Cole Kunsman

Many SMBs think enterprise scaling requires a "big tech" budget. We're changing that narrative. Datacate uses hyper-converged infrastructure in our owned Sacramento data center to provide Fortune 500 resilience at an SMB price. No middle-men or reselling: just full control over your security, speed, and experience. Stop settling for "good enough" and move to a platform that grows with you. 💡🔐 What’s your biggest challenge when scaling technology? #SacramentoBusiness #ITInfrastructure #HyperConvergence #ManagedServices #SmallBizTech #Datacate

2

We're excited to share one of our most in-depth reports on the Evolution of Modern Risk and Exposure Management Platforms by Aqsa Taylor! Vulnerability management has evolved far beyond scanning for CVEs. In 2025, the conversation has shifted toward continuous, contextual, and validated exposure reduction where risk is no longer measured by how much you scan, but by how effectively you reduce what matters most. Our comprehensive report “Evolution of Modern Risk & Exposure Management Platforms” breaks down this transformation and the technologies driving it. Here are 3 key takeaways from our research: 1. Prioritization is the new battleground. Enterprises don’t struggle to find vulnerabilities anymore; they struggle to know which ones actually matter. Modern platforms now combine exploitability, reachability, and business impact to drive evidence-based risk reduction. 2. Convergence defines the next platform era. Everyone wants to solve exposures. We're seeing lots of vendors from different contextual areas, from the trad VMs, RBVM, ASM, CAASM, but more and more ASPM, CNAPP, Network, and BAS vendors are wanting to merge into unified Risk & Exposure Management ecosystems, integrating discovery, context, remediation, and validation into a single operational loop. 3. There are many, many legacy vendors in this space, but we were impressed by existing vendors like Axonius, Zafran Security, Orca Security and new emerging startups; Astellia, Tonic Security, Cogent Security and, Seemplicity. Many of whom we were to their customers and CISOs to validate their products! The diagram below captures the modern exposure management flow — how today’s programs evolve from: 1️⃣ Vulnerability Management (VM) scanners: Foundational asset and risk discovery 2️⃣ Risk-Based Vulnerability Management (RBVM) hubs: Where prioritization and context take shape 3️⃣ Remediation Operations (RemOps): driven by contextual visibility from CAASM, ASPM, and CNAPP layers 4️⃣ Validation and Reporting: BAS platforms and threat intelligence loops that continuously measure and prove risk reduction Together, they form the foundation of modern risk and threat exposure management (CTEM) platforms. 📘 Read the full SACR report to explore practitioner insights, vendor deep dives, and our step-by-step guide to operationalizing exposure management in your organization. 👉 Read here: https://lnkd.in/ebEHtjph ** Disclaimer: Company logos are not representative of the entire market ecosystem; they depict case studies. *** #Cybersecurity #CTEM #ExposureManagement #RBVM #VulnerabilityManagement #CyberResearch

173

54 Comments

🤔I’ve watched strong products lose serious buyers because security due diligence turns into a dead end. When prospects ask for evidence and receive outdated reports, partial answers, or long response times, confidence fades quickly. The problem is rarely a single critical finding. It’s the lack of clarity and defensible proof when decisions are being made. What consistently shows up is a structural gap. Security programs were built for audits, not for real-time buyer validation. Teams that close enterprise deals treat security evidence as a living system, not a static document. Where does your security due diligence process break down when prospects start asking hard questions? Let’s share perspectives and ideas in the comments.⬇️

7

Here’s a pattern I’m seeing more often: More sites. More assessments. More reporting expectations. Same headcount. Security teams are being asked to scale output without scaling structure. So what happens? Assessments become episodic. Reporting takes too long. Prioritization becomes subjective. And leaders spend more time translating risk than reducing it. This isn’t a capability issue. It’s an architecture issue. At some point, physical security has to operate with the same operational discipline as finance and IT. Otherwise it stays in permanent catch-up mode. For security people overseeing medium to large portfolios (20+ sites): What’s currently your biggest bottleneck volume, visibility, or validation? And why do you think this is?

5

1 Comment

Lance Spitzner wrote about why leadership still misunderstands human risk — and honestly it's one of the most honest takes I've read on why security awareness programs struggle to get traction. The part about compliance metrics vs. real risk metrics? We've all been in that meeting. Worth a read if you're trying to make the case internally for going beyond the checkbox → https://lnkd.in/eRHQF5u3 #SecurityAwareness #HumanRisk

6

Most security and data teams I talk to today are feeling the same pressure: 🔻 SIEM costs are spiraling out of control as data volumes grow 🔻 Queries are slow when you need answers now 🔻 Rigid architectures make scaling painful (and expensive) 🔻 And migrating off legacy SIEMs feels like a massive, risky, time-consuming project Sound familiar? A leading global investment bank was dealing with these exact challenges—and knew the status quo wasn’t sustainable. They turned to Imply Lumi to rethink how they handle real-time analytics at scale: ✔️ Sub-second queries on massive datasets (no more waiting on investigations) ✔️ Cost efficiency that doesn’t punish you for ingesting more data ✔️ Flexible architecture that avoids painful lock-in ✔️ A path forward that doesn’t require a “rip and replace” overnight migration Instead of being stuck managing SIEM limitations, their teams can now focus on actually using data to drive faster decisions. If you’re evaluating alternatives, or just trying to get more out of your current SIEM stack, this is worth a read. 👉 Customer story: https://lnkd.in/eS8CPHjD 👉 Want to explore what this could look like for you? Book time with me: https://lnkd.in/gEfeFtiV #SIEM #CyberSecurity #DataAnalytics #RealTimeData #FinancialServices #Imply

