Combating Credential Stuffing, Bots & Abuse in Online Gaming

The gaming industry today faces increasingly complex cybersecurity threats, including credential stuffing, bot-driven cheating, in-game economy manipulation, and DDoS attacks. In this article, we focus specifically on threats targeting online web services and infrastructure.

In collaboration with Peakhour, a leading platform in credential stuffing, bot mitigation, and behavioural detection, RST Cloud offers a joint solution that brings our deep threat intelligence expertise to securing modern gaming environments.

GameDev Industry Is a Prime Target

Online games have evolved into high-value ecosystems. Player accounts often carry real monetary worth due to rare items, virtual currency, and in-game prestige. Many are also linked to stored credit cards, digital wallets, or even cryptocurrency assets. This makes them attractive targets for attackers, who exploit them through automated credential stuffing, inventory-hoarding bots, and in-game economic abuse.

Recent high-profile incidents targeting gaming platforms include (but are not limited to):

• Attackers compromised one of the largest Counter-Strike: Global Offensive (CS:GO) skin-trading platforms, CS.MONEY, by stealing mobile authenticator (MA) files used for Steam login. This enabled them to hijack trading bots and effectively steal over $6 million worth of CS:GO inventory in a single attack. Though this affected platform-side inventory accounts, it directly facilitated account takeovers and rapid resale of in-game assets for Counter-Strike players.
• Blizzard Entertainment faced major disruptions during key tournaments due to persistent Distributed Denial-of-Service (DDoS) attacks – first in 2020, and again in April 2025. These incidents not only frustrate gamers but also lead to significant financial losses for gaming companies.
• In early 2023, Riot Games fell victim to a social engineering attack that targeted employees and resulted in the exfiltration of source code for League of Legends, Teamfight Tactics, and Riot’s anti-cheat systems.

Multi-Layered Protection

To address this, organisations in the gaming industry should look into enabling a multi-layered defence, including:

• Foundational Network Protection and ZTNA: Establish robust security measures by configuring comprehensive firewall policies, enforcing rate limiting, and deploying DDoS mitigation solutions. These measures may be complemented by traffic redirection to a scrubbing centre via DNS or BGP, as needed. Augment these measures with Zero Trust Network Access (ZTNA) to ensure granular, identity-based access management across all resources.
• Web Application Firewall – WAF: Block known attackers, apply rules to prevent common web attacks, and implement traffic shaping, CAPTCHA challenges, and web redirection in response to suspicious or abusive behaviour.
• Bot mitigation: Detect cheating tools, residential proxies, browser simulators, and scraping activity.
• Credential stuffing protection: Monitor breached credentials and detect automated credential abuse, including those attempts that hide behind residential proxies.
• Layer 7 DDoS detection: Use fingerprinting techniques based on SSL/TLS, TCP timing, Layer 7 headers, protocol-specific behaviours, and adaptive thresholds.

The Strategic Imperative of Threat Intelligence

To effectively detect these types of attacks, it is essential not only to have the right tools, but also to maintain highly relevant data on current attacks and threat actor behaviours. This is the role of Cyber Threat Intelligence (CTI), which collects and analyses data providing a near real-time snapshot of malicious infrastructure, exploited vulnerabilities, and real-world web attacks identified from traffic. CTI also gathers information on proxies, bot automation hosts active in the wild, and other threat sources across the Internet — all sourced from live attacks and updated hourly.

However, given the nature of such threats—often involving legitimate user devices, accounts, or ambiguous network environments—the analysis and handling of these attacks must be carefully designed to avoid blocking legitimate users.

That’s where RST Cloud steps in.

RST Cloud’s Role: Operational Threat Intelligence

At RST Cloud, we specialise in making actionable, contextual threat intelligence available with minimal effort required from your SecOps team.

Our value lies in transforming unstructured, semi-structured, and structured data into actionable intelligence that drives security automation:

• Active Exploitation Attempts: information on active external exploitation of vulnerabilities and their ties to threat actors and malware.
• Threat Actor Intelligence: information on common TTPs, malware, and tools used by threat actors, including webshells and C2 infrastructure.
• IoC Intelligence: Know whether an IP is noisy, benign, or tied to malicious infrastructure.
• Proxy Intelligence: Know if an IP is a known SOCKS/HTTP proxy or a part of residential proxy network (RESIP).
• Bot intelligence: Know if an IP is related to bot actively, including browser simulators such as Selenium, playwright, and others.
• Scoring: Providing comprehensive scoring for collected IoCs based on multiple parameters, enabling the most risky indicators to be distinguished from purely informative ones. In the case of IP addresses — particularly relevant to web attacks — this helps prioritise IP sources (to block incoming connections) and IP destinations (to prevent call-backs to C2 servers, second-stage payload downloads, etc.). For other IoC types, scoring also supports the detection of malicious callback domains and URLs, as well as file hashes used to identify webshells.

Through the collaboration with Peakhour platform RST Cloud enriches detections with our in-depth scoring system based on:

• Frequency of appearance of attacks in the wild
• Number of independent sources confirming the attacks
• Behaviour category (e.g., web attacks – high risk, browser automation – medium risk, VPN – low risk)
• Number of related domains for the ASN (e.g., cloud-hosting = likely bot)
• History of attacks and reputations of networks
• Score decay based on recency of activity

For example, if a login attempt is detected from a suspicious source, RST Cloud can instantly provide context:

👉 Is the IP part of a known proxy network and browser automation was used ?

👉 Is the IP related to a compromised hosts or a known malicious infrastructure?

👉 Is it a well-known IP of a trusted bot that we could ignore (e.g. a scan from a security company)?

Use Cases Where Our Collaboration Shines:

How to Consume This Intelligence

Through the RST Threat Feed, this intelligence is delivered as structured IoC data, easily ingested into your existing security stack (WAF, NGFW, SIEM, SOAR, etc.).

We offer robust, standards-based APIs and custom formats to meet gaming industry demands – making integration plug-and-play.

Looking Ahead

This partnership combines Peakhour’s behavioral detection and RST Cloud’s global-scale threat intelligence into a powerful defense layer for game developers.

Together, we deliver not just protection – but insight, speed, and clarity.

Want to learn more about our APIs or game-industry use cases? Let’s connect!