Global AI Platform Elevates User Experience with Arkose Labs Collaboration

Discover how the company reduced malicious activity, protected costs, and enhanced user experience by detecting and deterring automated attacks effortlessly.  

What You’ll Learn

• How a leading AI platform faced unprecedented automated abuse across every major flow How attackers exploited sign-up, login, messaging, payments, developer tools, and LLM prompts in ways that strained infrastructure and degraded the user experience.
• Why the company needed a partner capable of continuous, real-time intervention How internal teams were overwhelmed by rapidly evolving attack patterns, infrastructure drain, and cross-channel fraud that exceeded the capabilities of their existing toolset.
• How Arkose Labs deployed multilayered protection across critical workflows How Arkose Bot Manager, Arkose GPT Protect, MatchKey challenges, email risk analysis, token enforcement, and phishing protections worked together to deter automated and human-assisted attacks.
• How security collaboration and threat intelligence neutralized attacker strategies How Arkose’s ACTIR and SOC teams tracked attacker repositories, monitored open-source tooling, and delivered countermeasures that prevented attackers from adapting.
• How guardrails were established to prevent LLM misuse and model-based evasion How Arkose Labs evaluated multimodal LLM capabilities to ensure attackers couldn’t use the models themselves to break challenges or bypass authentication defenses.

FAQ

What types of abuse were overwhelming the AI platform?

The company faced wide-ranging threats: LLM platform abuse, SMS toll fraud, phishing, account takeover, fake account creation, credit-card fraud, API circumvention, and access from prohibited regions. These attacks strained GPU resources, increased operational costs, and prevented real users from accessing the service reliably.

How did Arkose Labs improve security without harming the user experience?

Arkose Labs deployed adaptive, low-friction controls across the registration flow, chat prompts, authentication, developer portals, and profile updates. These measures stopped automated abuse while preserving seamless access for genuine users, ensuring that security enhancements did not impede legitimate traffic.

How did Arkose stop LLM platform abuse specifically?

Attackers were proxying the platform’s premium model to avoid API billing and resell access. Arkose implemented token enforcement, bot-resistant challenges, and workflow hardening, which raised attacker costs and forced them to abandon automated pipelines and human-farm-assisted tactics.

What role did Arkose threat intelligence play?

Arkose’s ACTIR team monitored attacker GitHub repos and communication channels and collaborated with Microsoft to disrupt global bot marketplaces, including Storm-1152. This network-wide intelligence blocked attacks not only against the AI platform but also across other enterprises benefiting from the shared threat-signal ecosystem.