BlinkOps

AI SOC maturity is not uneven by chance. It is uneven because response remains fundamentally broken. That’s the signal coming through clearly in our latest research. As Sean Sosnowski outlines, most SOC teams have accelerated investigation. The ability to execute safe, governed response has not kept pace. This is the action gap. And it’s where the market is now separating. Across the AI SOC landscape, investigation has converged. Most platforms can summarise, enrich, and build a case. On the surface, they look similar. The difference shows up when you follow the incident further: - Can the platform translate evidence into a defensible decision? - Can that decision be executed within defined authority and constraints? - Can the outcome be verified and proven after the fact? Most platforms break somewhere along that path. This is why maturity remains uneven. Some vendors remain investigation-heavy. Others extend into execution but lack clear governance. A smaller group is building toward a continuous system that connects evidence, decision, authority, execution, and verification. Across the market, you can see these approaches take shape. AI-native platforms like 7AI, Exaforce, Prophet Security, Simbian, AiStrike, Dropzone AI, Qevlar AI, and Radiant Security are pushing deeper into investigation and decisioning. Vendors such as Torq, BlinkOps, Swimlane, and D3 Security bring strength in workflow control and governed execution. Platform players including CrowdStrike, Palo Alto Networks, and SentinelOne are integrating these capabilities across their broader stacks, while others like Intezer, Mate, and Stellar Cyber contribute across different parts of the response path. Different architectures, same constraint. The platforms that close the action gap, even for a narrow set of actions, are the ones that move ahead. For CISOs, the implication is practical. You are not evaluating who investigates best. You are evaluating which platform can take a specific action, under defined authority, and prove the outcome. That’s what defines AI SOC maturity in 2026. Read the full research: https://lnkd.in/dGM4xyqq #AISOC #SecurityOperations #SOAR #CyberSecurity #AISecurity

Multiple recent security incidents documented AI agents breaking into infrastructure and operating at machine speed. Is an AI SOC the answer to attacks moving this fast? Join BlinkOps practitioners Filip Stojkovski (Director of SecOps AI Strategy), Anthony G. Tellez (Principal Sales Engineer), and Joshua Weinick (AI Automation Engineer) for a working session on what the July and August disclosures actually mean for detection engineering. 👇 Join us tomorrow, September 2 at 10am ET

Thinking about adopting AI agents for security? Start micro. Go macro. David Grable breaks it down.

Everyone's worried about agents hallucinating....fair. Here's how we designed around it: the macro-agent doesn't get to go looking for answers on its own. The micro-agents feed it — that's the only input it has. It can't invent what it wasn't given. And everything leaves a trail. Every action, every search, every decision. That's the difference between an AI demo and something you'd actually run in production. David Grable breaks it down:

Most of what's been written about the recent AI agent incidents comes from the attacker's side. Not much from the people who'd actually have to catch it. Filip Stojkovski, Anthony G. Tellez and Joshua Weinick are holding a deeper discussion on September 2 to talk about it from a practitioner's perspective: 👀 Would AI agent defenders have caught this? 👀 What machine-speed offense really changes for detection engineering. 👀 Where agentic SecOps fits, and where it's oversold. If you're trying to protect against this specific failure, the thing to fix isn't detection coverage. It's whether severity can move on its own once evidence starts stacking up on the same entity, host or identity. That's where agentic security micro-agents can add value: they can keep reassessing as the picture changes, and escalate it with a human-in-the-loop. The webinar panel will also touch on how you can assess if your current automation stack set up to defend in this way today. 👇 Register for the webinar below.

A hybrid mid-market SOC does not need another platform transformation. It needs stronger analyst leverage across the environment it already has. In Part 2 of our AI SOC Technoscope Series, Sean Sosnowski evaluates 18 vendors across three operating environments, including the hybrid mid-market SOC: a lean security team working across a mixed SIEM and data-lake architecture. Some key takeaways for hybrid SOC buyers: → Torq, 7AI, and Swimlane form the leading hybrid shortlist, combining cross-stack action with strong case assembly and analyst effectivenes. BlinkOps and Prophet Security also clear both leadership thresholds, with different implementation, reasoning, and maturity tradeoffs. → Palo Alto Networks remains highly capable but brings more platform and consolidation weight. Exaforce performs most strongly when buyers can take full advantage of its data architecture. → Mate, Simbian, and AiStrike show promise in reasoning, investigation, and staged authority, although their production evidence or integration maturity is still developing. → Radiant Security, Intezer, Qevlar AI, and Dropzone AI can provide meaningful analyst value through investigation and evidence assembly, but currently offer narrower governed-response capabilities. → CrowdStrike, SentinelOne, Stellar Cyber, and D3 Security bring established strengths in areas such as native enforcement, Open XDR, case management, orchestration, and governance. However, their platform weight, workflow dependencies, or product fragmentation make them less naturally aligned with the needs of a lean hybrid environment. For security teams, the key question is where the workflow stops. Does the product execute directly, provide a recommendation, trigger an existing SOAR playbook, or rely on a managed service? That handoff determines whether improved investigation translates into less manual coordination and a measurable reduction in time to closure. Read our full analysis here: https://lnkd.in/e6iVWk4K #AISOC #SecurityOperations #SOAR #Cybersecurity

How do you detect AI agents doing bad stuff? Just like Cloud & SaaS used to be unchartered territory, we're here all over again. How do AI agents work? How are they being abused? What are all the techniques that have been documented in the wild? Prompt injection, tool abuse, memory poisoning, cross-agent coordination, excessive agency? Which of this stuff is actually real and what logs do I use to catch this stuff? Do I use Claude Code OTel logs? What about Cowork? Are those the same? What exactly is in Anthropic’s Compliance API? Wait..what about OpenAI, Gemini, Cursor, Bedrock, AgentCore, Microsoft Copilot? This is why we're releasing an initial 36 tradecraft from our research team at Spectrum Security for AI & Agents. These cover some of the most common and newest threats that have been observed: from agents putting malicious instructions into Slack to poisoning MCP configs & skill files. Check out the repo in the comments -->

Intelligence without action is a backlog. Censys sees what's exposed, Blink agents work it end to end. We're so excited about this partnership.🤝

With vibe coding, anyone can build websites and apps - no engineering background required. The Blink Platform brings that same power to security: practitioners at any experience level can now build and deploy agentic workflows without waiting on an engineer. The democratization of software development has arrived in security operations. Zion Zatlavi + Aaron Beveridge