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ZeroStresser

Bot User-Agent: zerostresser

⚠️ Overview

ZeroStresser is a commercial DDoS-for-hire (booter/stresser) service that emerged around 2018, operated by a threat actor group sometimes tracked as “Angel” or “Mazut” based on forum posts and leak traces. The platform was marketed on Russian-language cybercrime forums and later on Telegram, offering subscription-based unlimited DDoS attacks for as little as $20 per month. According to research by Digital Attack Map and Flashpoint, ZeroStresser claimed over 10,000 registered users and boasted a peak attack bandwidth of 500 Gbps using compromised IoT devices and dedicated servers.

🔧 Technical Capabilities

ZeroStresser primarily executed layer 4 (network/transport) and layer 7 (application) DDoS attacks. Its layer 4 arsenal includes SYN floods, UDP amplification (NTP, DNS, SSDP, Memcached), and ACK floods, often utilizing a botnet of C2‑controlled Mirai‑based IoT zombies. For layer 7, it supported HTTP/S GET and POST floods, slowloris‑style attacks, and URL‑specific flooding. The platform provided a web panel where customers could input a target IP or domain, select attack duration (up to 12 hours), and choose from multiple “methods” each with an estimated bandwidth suggestion. Traffic analysis from Arbor Networks (2019) showed that ZeroStresser frequently weaponized NTP amplification with a factor of up to 556, generating 40+ Gbps from a single open NTP server. The service also integrated a CAPTCHA solver to bypass simple rate‑limiting controls and offered a “vanity” subdomain feature for resellers.

📜 History & Notable Incidents

In 2019, Cloudflare’s DDoS team attributed a series of multi‑vector attacks against gaming server providers to ZeroStresser users, noting the attacks peaked at 650 Gbps. The following year, the FBI’s Operation Power OFF (2020) led to the seizure of several booter domains, but ZeroStresser remained operational by migrating to new .ru and .su TLDs. A 2021 report by Kaspersky linked ZeroStresser to a wave of extortion attacks against e‑commerce sites in Southeast Asia, where the perpetrator demanded ransom to stop ongoing floods. No confirmed CVE identifiers are associated with the tool itself — it is a commodity service rather than a vulnerability exploit framework.

🔍 Detection Indicators

Unlike crawler bots, ZeroStresser does not use a unique User‑Agent string; its traffic appears as random HTTP requests with varied headers and often spoofed source IPs. Behavioral fingerprints include sudden high‑volume TCP SYN packets to multiple ports from diverse source IPs, consistent NTP/SSDP amplification queries, and repeated HTTP GET requests to a single resource without any response acceptance (high RST rates). Network‑level detection relies on volumetric thresholds: >1 million packets per second or >10 Gbps sustained from a new IP range.

☠️ Risk & Impact

ZeroStresser can cause complete service unavailability, financial losses from downtime (average $5,600 per minute for e‑commerce), and reputational harm. Extended attacks may also deplete cloud provider resources and incur unexpected bandwidth bills. In targeted cases, the platform has been used in extortion campaigns, threatening repeated attacks unless a ransom is paid.

🛡️ Mitigation

Because ZeroStresser is a confirmed malicious DDoS‑for‑hire service, it is blocked immediately on detection. Any IP or traffic pattern matching known booter signatures — such as amplification queries to high‑volume NTP or SSDP — should be blackholed via BGP RTBH or scrubbed by a DDoS mitigation service (e.g., Cloudflare, Akamai). No legitimate use case exists for this tool.

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ⓘ Data Notice: The information presented above has been compiled from publicly available internet sources. Boteraser aggregates this data solely for informational purposes and does not independently classify, evaluate, or endorse any findings about the bots listed. The accuracy and completeness of this information is the sole responsibility of the original publishers. Boteraser and its operators accept no liability for any decisions made based on this data.

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