensitive PII.
Conclusion
A robust API security strategy must be flexible, comprehensive, and easy to deploy. Imperva’s API-Anywhere solution integrated with your gateway environment meets these requirements by offering:
A Gateway Agnostic Security Solution: Seamlessly integrates with multiple API management tools.
Automated API Inventory and Protection: Continuously monitors and updates API endpoints, uncovering any shadow or deprecated APIs.
Dual-Level Threat Mitigation: Protects against both application-level and business logic attacks through dynamic profiling, protocol validation, and advanced correlation engines.
By integrating this solution, organizations can protect critical assets, streamline operations, and maintain high levels of security and compliance, all while enabling a faster, more agile development process.
We’re excited to announce the launch of Upload Scan and Control, an essential new feature for Imperva Cloud WAF. This add-on tackles one of the most critical vulnerabilities facing web applications today—insecure file uploads—offering protection with scalability, simplicity, and enterprise-grade control.
Why Secure File Upload Protection Is Critical for Modern Web Applications
File upload functionality is now a staple in web applications; from job portals accepting résumés to customer support platforms collecting documents.
Unfortunately, attackers exploit this functionality to inject malware, ransomware, and other malicious payloads into systems. This also can become the main source for remote code executions.
With Upload Scan and Control integrated into your Web Application Firewall (WAF), you’ll soon be able to enforce file size and type restrictions, blocking unauthorized or suspicious files before they enter your environment, ensuring your upload capabilities remain safe and compliant.
According to the OWASP Top Ten, insecure file uploads remain one of the most exploited web application vulnerabilities worldwide.
The Growing Risk of Malicious File Uploads
Across the Cloud WAF user base, we process over 20 million file uploads daily, with more than 800 customers across industries like finance, healthcare, retail, and government.
Cyber attackers are becoming more sophisticated and often target file uploads as an initial entry point. The earlier you can block malicious content, before it hits an endpoint or server, the greater your chances of preventing a breach entirely.
Endpoint antivirus and EDR tools play a critical role in detection, but they typically act after malicious files land on your system. At this stage, it may already be too late. Investigations take longer, the damage may already be done, and attackers may have gained a foothold.
Upload Scan and Control stops threats at the edge, before files are saved or executed, enabling true prevention over delayed remediation before they even reach your network layer.
Advantages of Imperva Upload Scan and Control for Cloud WAF
Our new feature delivers several enterprise-grade benefits:
Full visibility across all upload points: Identify which applications allow file uploads and monitor activity from a single dashboard.
Instant, one-click activation: Protect all current and future apps automatically, eliminating developer integration work.
Scalable security for large enterprises: No additional requirements for app owners or developers to introduce additional integrations significantly reducing operational overheads.
Peace of Mind for Security Leaders and Compliance Teams
With Upload Scan and Control, enterprises can:
Block threats at the edge before they reach your network.
Trace file origins and identify the responsible user or IP.
Maintain audit-ready compliance records (such as GDPR, CCPA, and HIPAA) without adding complexity to existing security stacks.
As cloud-native adoption accelerates and threat actors adapt, features like this are becoming essential to maintaining a secure, compliant perimeter.
Get Ready to Enable Upload Scan and Control
If you’re already using Imperva Cloud WAF today, check your Imperva console to see which apps you currently allow file uploads against and start protecting them today. Get in touch so you can activate Upload Scan and Control within your Cloud WAF environment or to schedule a demo, contact your Imperva account team.
In an era marked by escalating cyber threats and evolving risk landscapes, organisations face mounting pressure to strengthen their security posture whilst maintaining seamless user experiences. At Thales, we recognise that robust security must be foundational – embedded into products and services by design, not bolted on as an afterthought. This principle underpins our commitment to the U.S. Cybersecurity and Infrastructure Security Agency (CISA)’s Secure-by-Design pledge, which calls on software manufacturers to establish security features like multi-factor authentication (MFA) as standard across their product portfolios.
