As generative AI continues to empower modern businesses in their innovative efforts, it's also redefining the cybersecurity threat landscape in ways that can’t be ignored. Sophisticated bots, powered by machine learning and AI, are now outsmarting legacy defenses, mimicking humans and bypassing traditional detection tools with alarming precision.
Imperva’s 2025 Bad Bot Report found that automated bot traffic now accounts for more than half of global internet activity, and with malicious bots alone making up 37%, it’s increasingly difficult to distinguish between bad bot behavior and legitimate buyers.
The rapid rise of bad bots is transforming familiar interfaces used by legitimate buyers, such as login pages, checkout flows, and customer service portals, into high-risk vulnerabilities that can facilitate fraud. This emerging threat signals a critical shift for enterprise security teams, highlighting the need to recognize how the very tools integrated into their workflows can be weaponized against them, putting trust, revenue, and sensitive data at serious risk.
Nowhere is this threat more apparent than at the API (Application Programming Interface) layer. APIs are designed to streamline digital services and have become top targets for AI-driven bots, accounting for 44% of advanced bot attacks. These interfaces handle the behind-the-scenes business logic that powers identity validation, payment processing, inventory updates, and other functions, making them not just entry points but high-value chokeholds of sensitive information.
Bad bots don’t exploit this logic with brute force; instead, they’re imitating legitimate actions, such as placing (fake) orders. Bots are scraping competitive pricing and also abusing return policies in ways that evade traditional rule sets. AI enhances these tactics even further by replicating genuine user behavior with emulated mouse movements, timing patterns, and browser fingerprints.
The Cost of Account Takeover and Identity Fraud
As bots become more sophisticated with AI, they’re betting big on businesses’ bottom line. In 2023, the FTC reported that Americans lost $2.7 billion to imposter scams, with a significant portion of the losses tied to credential theft and bot-based crime.
Beyond being a security issue, bad bots are a threat to user experience and brand equity. Account takeovers (ATOs) spiked 40% year-over-year, and 14% of all login attempts were deemed takeover attempts, according to the Bad Bot report.
For example, in financial services and retail, where customer accounts often tie directly to payment data and loyalty systems, these bots can drain wallets before red flags are raised. In healthcare, bots can scrape or breach personally identifiable information (PII), and the impact can persist for years, affecting victims through identity fraud and insurance scams. These thieves don't just steal credentials and fuel identity fraud; they’re hijacking trust, revenue, and reputation.
AI’s Role in Expanding Organizational Blind Spots
Enterprises are embracing AI at an unprecedented rate and must also engage their security defenses at the same pace. According to the 2025 Thales Data Threat Report, 69% of organizations identified the pace of AI evolution as their top security risk related to generative AI.
As businesses integrate AI into customer service, content creation, operations, etc., bots are learning to do the same, mimicking human users with a precision that is hard to detect. One stark example is a vulnerability that security researchers uncovered in the DeepSeek V3 model, which allowed attackers to bypass all 50 known jailbreak prompts tested. The model failed 100% of those challenges—a reminder of how untested AI deployments can open floodgates to exploitation.
Part of the problem is architectural complexity. APIs, multi-cloud, and automation drive modern enterprises. According to the Data Threat Report, one in three organizations now manages more than 500 APIs, and many lack visibility into how these APIs are accessed, secured, or monitored. Even more concerning, secrets management (securely storing sensitive information like encryption keys and passwords) remains under-prioritized, with just 16% of organizations identifying it as key to protecting data, despite it being a top DevOps security concern.
Misalignment and misunderstanding of these complexities and security controls create fertile ground for AI-powered bots to infiltrate an organization’s digital environment. Bad bots are overwhelming API endpoints, exploiting business logic, interrupting workflows, automating payment fraud, hijacking accounts, and exfiltrating data via these security blind spots with greater speed than ever before.
Your Move: Strategically Keep AI Investments Paced with Security Solutions
To combat these evolving threats, security teams must move beyond reactive defense. APIs are a critical attack surface in modern digital infrastructure, and many companies are expanding their investments in AI-specific security tools, but it’s not just about deploying tools; it’s about a comprehensive strategy that deploys the right defenses, in the right places, at the right time.
Here’s how organizations can make a targeted approach:
- Identify and Prioritize Risk Hotspots: Assess the areas of your site that attract bot traffic. Pages for product launches, login portals, checkout forms, and pages with gift cards or exclusive inventory are great places to start evaluating high-risk.
- Deploy Adaptive Bot Detection and Rate Limits: Use AI-powered tools that detect evasive and human-like bots in real-time. Implement dynamic rate limiting, adaptive CAPTCHAs, and traffic anomaly detection to contain suspicious behavior without degrading user experience.
- Harden API Endpoints Against Abuse: Protect API logic with strict authentication, behavior-based monitoring, and rules that detect scripted activity (e.g., account takeover attempts, scraping). Avoid exposing overly permissive endpoints and monitor abnormal patterns in purchase/request volumes.
- Enforce Multi-Factor Authentication (MFA) and Credential Protections: Implement phishing-resistant MFA, particularly on login and administrative interfaces. Guard against credential stuffing and carding attacks by integrating credential intelligence services and blocking known breached credentials.
- Continuously Monitor and Test for Emerging Threat Patterns: Define your baseline for failed login attempts on login pages, then monitor for anomalies or spikes. Implement tools to monitor bot behavior in real time and adapt defense strategies as bots evolve by regularly testing new attack vectors on your own applications.
And finally, don’t play all your security cards at once. Implementing techniques simultaneously across an entire platform can inadvertently reveal your whole defensive playbook, giving attackers a chance to analyze and develop countermeasures over time. Instead, stagger defenses strategically to roll out protections in phases, or target specific high-risk areas first. This approach also allows for real-time learning and adaptation as threats evolve.
