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Massive DDoS Attack Evades Detection Using 1.2M IPs

Massive DDoS Attack Evades Detection Using 1.2M IPs

Posted on May 7, 2026 By CWS

A sophisticated Distributed Denial of Service (DDoS) attack recently targeted a prominent user-generated content platform, generating an astonishing 2.45 billion malicious requests within a mere five-hour window. This attack represents a significant shift in DDoS tactics, as it leveraged over 1.2 million distinct IP addresses to effectively bypass traditional rate-limiting measures.

Innovative Tactics in DDoS Attacks

Unlike typical brute-force methods, the attackers strategically dispersed traffic across a vast array of IP addresses. This innovative approach highlights a critical vulnerability in conventional rate-limiting defenses, allowing the attackers to maintain persistent pressure on their target while evading detection.

The attack’s metrics indicate a highly coordinated operation, with a peak request rate of 205,344 requests per second (RPS) and an average of around 136,000 RPS. By ensuring each IP sent a request every nine seconds, the attackers managed to remain undetected, presenting traffic patterns that appeared benign in isolation.

Complex Infrastructure and Evasion Techniques

Analysis of the attack revealed its distributed nature, with the botnet spreading across 16,402 autonomous systems (ASNs). This level of distribution underscores the operation’s sophistication, as no single ASN contributed significantly to the overall traffic, making it difficult to block the attack by targeting specific ASNs.

The attackers cleverly mixed traffic from anonymity-focused ASNs and reputable cloud providers like Cloudflare, AWS, and Google. This strategy enabled the malicious traffic to blend seamlessly with legitimate data flows, complicating detection efforts.

Effective Detection and Mitigation Strategies

Despite the attack’s scale and complexity, it relied on moderately sophisticated evasion techniques. Attackers manipulated headers and cookies but lacked advanced browser automation capabilities, leaving some room for detection.

DataDome’s Galileo threat research team successfully intercepted the attack by employing a multilayered behavioral detection system. This approach focused on identifying network-layer inconsistencies and anomalous session behaviors, as well as flagging IP addresses with poor reputations.

The incident highlights the importance of evolving detection methods in line with increasingly sophisticated DDoS tactics. As attackers continue to refine their evasion strategies, defenders must adopt dynamic, behavior-based detection systems that analyze patterns over time and across multiple sources.

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Cyber Security News Tags:anonymization, autonomous systems, behavioral detection, Botnet, cloud providers, cyber attack, Cybersecurity, DataDome, DDoS, Galileo research, IP evasion, network security, rate limiting, Threat Actors

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