📊 Webinar Alert: Don’t miss your chance to learn which LLMs are ready for the SOC frontline—and which ones still need training wheels.
🏆 Real-World Ready: Simbian’s AI SOC Agent wins “AI Agent Product of the Year”—proving that autonomous investigations aren’t just possible, they’re production-grade.
🧠 New Feature Drop: Transparent AI investigations—see what the SOC Agent did, why it did it, and how it got there..
🎙️ Benchmarking Reality: Tech Field Day hosts unpack how Simbian’s AI SOC Leaderboard cuts through the hype to reveal where LLMs deliver in the SOC.
📰 Industry Buzz: AI pentesters go pro, zero-click Copilot exploit rattles M365, and LLMs take the wheel on CTI automation.
Get an inside look atSimbian’s AI SOC LLM Leaderboard—a groundbreaking benchmark that puts today’s leading language models to the test across real-world security tasks: investigating kill-chain alerts, writing code, and reasoning through complex evidence like seasoned analysts.
If you're evaluating AI for your SOC, this is your chance to get ahead of the curve—and make informed choices before the rest of the industry catches up.
Simbian’s AI SOC Agent has been named the 2025 “AI Agent Product of the Year” by TMC—marking a major milestone not just for us, but for the entire security industry.
The recognition validates that autonomous alert investigation is ready for real-world deployment—not just demos. It also affirms that LLM-driven agents can meaningfully reduce analyst toil without compromising security. Most importantly, it reinforces that AI can be trusted to keep up with today’s nonstop threat landscape.
Huge thanks to our customers, analysts, and competitors who helped push us—and the industry—forward.
For AI to thrive in the SOC, explainability isn’t a “nice-to-have”—it’s table stakes. Security teams need to understand not just what the AI did, but why it made those decisions.
That’s why Simbian’s SOC Agent delivers explainability through three distinct yet complementary lenses:
Verdict Reasoning offers clear, human-readable justifications for each decision the AI makes—so you’re never left guessing why WHY an alert was marked benign or malicious.
Execution Graphs reveal the internal workings of the AI Agent—what data it pulled, how it analyzed the relationships, and the path it followed to reach a conclusion.
Timeline View reconstructs the full chain of events from the environment, helping analysts visualize the threat flow for reporting, response, and root cause analysis.
We have rolled this out to our customers, and it is a big hit! Analysts feel very confident standing by the decisions of Simbian’s AI SOC Agent, even when it differs from their initial gut, thanks to the detailed explanation.
You get transparent, traceable logic for every alert that Simbian investigates. Because when the stakes are high, you don’t want a black box. You want a second brain that shows its work.
The goal: spotlight where AI truly adds value—by accelerating routine work, not replacing human analysts. Simbian’s approach emphasizes transparency, hands-on testing, and helping companies choose AI tools based on performance, cost, and real-world value—not hype.
XBOW’s AI Pentester Tops HackerOne Leaderboard—XBOW, an autonomous AI pentesting engine, has surged to the top of the HackerOne leaderboard, outperforming human hackers with precision and scale. This blog unpacks the strategies, architecture, and automation behind XBOW’s rise—signaling a major shift in offensive security. 🔗 Read more
EchoLeak: The First Zero-Click AI Prompt Injection in Microsoft 365 Copilot – AIM Security exposes a groundbreaking vulnerability—EchoLeak—that exploits AI copilots through zero-click prompt injections, enabling silent data exfiltration from Microsoft 365 environments. The post walks through the mechanics, risks, and defensive considerations around securing LLM-integrated enterprise platforms. 🔗 Read more
Building a Smarter CTI: How LLMs Power Automated Threat Intelligence Graphs: This article presents an innovative framework that leverages large language models (LLMs) to automatically generate cyber threat intelligence (CTI) knowledge graphs from unstructured threat reports. The system extracts entities, relationships, and indicators to form structured, actionable intelligence—offering a scalable, low-latency solution for modern threat detection and response. 🔗 Read more
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