Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Why AI Is Becoming an Operational Requirement for Security Teams

In our previous article, From Vulnerability Management to Continuous Security Operations, we explored how organizations are moving beyond traditional vulnerability management toward a model built on continuous visibility, continuous prioritization, and continuous action. But that evolution raises an important question: how do security teams sustain this model at scale? For years, the cybersecurity industry focused on visibility.

AI Analysts for Autonomous Vulnerability Response

Security teams are drowning in findings, not because scanners miss things, but because nothing confirms which ones an attacker could actually reach. Seemplicity AI Analysts run the investigation themselves, checking runtime configuration, network reachability, and exploit conditions for each finding, and re-rank your backlog by confirmed exploitability. What rises to the top is backed by evidence. What drops down has been checked and reasoned out.

Not Zero-Days. Not Nation-States. A Firewall Rule.

A firewall's entire job is to control what gets in. In Reach's research, it was the most common source of a configuration-related near miss or exposure, ahead of EDR and identity controls. It does not take much. One rule broadened for a project, one exception that outlived its reason, one change that shipped without anyone checking it against intent. A single overly permissive rule, sitting live between quarterly reviews, is enough.

6 Key Elements of a Responsible AI Usage Policy

Recently, I had the pleasure of presenting an AI governance-focused webinar with my colleague Neil Jones at Egnyte. In the session, we discussed many ways to improve AI governance, and you can watch and share the complete session replay here. During the session, we discussed the importance of respo nsible AI usage policies. However, my experience is that many organisations struggle to create policies aligned with their business requirements and the technological solutions that they use.

How JFrog and NanoClaw are Bringing Software Supply Chain Security to the Age of Autonomous AI

There’s a category of security risk that most organizations aren’t ready for. It doesn’t live in your code repository, your CI pipeline, or your developer laptops. It lives in your runtime, in the autonomous AI agents already running in your environment, extending their own capabilities, and making decisions that no human explicitly approved. This is the challenge JFrog set out to address with our integration with NanoCo AI and their open-source agent framework, NanoClaw.

Why Uniform Governance Fails with Enterprise AI Agents (And How to Fix It)

As organizations aggressively shift from static Large Language Model (LLM) chatbots to fully dynamic, autonomous AI agents (e.g. systems designed to plan workflows, call APIs, write runtime code, and modify enterprise databases), traditional compliance and governance frameworks are hitting a breaking point. A landmark press release from Gartner highlights a critical systemic risk: treating AI agent governance as a monolithic, one-size-fits-all policy guarantees project failure.

A Step by Step Guide to Creating Realistic Instagram Post Mockups for Presentations

A realistic Instagram post mockup can make a presentation easier to understand, especially when a campaign idea is still being reviewed. Instead of showing a loose image, a caption in a separate file, and notes in a slide, the post can be shown in a format that feels close to the final Instagram layout. This helps agencies, SMM specialists, designers, and brand teams discuss creative choices with less confusion. A good mockup is not about pretending that something was published, but about showing how a post may look before approval, portfolio use, or campaign planning.

TITAN AI Demo Series: How AI Agents Automate KEV Remediation

Most security teams find out about a critical vulnerability after it's been added to CISA's Known Exploited Vulnerabilities (KEV) catalog. By then, the clock is already running. In Episode 3 of SecurityScorecard's Demo Tuesday series, see how TITAN AI Agents automate KEV remediation workflows — so your team spends less time triaging and more time closing exposures. Watch to learn how to: Instantly identify which vendors in your ecosystem are exposed to KEV-listed vulnerabilities.