Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Why You Must Still Review AI Code

Jul 13, 2026 By Snyk In Snyk
In this video, we break down why skipping code reviews is a massive mistake that will ultimately slow you down, leave you vulnerable, and compromise your system's accountability. We dive into three concrete reasons why reviewing AI-generated pull requests actually makes you a faster, safer developer, including a real-world story of a production bug caught in under 90 seconds. Resources Chapters.
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kovrr

How Organizations Can Assess and Manage AI-Related Risks

Jul 13, 2026 By Kovrr In Kovrr
Organizations assess and manage AI-related risks by establishing a cross-functional governance framework, mapping risks based on impact and financial likelihood, and instituting continuous monitoring that connects AI asset discovery to risk quantification, compliance, and enforcement. The most effective programs treat AI risk management not as a one-time assessment but as a continuous, data-driven discipline that evolves alongside the AI systems it governs. ‍
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What Server Do You Need to Run an AI Language Model?

What Server Do You Need to Run an AI Language Model?

Jul 13, 2026 By SecuritySenses In SecuritySenses
Running your own AI model sounds exciting, but one question appears almost immediately: what kind of server do you actually need? A small language model can run on a personal workstation, while a large 70B parameter model may require enterprise-grade GPUs and expensive infrastructure. Choosing the wrong hardware can lead to wasted money, unnecessary complexity, or disappointing performance.
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kovrr

What AI Governance Tools Exist in the Market Today

Jul 12, 2026 By Kovrr In Kovrr
‍AI governance tools are software platforms designed to help organizations manage AI risks, ensure regulatory compliance, and enforce responsible AI use across the machine learning lifecycle. The market has expanded rapidly, and in 2026 it includes tools spanning compliance automation, model observability, data governance, infrastructure security, and integrated risk quantification.
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The Safety Problem Nobody Warns You About When You Start Training a Language Model

The Safety Problem Nobody Warns You About When You Start Training a Language Model

Jul 12, 2026 By SecuritySenses In SecuritySenses
There's a version of the LLM safety conversation that stays comfortably abstract - AI alignment, existential risk, theoretical failure modes that matter at a scale most organizations will never reach. That conversation is important, but it's not the one most product and technology leaders need to be having right now. The one they need to be having is more immediate and considerably more practical: how the specific decisions made during llm training services directly shape whether the model you deploy is one your organization can actually stand behind.
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egnyte

Latency Lessons From Building a ReAct AI Agent for Agentic Search

Jul 10, 2026 By Sameer Rastogi In Egnyte
Egnyte AI surfaces insights from an organization's documents for regulated industries—life sciences, financial services, architecture, engineering, and construction—and does that within existing permissions and compliance controls. Our AI Assistant is the conversational front door. Ask a question about your documents in plain language, summarise a contract, find the latest version, pull a compliance clause, and get an answer grounded only in the files you're permitted to see.
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upguard

Best Tools for Securing MCP and LLM Integrations

Jul 10, 2026 By Lance Turner In UpGuard
Shadow IT used to mean employees spinning up unsanctioned software-as-a-service (SaaS) apps that stored company data without approval. Today, shadow MCP and unsanctioned LLM integrations represent the next evolution, and they're more dangerous. Model context protocol (MCP) servers don't merely store data; they act on it, executing code, calling APIs, and accessing internal tools on behalf of AI agents that developers connect with a config file.
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Your Firewall Rules Are Drifting Right Now. You Just Can't See It

Jul 10, 2026 By Reach Security In Reach Security
Firewalls are the single most common source of misconfiguration-related breaches, yet they get changed a hundred times a week and audited once a quarter. This is the network security gap AI attackers exploit first. Endpoint gets the budget. Identity gets the roadmap. The firewall gets changed constantly and reviewed rarely. It is also the control most tied to breaches: 42% of security teams pinned a firewall misconfiguration to a breach or near miss last year, ahead of EDR at 40% and identity at 39%.
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cyberhaven

How to Secure AI Agents in the Enterprise: A Practical Guide for CISOs

Jul 10, 2026 By Aman Sirohi In Cyberhaven
Building guardrails for AI agents sounds like a policy problem but it is actually a data problem. You cannot enforce boundaries on behavior you cannot see. And you cannot govern identity for actors you have not discovered. That dependency chain is what most enterprise security programs miss in 2026, and it is where exposure quietly accumulates. A human employee who mishandles sensitive data creates a containable event. An AI agent with the same permissions creates a different problem.
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