Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

A Look At GitGuardian's ML-Powered Contextual EnrichmentAnd Incident Scoring

Apr 14, 2026 By GitGuardian In GitGuardian
In this quick introductory video, Mathieu Bellon, Senior Product Manager at GitGuardian, sits down with Dwayne McDaniel, Developer Advocate, to cover some of the advancements GitGuardian has made by integrating machine learning directly into the secrets security platform. Mathieu describes how engineers and responders can save serious time as by automating contextual analysis, geving the humans in the loop with the best information to be able to take an informed action when it comes to secrets leaks. They also discuss the security implications and where teams can look if they want to opt out or bring their own agents.
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protecto

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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teramind

How to Track and Monitor Employee AI Usage

Apr 14, 2026 By Teramind In Teramind
Artificial intelligence is rapidly moving from an experimental phase to a fundamental business requirement. While tools like ChatGPT can turn hours of data analysis into minutes of work, they also introduce a new era of Shadow IT and data security risks. If you’re concerned about sensitive spreadsheets being uploaded to third-party AI or want to ensure your team is seeing a true return on investment, you need a clear strategy for monitoring employee AI usage.
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cyberhaven

Best Enterprise DLP Tools for AI Data Risk (2026 Comparison)

Apr 14, 2026 By Cyberhaven In Cyberhaven
Employees move sensitive data into AI tools every day. Someone pastes customer records into ChatGPT to draft an email. A developer feeds proprietary source code into a coding assistant to fix a bug. A project manager drops a confidential contract into Gemini to summarize it for a meeting. According to research from Cyberhaven Labs, 39.7% of the data employees share with AI tools is sensitive, and enterprise adoption of endpoint-based AI agents grew 276% in the past year alone.
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tanium

Understanding shadow AI in your endpoint environment

Apr 14, 2026 By Tanium In Tanium
Generative AI–and large language models in particular–reached mass consumer adoption beginning in late 2022 and early 2023, with ChatGPT reaching 100 million users faster than any consumer application in history. Since then, AI has advanced at a breakneck pace and now seems to be incorporated in every tool, app, and website–regardless of how useful it might actually be.
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LimaCharlie

Claude Code Cuts SOC Setup to 10 Minutes

Apr 13, 2026 By LimaCharlie In LimaCharlie
Security teams accept that standing up a real SOC requires days of configuration, credential wrangling, and infrastructure work before any actual security engineering begins. With LimaCharlie, actual setup time is closer to ten minutes. It gives valuable time back to SecOps teams by managing infrastructure and simplifying onboarding and operations with Claude Code. Using agentic AI to deploy SOC capabilities means your team spends less time on infrastructure and more on security work.
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salt security

Everyone Is Securing the Wrong Layer of AI

Apr 13, 2026 By Michael Callahan In Salt Security
The AI security market is crowded. Vendors are racing to protect prompts, harden models, detect jailbreaks, and scan for data leakage at the LLM layer. The investment is real. The intent is good. And most of it is missing the point. Here is the problem: agents do not just think. They act. They call APIs. They trigger workflows. They write to databases, send emails, move money, and modify production systems.
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