You cannot verify a vendor’s security claims from their own datasheet, including ours. That is why independent validation matters. In our recent guide to the best WAAP solutions (Best WAAP Solutions 2026: Enterprise Buyer Guide), we argued that every serious shortlist should include independent third-party testing across both web and API threats. SecureIQ Lab’s Cloud WAAP v5.0 CyberRisk Validation, published this week, delivers exactly that: twelve leading cloud WAAP platforms, 1,608 attack scenarios, and 1,487 false-positive traps, all run under identical, adversarial conditions, with every vendor’s results published in full.

This blog is the follow up to that buyer guide and explains what the new report says and how to read any benchmark.

Balancing security efficacy and false positives

A high security-efficacy score, on its own, is easy. Tune any WAF aggressively enough and it will stop every attack, along with a meaningful share of your customers. That is the trap: security efficacy and false positives pull against each other, and false positives are never a rounding error.

Every legitimate transaction blocked is lost revenue, an abandoned cart, a support ticket, a SOC triage, another tuning cycle, and operational cost on top of the license. At scale, teams respond to false-positive pain by loosening policies or dropping rules into detect-only mode. The efficacy number you thought you were buying quietly disappears in production.

The genuinely hard engineering problem, the one that determines your real protection and your real total cost of ownership, is holding maximum efficacy and near-zero false positives at the same time.

That is the equation to grade this report on. Imperva WAF and API Security was placed in the Leader category with a perfect 100% Complete Security Score, the only perfect score of the twelve vendors, across every tested category: all OWASP web test cases, all ten OWASP API categories on all five protocols, every bot, AI-assisted bot, and Layer 7 DoS scenario, every evasion vector, and the full vulnerability assessment.

Against 1,452 legitimate-transaction test cases mixed into live traffic, Imperva achieved that balance of maximum efficacy and zero false positives. No other vendor in the field held a perfect score on both sides of the equation. This evaluation validated protection you do not have to trade away to keep your customers moving.

API security matters: Imperva scored 20% above average

Most vendors now score well on classic web attacks. The OWASP WAF group average was 89.96%, and five vendors scored 99.5% or better. APIs are a different story. Across the OWASP API Security Top 10, tested over five protocols, published scores ranged from 45.5% to 100%, around a group average of 80.3%.

Imperva scored 100% on every API category and every protocol tested, including WebSockets, where the twelve-vendor group averaged just 48%. If your evaluation shortlist is driven by web-attack demos, the API results are where you should spend more time. That was one of the main recommendations in the WAAP buyer guide, and the new numbers reinforce it.

New in 5.0: AI security and compliance

The 5.0 methodology adds AI application security: 35 attack scenarios aligned with OWASP LLM01 (Prompt Injection) and LLM05 (Improper Output Handling), scored independently of the headline results. Here is the honest reading: nine of the twelve vendors, Imperva included, scored 100% on that attack set. Runtime LLM attack-blocking is already table stakes.

Where the field separates is operating AI protection at enterprise scale. SecureIQ Lab’s GenAI & LLM Operational Efficiency rating looks at the ability to deploy, govern, and observe AI protections in production. Scores ranged from 0% to 100%, around a 73% group average. Imperva was one of five vendors rated 100%.

The second new dimension is compliance. SecureIQ Lab ran a five-layer assessment across regulatory, data-protection, audit, governance, and AI frameworks (NIST, ISO/IEC 27001 and 42001, PCI DSS, GDPR, HIPAA, and more). Imperva’s 87% was the highest score of all twelve vendors, against a 63.95% group average, including 100% on the AI security layer.

If your security purchases have to survive an audit committee, which is true for most enterprises, this is the part of the report to share with your GRC team.

In summary:

• 100% OWASP LLM score: Imperva blocked all tested LLM01 and LLM05 attack scenarios.
• Zero LLM false positives: legitimate AI interactions in the LLM test set were not blocked.
• 100% GenAI & LLM Operational Efficiency: Imperva scored 100% versus a 73% group average.
• Operational readiness matters: the rating reflects capabilities such as vulnerability coverage, sensitive data protection, full-stack LLM observability, SDK-based guardrail integration, and system-prompt-based context guardrails.

