Data AnalysisVerified

Reviewed and published by trentmaziarz, April 21, 2026. Discovered and drafted by our automated research pipeline.

Akamai uses machine learning in its Account Protector product to assess in real time whether a login or account action is coming from the genuine account owner or an impersonator, generating a risk score that customer businesses can use to block or challenge suspicious requests. The product launched in June 2021 and received expanded capabilities in October 2024.

Details

Account Protector builds an individual behavioral profile for each user over time, capturing typical devices, locations, networks, and activity patterns. For each new login or account action, the ML model compares the request against the stored profile and cross-references network-wide reputation signals from all Akamai customers to calculate a risk score. In October 2024, Akamai added lifecycle protection covering post-login activities including account updates, password changes, and payment transactions.

Products affected

Akamai Account ProtectorAkamai Bot Manager

Sources & Evidence

Company Disclosure

Company DisclosureVerified

Akamai Account Protector Adds New Capabilities to Power the Fight Against Fraud and Abuse

Akamai Newsroom·Oct 2024

https://www.akamai.com/newsroom/press-release/akamai-account-protector-adds-new-capabilities-to-power-the-fight-against-fraud-and-abuse

Company DisclosureVerified

Account Takeover and Identity Theft Protection | Akamai

Akamai·Jan 2024

https://www.akamai.com/products/account-protector

Company DisclosureVerified

Akamai Enables Organizations To Fight Fraud And Reduce Friction At The Edge With Account Protector

Akamai Newsroom·Jun 2021

https://www.akamai.com/newsroom/press-release/akamai-enables-organizations-to-fight-fraud-and-reduce-friction

Cite this record

Trace Foundation. (2026). Akamai Technologies: Akamai uses machine learning in its Account Protector product to assess in real time whether a login or account action is coming from the genuine account owner or an impersonator, generating a risk score that customer businesses can use to block or challenge suspicious requests. The product launched in June 2021 and received expanded capabilities in October 2024 (data as of 2026-04-21) [Data set record]. AI Trace. https://www.aitrace.org/r/practice/3351b33e-faa6-48e6-925d-e867ef485920. Accessed September 7, 2026.

Stable link: https://www.aitrace.org/r/practice/3351b33e-faa6-48e6-925d-e867ef485920
Data as of: April 21, 2026
Last verified: April 21, 2026

How to cite AI Trace

Other practices by Akamai Technologies

Data AnalysisAkamai uses machine learning models in its Akamai Hunt service to automatically detect suspicious movement of attackers through customers' internal networks, surfacing threats that evade traditional security tools. Human security experts then investigate each flagged event before alerting the customer.Data AnalysisAkamai uses AI in its Guardicore Segmentation product to automatically map how applications and devices communicate inside a customer's network, then generate ready-to-enforce security policies that limit attackers' ability to move between systems. Major AI-powered updates to this product were announced in April 2024 and March 2026.ModerationAkamai uses an AI framework in its Bot Manager product to automatically distinguish human web visitors from malicious automated bots across customer websites, apps, and APIs, assigning each request a bot-likelihood score in real time. This capability has been in production for multiple years and handles an average of 40 billion bot requests per day.

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