Despite heavy investments in securing employee logins with multi-factor authentication (MFA) and conditional access policies, a significant security gap exists in account recovery processes. Service desks frequently use knowledge-based questions for identity verification during password resets or account recovery, which can be easily circumvented by attackers.
Attackers can gather extensive personal and professional information from sources like LinkedIn, company websites, and social media. This data allows them to answer verification questions accurately, impersonating legitimate employees. Successfully passing these checks can lead to unauthorized password resets or account recovery, bypassing the initial strong login security measures.
The risks associated with knowledge-based authentication are recognized by industry standards; NIST's digital identity guidelines no longer endorse security questions as an acceptable authentication method. Stolen credentials contribute to 44.7% of data breaches, highlighting the severity of this vulnerability.
Cybercriminal groups, such as Scattered Spider, specifically target service desks. Instead of directly bypassing MFA, these groups impersonate employees to persuade service desk agents to reset passwords or register new MFA devices. The effectiveness of these social engineering attacks is amplified by generative AI, which makes impersonations more convincing and allows attackers to scale their efforts.
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Organizations often rely on knowledge-based questions for service desk identity verification, creating a security gap that bypasses stronger login protections like MFA. Attackers use publicly available information and social engineering, increasingly aided by AI, to impersonate employees and gain account access through password resets or MFA device registration. This vulnerability is significant as stolen credentials are a major factor in data breaches, and NIST guidelines no longer recommend knowledge-based authentication.