8

TREND VISION ONE Cyber Risk Exposure Management (CREM) Proactively uncover, predict, assess, and mitigate cyber risks—prioritizing impact, reducing exposure, and building cyber resilience The days of reactive security are over. Today’s threat landscape demands a proactive approach, and that’s where Trend Vision One comes in. Imagine seeing your organization’s entire attack surface—every potential exposure, misconfiguration and weakness—and understanding how its impact maps to your business outcomes. With its Cyber Risk Exposure Management (CREM) solution, you can uncover attack paths before they’re exploited, take immediate, meaningful action to strengthen your security and compliance posture and quantify and communicate cyber risk in business terms. It’s not just about managing threats—it’s about building true cyber risk resilience. CREM takes a revolutionary approach by combining key capabilities—like External Attack Surface Management (EASM), Cyber Asset Attack Surface Management (CAASM), Vulnerability Risk Management, and Security Posture Management—across cloud, data, identity, APIs, AI, compliance, and SaaS applications into one powerful, easy-to-use solution. It empowers you to protect your business proactively with control, clarity, and confidence. Learn more: https://spr.ly/6058FDJOn Netpoleon Cambodia

19

2 Comments

OpenClaw, or MoltBot, or Clawdbot, whatever it’s called this week, is the best thing to happen to AI security this year. Yes, the one that’s racked up more security incidents in a fortnight than some vendors have in their entire history. That one. I’ve been watching the security community’s reaction closely. Every major vendor has published their take. Cisco called it a nightmare. Palo Alto said it signals a crisis. Trend Micro warned of invisible risks. You’d think someone had plugged an unpatched Windows XP box directly into the internet. In a hospital. Running the ventilators. Deep breaths, everyone. They’re missing something. OpenClaw is open source. 2 million visitors in a single week, one of the fastest growing projects in GitHub’s history. Developers buying Mac Minis to run it from their spare rooms. Nobody should be running this against production systems or corporate email, and even the project’s own documentation describes it as an experiment not intended for most non-technical users. The creators are being honest about what this is. Which, in this industry, is practically unheard of. And experiments are exactly how security gets better. A researcher found that clicking a single malicious link could hijack an OpenClaw instance in milliseconds, bypassing every sandbox and safety guardrail the project had built. That’s a critical lesson: agentic AI safety controls designed to contain prompt injection don’t protect against architectural vulnerabilities in the control plane. Better to learn that on an open source hobby project than on your enterprise vendor’s agent platform. The 400 malicious skills published to its marketplace showed that AI skill registries have the same supply chain problems as traditional software package repositories, but with broader execution privileges. The early days of cloud computing looked exactly like this. Researchers poking at S3 buckets, finding everything wide open, the industry collectively losing its mind. There was plenty of real damage along the way. And yet somehow we survived, built proper controls, and got on with things. OpenClaw is doing the same thing for agentic AI. Every exposed gateway, every prompt injection chain, every malicious skill is teaching the security community what agentic threat models actually look like in practice rather than in framework documents. Real CVEs, real attack chains, real mitigation patterns against a system people can actually inspect, rather than a black box vendor product. Everyone’s worried about the open source project with 180,000 people scrutinising every flaw. Meanwhile, enterprise agent platforms ship with the same architectural problems. You just don’t get to see them. Your enterprise agent vendor has a trust page and a SOC 2 badge. OpenClaw has 180,000 researchers actually breaking things. Which one do you think finds the problems first? #AISecurity #AgenticAI #OpenSource #CyberSecurity #AIGovernance #ThreatModelling​​​​​​​​​​​​​​​​ #CISO

649

63 Comments

Every cybersecurity team today is under pressure: alerts pile up, threats evolve faster than ever, and analysts are drowning in noise. That’s why I built a workflow that automates security alert triage and remediation, giving SOC teams speed, clarity, and resilience. 🔹 What it does ~Enriches suspicious IPs/domains with real-time threat intel (VirusTotal, AbuseIPDB, etc.) ~Routes alerts by severity, with instant remediation for high-risk cases (firewall updates, account suspensions, endpoint isolation). ~Keeps humans in the loop by escalating high-value incidents for manager approval. ~Logs everything into Airtable/MongoDB with timestamps for compliance and audits. ~Generates AI-powered weekly Threat Landscape Reports for leadership visibility. ~Reduces noise with smart alert grouping, protecting analysts from alert fatigue. 🔹 Why it matters Faster incident response times ⏱️ Stronger compliance + audit trails 📊 Reduced burnout for SOC teams 🔒 Proactive security posture instead of reactive firefighting 🚀 With automation, security isn’t just stronger, it’s smarter.

22