Fingerprint helps enterprises distinguish between legitimate and malicious automated web traffic
Fingerprint announced new Smart Signals and platform enhancements that detect malicious bots and AI agents, distinguishing them from legitimate automated traffic.
As agentic commerce experiences explosive growth and autonomous AI agents become increasingly sophisticated, enterprises need advanced tools to protect against evolving fraud schemes without delaying innovation or turning away legitimate transactions.
Bots currently comprise over half of all internet traffic, with 30% classified as malicious, and Gartner predicts fully autonomous AI agents by 2036. This creates a critical challenge for businesses to differentiate between beneficial automation and malicious activity. Fingerprint’s new Smart Signals address this challenge by providing real-time risk indicators based on a device’s behavior, environment and configuration to enable enterprises to make better-informed decisions.
“Bots and AI agents represent both the biggest current risk and the fastest-evolving threat landscape we’ve seen,” said Dan Pinto, CEO of Fingerprint. “As agentic AI technology advances rapidly and becomes more cost-effective, malicious actors are increasingly leveraging these tools for sophisticated fraud. Fingerprint’s new Smart Signals ensures enterprises can harness the benefits of AI while maintaining robust defenses against malicious bots and agents that threaten essential business operations.”
Fingerprint Smart Signals and features for enterprises: Bot/AI agent detection
Bot Detection Smart Signal can detect dozens of bot detection and browser automation software tools. It performs intelligent classification on each API request to determine whether a bot or agent is legitimate or malicious, with only verified beneficial bots and agents classified as trustworthy.
Virtual Machine Detection Smart Signal further enhances AI agent and bot detection by identifying virtual machines, which are commonly used in automated fraud schemes. This capability provides an additional layer of protection against sophisticated attack vectors.
Residential Proxy Detection addresses one of the most challenging aspects of modern fraud detection. Residential proxies are increasingly accessible and affordable, making them attractive tools for fraudsters looking to mask their IP addresses. Because agentic traffic can be routed through ISPs to real residential IP addresses—giving malicious agents high authenticity—the ability to detect residential proxies with confidence levels is crucial for identifying all types of agentic-driven fraud.
Request Filtering: Fingerprint has gathered a list of known user agents used by AI companies for web scraping and model training, as well as AI assistants that help with scheduling and other repetitive tasks. The Request Filtering functionality allows customers to filter out these legitimate AI agents and bots from fingerprinting, helping optimize billing costs without compromising detection capabilities for AI-driven fraud.
The rise of intelligent automation demands smarter security for enterprises
As legitimate AI agents become more common for business operations—from AI assistants that handle scheduling and repetitive tasks to agentic commerce where agents research and purchase products on users’ behalf—the ability to differentiate between beneficial and malicious automation has become a critical industry requirement.
With these new enhancements from Fingerprint, organizations can gain comprehensive visibility into visitor intent, enabling proactive defense against evolving attack patterns.
The new Smart Signals and features are available immediately and are designed to integrate seamlessly with existing Fingerprint implementations.