Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Texas Data Privacy and Security Act (TDPSA): Website Requirements 2026

Applicability thresholds of state privacy laws often hinge on size or scale. TDPSA is different. It puts no revenue thresholds like CCPA or CPRA. So if your business operates in Texas or reaches the state’s residents, you’re most likely inside the scope already. The law took effect on July 1, 2024, and by January 2025, the universal opt-out obligations became fully enforceable. That transition is what moved TDPSA from a policy update to a website-level requirement.

Why AI Privacy is a Competitive Advantage (Not Just Compliance)

In most startups building or using AI, privacy often gets treated like a checkbox that legal or security will “handle later.” That mindset quietly kills deals, scares off enterprise buyers, and limits your access to the very data your models need. Here is the truth that more founders and CTOs are embracing. Privacy makes your product easier to buy, models better to train, and business more valuable.

We Built Protecto SaaS Because $50K/Month Privacy Tools Didn't Make Sense for Startups

Six months ago, we encountered a problem with no clear solution. We were building an AI agent inside a startup. When customer conversations were flowing in, we started looking for privacy tools that could keep up. Everything we found fell into one of three buckets: Somewhere in the middle of this, we caught ourselves looking for a simple, affordable way to mask data before it hits AI systems.

How Enterprise CPG Companies Can Safely Adopt LLMs Without Compromising Data Privacy

A major publicly traded CPG company wanted to adopt LLM to improve performance marketing, analytics, and customer experience. However, the IT team blocked AI usage and uploads to external AI tools as interacting with public AI models could expose sensitive brand, consumer, and financial data. This isn’t an isolated problem. It’s a pattern across enterprises: business agility collides with security requirements.

Why Removing Document Metadata Matters

Most people consider a document only as words, numbers, and images that are presented on their screen. They think that when they export a file to PDF or attach it to an email, what is visible is all that exists. However, digital documents have a lot more information beneath the surface that are not visible to the casual eye but can be easily accessed by anyone who knows how to find them. The hidden layer of a document is called metadata, and it is much more important in data security than a lot of organizations acknowledging.

How Quantum Computing Will Change Encryption and Data Privacy

Quantum computing is one of the most revolutionary technological frontiers of the 21st century. Built on the principles of quantum mechanics, it has the potential to solve computational problems that are practically impossible for classical computers. While this unlocks tremendous opportunities in science, healthcare, and artificial intelligence, it also poses a significant threat to the cybersecurity systems that protect global data infrastructure. As nations, companies, and cyber-criminals race toward quantum supremacy, the world is forced to reconsider the future of encryption, trust, digital privacy, and secure communication.

Protecting Your Privacy: Tips for Managing Phone Recordings

Your smartphone can capture sound with incredible clarity. Conversations, meetings, even quick reminders-everything can be recorded in seconds. But with this convenience comes a serious question: How safe are your recordings? In today's digital world, privacy protection has become one of the most discussed and crucial topics. Reports show that over 60% of smartphone users have used recording features at least once, often without realizing how much personal data those recordings may contain. Voices, locations, background sounds-all can reveal sensitive information.

5 Critical LLM Privacy Risks Every Organization Should Know

Large language models take in unstructured data. They transform it into context, embeddings, and answers. That journey touches raw files, vector stores, model logs, and third-party services. Traditional privacy programs focus on databases and forms. LLMs push risk to the edges. The riskiest moments are when you ingest messy content, when your system retrieves chunks to support an answer, and when an agent with tool access is tricked into over-sharing.

Mastering LLM Privacy Audits: A Step-by-Step Framework

Language models now touch contracts, tickets, CRM notes, recordings, and code. That means personal data, trade secrets, and regulated content move through prompts, embeddings, caches, and third-party endpoints. If your audit still reads like a generic security review, you will miss the places where leaks actually happen. A modern LLM Privacy Audit Framework starts where the risk starts.

BYOD management for privacy-conscious healthcare providers

What's more convenient than having access to your work apps on your personal device? Especially in healthcare, where physicians can avoid juggling between multiple devices during care delivery and just stick to that one device for all needs—both professional and personal. This convenience is one of the reasons for increased adoption of mobile devices among healthcare organizations.