As digital transformation accelerates and attack surfaces expand, the gap between security capabilities and emerging threats continues to widen. According to the 2025 Thales Data Threat Report, organisations are grappling with unprecedented challenges: 69% regard the fast-moving ecosystem as the most concerning GenAI security risk, whilst 83% report that strong MFA is used more than 40% of the time. This indicates both progress and significant opportunity for improvement. These findings underscore a critical reality: whilst security tools and technologies have advanced, comprehensive deployment and consistent enforcement remain essential challenges that demand immediate attention.
This blog examines the pivotal role of multi-factor authentication in modern cybersecurity strategies. We explore the fundamentals of MFA, analyse the evolving threat landscape that necessitates its adoption, and provide practical guidance on implementation. Whether you are a security professional seeking to strengthen your organisation’s defences or an individual user looking to protect personal accounts, this resource offers the insights and actionable steps needed to embrace MFA with confidence and rigour.
Understanding Multi-Factor Authentication: The Basics
Multi-factor authentication verifies your identity using two different forms of identification. Typically this involves something you know (like a password) and something you have (like a code on your phone). Think of it like using an ATM: you need both your bank card and your PIN to withdraw cash.
This dual-layer approach creates a significant barrier for attackers. Even if someone steals your password, they still can’t log in without that second factor. It’s elegantly simple, yet remarkably powerful – your password alone is no longer enough to unlock the door.
The Growing Threat Landscape: Why MFA Is No Longer Optional
Cyberattacks have grown increasingly sophisticated, with stolen passwords at the heart of many breaches. According to the 2023 Verizon Data Breach Investigations Report, nearly 49% of data breaches involved the use of stolen credentials.
MFA directly addresses this vulnerability. Our own research at Thales demonstrates the critical importance of strong authentication measures. According to the 2025 Thales Data Threat Report, 83% of organisations report that strong MFA is used more than 40% of the time, yet significant challenges remain in achieving comprehensive deployment. This data underscores both the growing recognition of MFA’s importance and the continued need for organisations to strengthen their authentication posture.
Furthermore, our 2025 Digital Trust Index – Third-Party Edition reveals a concerning reality: 40% of users reset passwords once or twice a month, highlighting the inherent weakness of password-only authentication systems. These frequent password resets not only frustrate users but also create security vulnerabilities that MFA effectively mitigates.
How MFA Defeats Common Attack Methods
MFA thwarts the most prevalent attack techniques:
Brute-force and credential stuffing attacks: These automated attacks become practically futile with MFA enabled because guessing the password isn’t enough to break in.
Phishing attacks: Even if you unwittingly hand over your password to a phisher, they still can’t access your account without the one-time code or second factor that MFA requires.
It’s no surprise that CISA’s Secure-by-Design guidelines explicitly call for making MFA a built-in, default security feature. In today’s threat landscape, MFA has evolved from a nice-to-have extra to an essential safeguard.
Thales’ Commitment: Security by Design and by Default
At Thales, we build security into our products by design, baked into our products and services. Our commitment to CISA’s Secure-by-Design pledge is reflected in how we develop features like MFA.
We already implement robust MFA across our cloud services to help safeguard your accounts and data. By requiring two forms of identification to access the Thales Cloud Security Console, we add an extra layer of protection that makes it “much harder for unauthorised users to access sensitive information”. This significantly reduces the risk of breaches and builds trust.
The Principle of Shared Responsibility
Thales’ approach recognises shared responsibility. “Security by default” means we provide secure settings and features right out of the box. However, security is also a partnership – we provide the tools, whilst you play a crucial role by using them.
We’ve made MFA available and straightforward to configure, and we actively encourage customers to use advanced authentication methods. Whilst MFA might not be mandated on all accounts by default today, we strongly recommend that you activate it. By choosing to enable MFA now, you’re not only protecting yourself immediately but also aligning with best practices that Thales and the cybersecurity community advocate globally.
Getting Started: How to Set Up MFA
Enabling multi-factor authentication on your Thales account is quick and straightforward. Here’s how:
Log in and navigate to your user settings. Go to Account Settings or Profile, where you’ll find security settings for MFA management. You can find these options in the Thales Cloud Security Console setup checklist.
Locate the Multi-Factor Authentication option and click to begin setup.
Select your preferred MFA method: authenticator app, SMS, or email.
