Edge UOL integrates end-to-end data security to contain shadow AI data leaks

DLP technologies begin monitoring the use of artificial intelligence in companies after tools become the primary vector for corporate data exfiltration

The accelerated adoption of Generative Artificial Intelligence (GenAI) without IT team approval has consolidated a new, silent cyber risk in corporations: so-called Shadow AI. The reflection of this vulnerability appears in market indicators: the Microsoft Work Trend Index points out that 75% of professionals use artificial intelligence (AI) without corporate authorization, turning these platforms into today’s primary vector for business data exfiltration, according to the LayerX Enterprise AI Report. In this scenario, the Brazilian market requires Data Loss Prevention (DLP) technologies specifically designed to mitigate risks and leaks.

This phenomenon highlights the lack of visibility and control that technology departments have over the resources accessed by employees. Driven by the fast-paced nature of daily deliverables, teams frequently input strategic spreadsheets, proprietary code, and internal reports into public platforms to get quick summaries or analysis. This behavior results in the unintentional exposure of intellectual property, leading companies to lose control over their own information assets.

To support technology leaders through this challenge, Edge UOL, a Brazilian company specializing in cybersecurity and IT infrastructure, offers robust DLP portfolios. With comprehensive coverage, the solution encompasses the protection of data in use, data in motion (in transit), and data at rest, adding customized defenses against Shadow AI. The system proactively monitors endpoints – such as corporate laptops and mobile devices – as well as cloud-based services, acting promptly to identify, classify, and block non-compliant interactions.

“Professionals will continue seeking technological alternatives to enhance their productivity and digital literacy. Therefore, the new corporate race isn’t solely about operational efficiency, but rather implementing rigorous governance that protects the future and long-term sustainability of the business,” says Rodrigo Lobo, COO of Edge UOL.

Security That Keeps Pace with AI

The technology can analyze the nature of prompts, detecting sensitive information – such as Social Security numbers and personally identifiable information (PII) – and intercepting the transmission of data packets to public platforms like ChatGPT, Gemini, and Claude.

“Our DLP approach isn’t limited to blocking specific physical outputs, like USB ports; it focuses on the structural movement of information based on content classification. If an attempt is made to upload a restricted file to a commercial AI, transfer it via external emails, or even tamper with the document’s classification to bypass compliance guidelines, the system automatically stops that behavior. The tool can even temporarily disable commands such as copy and paste (Control-C/Control-V) and screen captures, ensuring the total integrity of the asset,” explains Mauro Cesar de Souza, General Manager of Operations at Edge UOL.

In addition to endpoint control layers on user devices, the architecture is supported by a Security Operations Center (SOC) structured to operate around the clock, providing masking capabilities and strict policies focused on continuous compliance with LGPD (Brazil’s General Data Protection Law) and regulatory audits. This surgical tracking of information flows will soon establish itself as a mandatory compliance guideline for the corporate market.

The convergence of real-time visibility and automated responses redefines companies’ defensive postures in the era of mass AI adoption. “The market has realized that banning access is neither a viable nor a smart business alternative. The next step in information security will be governed by the ability to enable innovation without compromising data sovereignty,” concludes Lobo.