pk.org: Computer Security/Lecture Notes

Addendum

Part 7 - Anti-Cheat Technology

Paul Krzyzanowski – 2025-11-20

Part 1: Introduction to Malware and Taxonomy
Part 2: Malware Architecture and Components
Part 3: Delivery and Initial Compromise
Part 4: Social Engineering Attacks
Part 5: Specialized Malware Components
Part 6: Defenses Against Malware Part 7: Addendum: Anti-Cheat Technology (optional)

Note

This is a topic you don't need to know for the exam but is related to malware. I'm adding it for those who may be interested.

Addendum: Anti-Cheat Technology in Online Gaming

The defense techniques we've examined so far focus on protecting systems from malicious software that seeks to steal data, disrupt operations, or hold systems hostage.

However, there's another category of software modification that, while not traditionally considered malware, presents similar detection challenges and employs similar defensive approaches: cheating in online games.

A key difference is that users don't install malware deliberately. Cheaters, on the other hand, willingly install software to give themselves a competitive advantage and are therefore willing to bypass any system protections to do so. This fundamentally changes the threat model: rather than tricking users into compromising their systems, cheat detection must contend with users actively working to circumvent protections.

The Gaming Cheating Problem

Online gaming generates billions of dollars annually, with games like Fortnite, League of Legends, and Counter-Strike maintaining massive player bases. The competitive nature of these games, combined with potential rewards (exclusive items, streaming revenue, professional play opportunities), has created a substantial cheating problem.

Players modify game software or system components to gain unfair advantages: seeing through walls, achieving perfect aim, removing visual obstacles, or obtaining information that should be hidden from them.

The scale is huge. A 2018 survey by Irdeto found that 60% of online gamers reported their experience being negatively impacted by cheaters, while 77% stated they would likely stop playing if they believed others were cheating. Perhaps most telling, 37% of surveyed players admitted to cheating themselves.

For game companies, this isn't merely about fairness: frustrated legitimate players abandoning games directly impacts revenue. Anti-cheat systems attempt to detect and prevent these modifications.

How Anti-Cheat Software Works

At its core, anti-cheat software operates much like antivirus software but focuses on detecting game modifications. It performs signature-based scanning to identify known cheating tools, monitors system behavior for suspicious patterns (such as unauthorized memory access or process injection), and validates game integrity by checking that game files and memory haven't been tampered with.

When the anti-cheat system detects anomalies, it typically sends reports to the game company's servers for analysis. Confirmed violations result in account bans, while newly discovered cheating techniques get added to signature databases for future detection.

The key challenge in detection lies in where the cheating software and anti-cheating software likes runs in the operating system hierarchy. This brings us to a technical arms race that mirrors the evolution of rootkits and antivirus software.

The Privilege Escalation Arms Race

When we studied access control, we explored the concept of modes of operation and rings of protection, where instructions in a processor have different privileges based on the mode in which the processor is currently running.

Anti-cheat software initially operated at user-mode (Ring 3 in the x86 privilege model). At this level, applications run in isolation and cannot directly access hardware or other applications' memory. They must request permission through system APIs to scan for cheating software. This worked reasonably well initially, but the situation mirrors our earlier discussion of malware evolution: attackers adapt to defensive measures.

Cheat developers responded by moving their software to kernel-mode (Ring 0), where code executes with the highest privileges. At the kernel level, software can access any memory address, hook system calls, and modify data before user-mode applications ever see it. When anti-cheat software running in user-mode queries the system, kernel-level cheats can intercept those queries and return modified, legitimate-looking data. The anti-cheat software, having no visibility into kernel operations, detects nothing suspicious.

This forced game companies to respond in kind. Modern anti-cheat systems like Easy Anti-Cheat (used in over 150 games, including Fortnite and Apex Legends), BattlEye, and Riot's Vanguard now install kernel-mode drivers that monitor system activity at the deepest level.

These drivers can observe process creation, track memory access patterns, detect unauthorized modifications, and identify signature patterns of known cheating tools. By operating at Ring 0, they monitor "at the source" rather than relying on potentially compromised system calls.