Configure the chosen method:
For an authenticator app, scan the displayed QR code with your app ( MobilPASS+, Google Authenticator, Microsoft Authenticator, Authy, etc.).
For SMS, enter your mobile number to receive a verification code.
For email, a code will be sent to your registered email address.
Save your backup codes. These are your safety net if you lose access to your MFA device. Store them in a secure location like a password manager.
Complete and test the setup. Once verified, MFA will be enabled. Log out and log in again to ensure everything works properly.
That’s it! You’ve added a powerful extra layer of security in just a few minutes.
Choosing Your MFA Method: A Comparison
For organisations seeking a comprehensive overview of authentication options, Thales offers an extensive portfolio of MFA tokens and authenticators. Our OneWelcome Authenticators Portfolio includes FIDO2 passkeys, hardware tokens, smart cards, and software authenticators, ensuring secure access across different environments and devices . This breadth of choice allows organisations to select the authentication method best suited to their security requirements and user needs
When setting up MFA, you have several authentication options:
Authenticator App (recommended): Generates a new 6-digit code every 30 seconds. This method is very secure, works offline, and is significantly more phishing-resistant. Pros: High security, no network dependency. Cons: Requires your phone.
Text Message (SMS): Sends a one-time code to your mobile phone. Pros: Easy to use, no app required. Cons: Slightly less secure than authenticator apps due to potential SIM-swapping attacks, but still greatly improves security over no MFA. CISA recommends SMS-based authentication only as a “last resort” when more secure options aren’t available
Email Codes: Sends verification codes to your registered email. Pros: No extra device needed. Cons: Least secure option if your email is compromised. Use only if other methods aren’t feasible, and ensure your email itself has MFA.
Hardware Security Keys: Physical devices, such as Thales FIDO Security Keys that you plug in or tap to verify login. Pros: Highest level of security, phishing-resistant. Cons: Requires purchasing a device.
Which should you choose? If possible, use an authenticator app or hardware key, as these are most secure. For most users, an authenticator app strikes an excellent balance. SMS is a solid fallback, and email can work if necessary – just be aware of the security trade-offs.
Whilst MFA significantly strengthens security, the most forward-thinking organisations are taking the next step: eliminating passwords altogether. Passwordless authentication removes the vulnerabilities inherent in password-based systems – no passwords to steal, phish, or reuse.
Thales’ SafeNet Trusted Access empowers organisations to build comprehensive passwordless policies using FIDO2 passkeys, biometrics, and hardware authenticators. Our Passwordless 360 approach provides a detailed framework for implementing passwordless authentication across your organisation, combining security, user experience, and regulatory compliance.
Troubleshooting and Frequently Asked Questions
Q: Do I have to enter an MFA code every single time I log in?
A: Often not every time. Many systems offer the option to “remember” a device for a certain period (e.g., 14 days). This means you won’t need to enter a code each time on that trusted device. However, use this feature only on personal devices you control, not shared or public computers.
Q: I’m not receiving the MFA code, or it says the code is wrong. What should I do?
A: Common solutions include: For SMS, check your signal and that your phone number is correct in account settings. Wait a moment and click “Resend code” if available. For authenticator apps, ensure your phone’s clock is accurate, as codes are time-based. For email, check your spam folder.
Q: What if I lose access to my phone or MFA device?
A: Use your saved backup codes to log in. If you’ve lost those as well, contact Thales support for account recovery assistance.
Q: Can we use our own IdP?
A: Yes, you can leverage external IdPs like SafeNet Trusted Access by Thales, which allows you to build adaptive authentication policies and leverage a broad range of MFA options.
Q: Can I switch MFA methods?
A: Yes. You can disable MFA and re-enable it with a new method anytime through your account settings.
Q: Is MFA required?
A: Whilst not mandatory on all accounts today, we strongly recommend enabling it. It’s one of the most effective ways to protect your account.
Understanding Digital Trust: Research from Thales
Thales’ research demonstrates the critical importance of strong identity and access management. Our 2025 Digital Trust Index – Third-Party Edition reveals that 96% of third-party users face issues logging into partner systems, wasting 48 minutes a month on average. Additionally, 40% reset passwords once or twice a month – highlighting the need for more secure, passwordless methods like MFA.
