DDoS Attack Hits 1.5 Billion Packets Per Second, Fueled by IoT Devices
A European DDoS mitigation provider has been struck by an unprecedented attack, with traffic volumes peaking at 1.5 billion packets per second. The massive wave originated from thousands of compromised IoT devices and MikroTik routers, weaponized by attackers into a sprawling distributed botnet. The incident was detected and contained in real time through the FastNetMon monitoring system, which activated router-level filters and advanced traffic-scrubbing mechanisms.
According to FastNetMon specialists, the assault was a massive UDP flood emanating from more than 11,000 networks worldwide. Mitigation relied on access control lists deployed across edge routers and the capabilities of specialized scrubbing centers, which analyzed packets, throttled rates, and applied heuristic anomaly detection. While the targeted client remains undisclosed, it has been confirmed that the victim was itself a DDoS filtering service, specifically designed to withstand such large-scale attacks.
The distinguishing feature of this incident was not only its sheer volume of traffic sources, but also the exploitation of consumer-grade networking equipment as offensive infrastructure. This marks a disturbing trend: only a week earlier, Cloudflare reported the largest volumetric attack ever recorded, reaching 11.5 Tbps and 5.1 billion packets per second. In both cases, adversaries sought to overwhelm data-processing resources, risking widespread service outages.
Pavel Odintsov, founder of FastNetMon, warned that this trajectory threatens the stability of the global internet. He emphasized that countering such attacks demands proactive measures at the level of internet service providers, who must implement outbound traffic filtering before malicious flows reach critical mass. Without such systemic intervention, Odintsov cautioned, millions of infected consumer devices will continue to be transformed into weapons capable of inflicting damage on infrastructure at a planetary scale.
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