How Kernel-Level Anti-Cheat Works

The technical approach parallels antivirus software but focuses on different threats. When a game with kernel-level anti-cheat is installed, a signed kernel driver is installed alongside it. This driver typically:

Starts at boot time: Many anti-cheat drivers load when the operating system starts, before user applications run. This early initialization prevents cheats from establishing themselves before detection mechanisms are active. Riot Games specifically noted they had been "forced to play this game from the user-level, effectively giving cheaters a much-needed, twelve-stroke handicap" before implementing boot-time kernel drivers.

Monitors system activity: The driver registers for kernel events to track process creation, DLL injection, memory modifications, and suspicious patterns. It watches for known cheat signatures (similar to antivirus signatures) and behavioral anomalies (similar to heuristic analysis).

Validates game integrity: It verifies that game files and memory haven't been modified, that no unauthorized processes are accessing game data, and that the gaming environment matches expected parameters.

Reports violations: When suspicious activity is detected, reports are sent to the game company's servers for analysis. Confirmed cheaters have their accounts flagged or banned. New cheating techniques are added to signature databases for future detection.

The similarity to antivirus techniques isn't coincidental. Both are attempting to detect and prevent unauthorized software modifications in an adversarial environment where attackers continuously develop new evasion techniques.

The Security Trade-offs

Kernel-level access provides effective cheat detection but introduces significant security concerns. Any flaws in a kernel driver can cause system-wide crashes (the infamous "blue screen of death") or, more seriously, provide attack vectors for actual malicious actors. A vulnerability in an anti-cheat kernel driver could allow complete system compromise.

As with any vulnerable system, security implications extend beyond that individual device. Once an attacker gains kernel-level access through an anti-cheat vulnerability, they could potentially pivot to other devices on the network. For remote workers whose gaming systems share networks with work devices, this creates enterprise security risks.

Modern operating systems have responded with security features that sometimes conflict with kernel-level anti-cheat. Windows' Hypervisor-Protected Code Integrity (HVCI), Kernel DMA Protection, and hardware-enforced stack protection all restrict what kernel drivers can do, precisely to prevent the kinds of deep system access that anti-cheat software requires. This creates compatibility tensions: the same security features that protect against malware can interfere with anti-cheat detection.

The privacy implications also warrant consideration. Kernel-level drivers have visibility into all system activity, not just game-related operations. While game companies state they only collect gaming-relevant data, the capability for broader monitoring exists. Some anti-cheat systems have been criticized for scanning external devices, monitoring hardware ports (to detect direct memory access devices), and generally having access well beyond what's necessary for game integrity.

The Ongoing Debate

Anti-cheat technology represents a microcosm of broader security tensions. Game developers and many players argue that kernel-level access is necessary to maintain game integrity and fair competition. Without it, sophisticated cheats operate undetected, driving away legitimate players and destroying game economies. The effectiveness seems clear: games with kernel-level anti-cheat generally report lower cheat rates than those without.

However, security researchers and privacy advocates point to the risks: vulnerabilities in widely-deployed kernel drivers create attack surfaces affecting millions of systems, the same access used for legitimate anti-cheat could be abused or exploited, and users have limited visibility into what these drivers actually do. The requirement to grant kernel-level access essentially requires trusting game companies with the deepest levels of system control.

This situation illustrates the fundamental challenge we've seen throughout our malware discussion: there's no perfect solution. Effective detection requires deep system access, but deep system access creates security risks. Game companies must balance cheat prevention against user security and privacy. Players must weigh their desire for fair gameplay against concerns about system control. Operating system vendors must decide how much to restrict kernel drivers, knowing that restrictions improve security but may break legitimate applications.

The arms race continues. Cheat developers constantly search for new evasion techniques. Anti-cheat systems become more sophisticated. Operating systems add new security restrictions. Each side adapts to the other's moves, creating an evolutionary pressure toward increasingly complex solutions. This mirrors the malware defense landscape we've examined: perfect security is impossible, but layered defenses and continuous adaptation make attacks harder and more expensive. Whether that trade-off is worthwhile depends on what's being protected and what risks are acceptable.

References

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