The bot threat landscape has fundamentally changed, with a new reality that is far more sophisticated than the simple, scripted bots of the past: AI-enhanced bots. AI has dramatically lowered the barrier to entry for attackers while amplifying the scale and sophistication of their attacks.
The stakes have never been higher. According to Radware’s 2025 Global Threat Analysis, bad bot activity grew by 57% in H1’2025 compared to H2’2024, nearly reaching 90% of the total 2024 volume in just 6 months. This massive growth underscores the rapid acceleration of the bot threat landscape, driven overwhelmingly by the weaponization of AI.
To effectively combat these evolving AI-driven threats, organizations need advanced solutions that meet the threat with far more stronger, AI-powered capabilities across every phase of the attack lifecycle: Threats must be anticipated and blocked at the perimeter. Those that get through must be detected in real-time. Detected threats require immediate, effective mitigation. Critical incidents must be identified and investigated to strengthen the entire defensive posture.
Phase 1: Preemptive Protection
Preemptive protection stops attacks before they consume resources or reach your applications. It isn’t just about saving infrastructure costs, it also reduces the burden on detection and response systems, enabling focus on the more sophisticated threats rather than known attack patterns.
With AI-powered preemptive protection capabilities, attack patterns can be analyzed and threats can be correlated across applications to identify and block malicious actors at the perimeter before they probe your defenses.
Phase 2: Real-time Detection with Comprehensive Visibility
Comprehensive, real-time visibility is the foundation of effective bot management. The key challenge is to accurately distinguish human users from legitimate bots, malicious bots, AI crawlers and agents within incoming traffic.
Traditional signature-based detection fails against sophisticated, AI-enhanced bots that constantly evolve their tactics. AI-based behavioral analysis capabilities can identify the intent of incoming traffic in real-time, rather than just recognizing known patterns. This enables accurate differentiation of human users from bots, moving beyond the traditional ‘bot or not’ to understanding who is behind the traffic.
Phase 3: Advanced Mitigation Techniques
Effective mitigation isn’t about blocking all suspected threats, it’s about applying the right response to the right threat while minimizing friction for legitimate users. The goal is to find the optimal balance between security effectiveness and user experience.
Bot management solutions that leverage AI and machine learning to generate real-time signatures from newly detected attack patterns can provide immediate protection against emerging threats. From effectively blocking threats to advanced CAPTCHA-less mitigation techniques such as cryptographic challenges, flexible mitigation options can provide a nuanced approach that stops threats without creating friction that drives away legitimate customers.
Phase 4: AI-based Incident Remediation
Bot attacks generate thousands of security events, overwhelming SOC teams and causing alert fatigue for analysts. Traditional manual investigation cannot keep pace with the frequency and volume of modern attacks. Carrying out detailed root cause analysis (RCA), reconstructing attack timelines, and identifying patterns across events could take human analysts hours or days to complete.
AI-based incident remediation capabilities can provide another layer of active defense by continuously monitoring for leaked or unmitigated bot threats. It can provide instant attack analysis and contextual insights to accelerate RCA, and automate remediations, thereby reducing the mean time to resolve (MTTR) incidents. By handling routine analysis and investigation, this will free up security analysts to focus on complex cases requiring human expertise and strategic decision-making.
Fighting AI with AI
In the battle against sophisticated bot threats, AI isn’t optional. Organizations that adopt AI-powered bot management solutions can build long-term resilience that evolves alongside the threat landscape. It’s the only way to respond to the scale and frequency of modern attacks with end-to-end lifecycle coverage while maintaining the efficiency and user experience that the business demands.
To gain deeper insights into managing AI-driven bot traffic throughout the attack lifecycle and learn more about the Radware Bot Manager’s real-time, AI-powered bot protection capabilities, listen to our webinar here.