Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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Privacy in Enterprise AI: Why It's the Foundation, Not a Feature

Apr 27, 2026 By Amar Kanagaraj In Protecto
Last week, OpenAI released Privacy Filter, an open-weight model for detecting and redacting PII in text. It is a thoughtful release: Apache 2.0 licensed, able to run locally, designed for high-throughput workflows, and built to go beyond regex-based detection. This is good news for everyone building enterprise AI. Privacy at the model layer is getting real attention. What we liked most was how clearly OpenAI described the role of the model.
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What Is Generative AI Security? Key Risks and How to Fix Them

Apr 24, 2026 By Mariyam Jameela In Protecto
Generative AI security is the practice of protecting the data that flows into AI systems, and the outputs those systems produce, from leaks, attacks, and unauthorized access. Every organization using AI today has the same blind spot. Sensitive data enters an AI pipeline, and most security teams have no visibility into where it goes next. An employee pastes a customer record into ChatGPT. A developer submits code containing API keys to an AI debugging tool.
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What Is AI Agent Security? Threats, Risks, and What Actually Stops Them (2026)

Apr 22, 2026 By Mariyam Jameela In Protecto
Over two-thirds of enterprises are already running agentic AI in production, according to a 2025 industry survey on the state of agentic AI security. Fewer than one in four have the visibility to know what those agents are actually doing. That gap is live right now, in systems handling customer data, financial records, and protected health information.
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Why AI Security Needs More Than One Tool #shorts #ai

Apr 20, 2026 By Protecto In Protecto
Why AI security needs more than one tool Most teams believe a single cybersecurity tool—like WAF, EDR, or API security—is enough to protect their AI systems. But that approach is outdated. AI security is not one layer—it’s a full stack problem. Discovery – Identify Shadow AI and unknown AI usage Build-Time Security – Prevent data poisoning & model risks (MLSecOps) Runtime Security – Stop real-time AI attacks and agent misuse Governance (AISPM) – Ensure visibility, compliance, and policy control.
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Types of AI Guardrails and When to Use Them (2026)

Apr 18, 2026 By Mariyam Jameela In Protecto
The types of AI guardrails are input guardrails, output guardrails, security guardrails, ethical guardrails, and operational guardrails, each positioned at a different failure point across an inference pipeline. Gartner’s research found that 30% of generative AI projects don’t survive past the proof-of-concept stage, with weak risk controls cited as the leading reason. Most of those projects weren’t badly built. The models worked. The gaps were in what sat around them.
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What Is AI Context Security?

Apr 17, 2026 By Amar Kanagaraj In Protecto
Every enterprise wants to use AI on its most valuable data — customer records, financial documents, clinical notes, legal files, engineering IP. The problem is simple: the moment that data enters an AI workflow, traditional security stops working. Firewalls protect the network. Encryption protects data at rest. Access controls protect the database. But none of them protect what happens when an AI agent retrieves five documents, synthesizes an answer, and delivers it to a user.
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How to Secure AI Agents Accessing Enterprise Data: A Complete Guide

Apr 16, 2026 By Sakshi In Protecto
Artificial intelligence is changing how a business handles its operations, and that too very rapidly. AI agents can easily read, analyze, and act on enterprise data in real time. This ease also brings serious risk. If not managed well, these systems can expose sensitive information, break compliance rules, or even make harmful decisions. Did you know that on average, the overall cost of a data breach reached $4.45 million in 2023?
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Why Your Security Tools Are Useless Against AI?#short #ai

Apr 15, 2026 By Protecto In Protecto
Most companies believe their security tools—WAF, EDR, API gateways—are enough to stop cyber attacks. But AI has changed the game. AI-powered attacks: –Learn your security patterns–Adapt in real-time–Bypass traditional defenses These tools were built for a predictable world. AI attackers are non-stop, intelligent, and evolving. That’s why even the best security systems are failing against modern AI threats.
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7 Generative AI Security Risks and How to Defend Your Organization

Apr 14, 2026 By Mariyam Jameela In Protecto
Generative AI creates new attack surfaces that traditional security tools were not designed to address. The biggest generative AI security risks include prompt injection, data leakage, shadow AI, compliance exposure, model poisoning, insecure RAG pipelines, and broken access control. Each one requires a specific defense, not a generic firewall or DLP rule.
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