AI protection cannot stop at attack blocking. As organizations bring LLM-backed applications into production, they also need visibility, guardrails, integration, and governance that teams can operate day to day.

Imperva’s AI results show both sides of that equation: tested protection against key LLM threats and validated operational readiness to help enterprises adopt AI more securely and manageably.

WAAP Operational Efficiency in Real Life

Operational efficiency determines how practical a WAAP will be for real-world application teams.

In the SecureIQ Lab Cloud WAAP 5.0 validation, Imperva achieved a 98.8% WAAP Operational Efficiency rating, outperforming the 94.1% group average while also delivering perfect security efficacy and 100% false positive avoidance.

That combination matters because modern security teams are not only judged by whether they stop attacks, but by whether they can do so without slowing deployments, creating unnecessary tuning work, or interrupting legitimate business traffic.

The nine operational security categories tested were:

1. Ease of deployment
2. Ease of management
3. Ease of risk management
4. Logging & auditing capabilities
5. Visibility & analytics
6. Support & documentation
7. API Gateway efficiency
8. Integration capabilities
9. Geolocation based security features

Imperva scored 98.8% against a 94.1% group average, with perfect scores in every category except API Gateway Efficiency (94.4%), where JWT validation has been identified as an improvement opportunity.

The operational results show strength across the day-to-day capabilities that determine whether a WAAP can be run confidently at an enterprise scale.

Imperva was rated 100% in ease of deployment, ease of management, ease of risk management, logging and auditing, visibility and analytics, support and documentation, integration capabilities, and geolocation-based security features.

These categories translate directly into practitioner outcomes: faster setup, simpler policy reuse, stronger role and user management, clearer threat analytics, easier SIEM and SOAR integration, more flexible logging, and better tools for reducing false-positive risk.

The only operational category below 100% was API Gateway Efficiency, where Imperva scored 94.4% against a roughly 95% group average, with JWT validation identified as an area for improvement.

The takeaway for buyers: operational efficiency is not a secondary metric. A WAAP that is difficult to deploy, difficult to tune, or noisy in production becomes an operational burden even if its detection rates look strong.

Imperva’s results show that protection can be both highly effective and highly manageable — giving security, application, and platform teams independent validation that they can strengthen defenses without adding unnecessary friction to the business.

In summary: Four rules for reading any WAAP benchmark

• Read efficacy and false positives as one result, not two separate ones. A perfect block rate with a high false-positive rate does not deliver security. That combination is an outage generator with a dashboard, and its real-world efficacy will be tuned away within a quarter.
• Go to the API results before the web results. Web scores tend to cluster near the top across the industry; API scores are where architecture differences show up.
• Check which deployment model was tested. A SaaS cloud service and a self-managed virtual appliance are different operational propositions; the report calls out the model for each vendor.
• Ask every shortlisted vendor for their current published results, and for the categories where they did not lead. A vendor who cannot name one has not read their own report or needs to check their points.

The full report and methodology are public.

If you are still shaping a shortlist or building evaluation criteria, go back to the earlier Best WAAP solutions blog, Best WAAP Solutions 2026: Enterprise Buyer Guide. It is a practical playbook for what to look for in WAAP architecture, operations, and economics. SecureIQ Lab’s Cloud WAAP 5.0 results now give you independently validated numbers to plug into that playbook.

Source for all figures: SecureIQ Lab Cloud WAAP CyberRisk Validation v5.0, 2026 (AMTSO-certified). Placements and competitor scores from the published comparative report.

The post What SecureIQLab Cloud WAAP 5.0 means for your application security appeared first on Blog.

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.

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The Rise of Uncontrolled Automation

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.

Download the Full 2026 Bad Bot Report

Get the complete data, sector breakdowns, and defense recommendations in Imperva’s 2026 Bad Bot Report: Bad Bots in the Agentic Age.

Frequently Asked Questions

What is the Imperva Bad Bot Report?

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.

The post Bad Bot Report 2026: The Internet Is No Longer Human and It’s Changing How Business Works appeared first on Blog.