The 2025 Data Threat Report further emphasises this urgency. According to our research, 83% of organisations report that strong MFA is used more than 40% of the time, yet challenges remain. As organisations adopt AI and face evolving quantum threats, robust authentication becomes even more critical.
Thales’ comprehensive Identity and Access Management solutions provide organisations with the capabilities needed to improve user experiences whilst strengthening security. From Multi-Factor Authentication and Single Sign-On to passwordless authentication and passkeys, Thales delivers the tools to make IAM processes straightforward and dependable.
Final Thought
Cybersecurity is a shared responsibility. We design secure systems, and you make them stronger by turning on protections like MFA. Enable MFA today in your Thales account settings. It takes just a few minutes and makes a significant difference.
The surge in AI-driven traffic is transforming how websites manage their content. With AI bots and agents visiting sites at unprecedented rates (often scraping without permission, payment, or attribution) content owners face a critical challenge: how to protect their intellectual property while capitalizing on legitimate AI use cases.
Today, we’re excited to announce Imperva’s integration with TollBit, a groundbreaking solution that enables our Cloud Web Application Firewall (CWAF) customers to monetize traffic from AI bots and crawlers that would otherwise scrape their content without permission or compensation.
Meeting the AI Traffic Challenge
The traditional ad-supported and subscription-based content models are being disrupted by AI. This integration provides a new economic model where value flows fairly between content creators and AI developers, transforming unauthorized scraping into a sustainable revenue stream.
How Imperva and TollBit Work Together
The integration leverages Imperva’s industry-leading Web Application Firewall capabilities alongside TollBit’s analytics and monetization platform to create a comprehensive solution:
Detection & Enforcement: Imperva CWAF identifies AI bot traffic at the edge, providing the critical first layer of protection.
Intelligent Redirection: Using Imperva’s redirect rules, requests from AI bots are automatically redirected to a TollBit subdomain (e.g., tollbit.example.com), with CWAF returning an HTTP 302 response.
Payment Gateway: The TollBit subdomain returns an HTTP 402 response code (payment required), prompting AI bot operators to obtain valid TollBit tokens for authorized access.
Analytics & Insights: Through SIEM log integration, Imperva Access and Security logs flow to TollBit’s analytics engine, providing executives with clear, AI-specific analytics that show how bots are engaging with their content and the business impact of that traffic both within Tollbit and Imperva’s UMC.
Implementation Architecture
The integration requires a straightforward setup process:
Onboard your domain to Imperva Cloud WAF
Create a TollBit account and verify domain ownership via DNS TXT records
Configure a TollBit subdomain with appropriate DNS NS records
Create redirect rules in Imperva’s management console to route AI bot traffic
Set up AWS S3 bucket integration for log processing and analytics
To ensure compatibility with TollBit’s requirements, an AWS Lambda function prefixes dates to Imperva log file names, enabling seamless ingestion into TollBit’s analytics platform.
A Shared Vision for Fair Compensation
This partnership represents a fundamental shift in how content owners approach AI traffic. Rather than simply blocking all bots or allowing unrestricted scraping, sites now have granular control to enforce access rules and pricing on their own terms.
Content owners deserve fair compensation for how their content powers the AI ecosystem. By combining Imperva’s security capabilities with TollBit’s monetization tools, we’re enabling the transition from unauthorized scraping to sustainable, licensed transactions.
What This Means for Imperva Customers
With this integration, Imperva CWAF customers gain:
Robust protection against unauthorized AI scraping at the application layer
Complete visibility into AI traffic patterns and behaviors through dedicated analytics
Flexible control to decide which AI agents can access content and under what conditions
New revenue streams that turn scraping attempts into legitimate, paid transactions
The agent economy is here, and autonomous AI visitors are becoming a permanent fixture of web traffic. With Imperva and TollBit, you can ensure these interactions happen on your terms—fairly, transparently, and profitably.
Get Started
If you’re an Imperva Cloud WAF customer and want to activate the integration:
The more critical APIs become, the more sensitive data they carry identities, payment details, health records, customer preferences, tokens, keys, and more.
And this is where organizations face a painful, often invisible problem:
To protect APIs, many organizations end up exposing the very data they are trying to secure.
Most API security tools still rely on raw-payload logging, traffic replay, or shipping full request bodies into external analytics systems. That means sensitive customer data:
Leaves controlled environments
Gets stored in multiple systems
Crosses borders without intention
Lands in tools not designed to hold PII
Multiplies breach risk and regulatory pressure
This creates a direct conflict between security, privacy, and compliance, and businesses are caught in the middle.
The Real-World Impact: When Privacy Becomes a Security Liability
Across industries – financial services, retail, healthcare, travel, public sector, the story repeats:
1. Breach blast radius expands
The more systems that hold raw API payloads, the bigger the impact when any one of them is compromised.
2. Compliance becomes harder, not easier
GDPR, CCPA, HIPAA, PCI, and emerging data-sovereignty regulations penalize:
unnecessary data retention
cross-border data transfers
third-party exposure
lack of data-minimization controls
Most API security tools inadvertently violate all four.
3. Data residency rules block API security deployments
Organizations operating in multiple regions can’t centralize raw API data in a single cloud service, but many tools require doing exactly that.
4. Dev and QA environments become privacy risks
When security tests are based on production payload replays, sensitive data leaks into non-production systems.
5. Security teams lose visibility if they avoid raw logging
Many leaders try to “lock down” data flows, but that often leaves API blind spots, making it harder to detect business logic abuse, scraping, or session-based attacks.
This is the API privacy paradox:
You either weaken privacy to strengthen security or weaken security to preserve privacy.
The Industry Approach Is Broken
The traditional API security model makes three flawed assumptions:
You must log or store raw payloads to get visibility.
You must centralize traffic for analytics.
You must replay production data to test API security.
These assumptions create privacy exposure, compliance failure, and operational friction.
Imperva Solves This by Rethinking the Architecture
API security should not require exposing sensitive data, ever.
The architecture flips the traditional model:
1. Inspect at the PoP (where traffic lives)
Traffic is parsed in-memory at the Point-of-Presence closest to the application, SaaS PoP or on-prem.
Raw values never leave the PoP.
2. Convert sensitive values into privacy-safe artifacts
Classification + hashing replaces raw payloads with:
label
schema fragments
one-way irreversible hashes
This is the only data that ever moves upstream.
3. Detect and respond using metadata only
Anomaly detection uses metadata such as:
data labels
schema context
session identifiers
hashed tokens
No raw content is needed or exposed.
4. Enforce using hashes, not identities
Hash-based enforcement enables:
per-session blocking
token-level mitigation
behavior-based decisions
without seeing or sharing the sensitive value behind the hash.
5. Same privacy guarantees across all deployments
Cloud, on-prem, hybrid – the mechanics never change.
What This Means for the Business
This is where Imperva’s architecture translates directly into measurable, enterprise-wide value:
Smaller blast radius = lower breach liability
Fewer systems hold PII, drastically reducing what attackers can steal and what you must disclose.
Faster compliance alignment
Local data processing and zero raw persistence align with GDPR, HIPAA minimum-necessary, and sovereignty rules.
Real-time protection with zero added exposure
Inline, in-PoP inspection gives detection teams full visibility without raw payload retention.
Safer automation in Dev/QA
Privacy-aware test artifacts eliminate the risk of production PII leaking into pipelines.
Reduced third-party risk
Vendors never receive raw payloads, only metadata and hashes.
A future-proof privacy posture
As regulatory pressure increases, architectures like this become mandatory, not optional.
Why This Whitepaper Matters
This whitepaper breaks down exactly how Imperva delivers production-grade API protection while preserving privacy, with clear explanations and practical examples.
You’ll learn:
How to get deep visibility without storing raw payloads
Why in-PoP processing reduces exposure and simplifies compliance
How hash-based enforcement protects identities while enabling precise blocking
How to design a privacy-first architecture that works across hybrid/multi-cloud
In other words:
If you need to secure APIs and meet privacy, residency, or compliance requirements – this is essential reading.
Ready to See How Privacy-First API Security Really Works?
Download the whitepaper and learn how Imperva protects APIs without exposing sensitive data.
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.
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
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.
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.
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.
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.
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