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At some point in the last decade, SIEMs turned into that one friend who always promises to help you move, then shows up late, eats all your pizza, and still expects gas money. They were supposed to deliver centralized visibility and faster investigations. Instead, most SOC teams ended up with endless alerts, eye-watering bills, and dashboards that look impressive on the big screen but don't actually stop attackers. So, how did we end up here? A short history: when SIEMs were actually useful Back when firewalls were still exciting, SIEMs solved a real problem: logs scattered everywhere, auditors breathing down your neck, and no way to answer "who logged into what, when?" Then came the "next-gen" era. Vendors promised smarter detection, correlations across your stack, and even a pinch of threat intel. The promise was fewer false positives and a faster response. But instead of taming noise, NG SIEMs just amplified it. It was like turning up the volume on a broken radio and calling ...

Security teams today live in two different realities. On one side, platforms like ServiceNow create order: every vulnerability has a ticket, every incident has a workflow, and everything ties back to the CMDB. On the other side, attackers create chaos. They don't follow workflows. They look for the easiest way in, chaining together whatever exposures they can find until they reach something valuable. A vulnerability marked as "medium" in a ticketing system can still be the critical link in an attack path that leads straight to a company's crown jewels. In the ticketing system, the issue appears in isolation, yet attackers see how it connects to everything else. Without visibility into how exposures link together, teams risk wasting effort while the actual attack paths stay open. This is where ServiceNow's integration with XM Cyber comes in. By layering attack graph analysis onto VR and SIR , the platform lets teams see each issue through an attacker's eyes. Tickets and incidents ar...

ShinyHunters is a notorious cybercrime group that has resurfaced with a new playbook of SaaS-focused attacks. Known for monetizing stolen data on underground forums since 2020, ShinyHunters has historically breached companies by stealing credentials and databases. Recently, however, they've shifted tactics to aggressive social engineering, mirroring the methodology of the Scattered Spider group. Instead of exploiting software vulnerabilities, ShinyHunters now exploits human trust, targeting the underbelly of third-party SaaS platforms through impersonation and phishing. In mid-2025, a wave of breaches struck companies like Google, Workday, Pandora, Cisco, Chanel, and others, all tied together by one common thread: the attackers leveraged access to these firms' Salesforce CRM or similar cloud systems. Below, we look at what happened in the Google and Workday breaches, examine techniques ShinyHunters used, and demonstrate how a dynamic SaaS security approach (like Reco's) could have...

In early 2025, Russian state-backed threat group Secret Blizzard targeted foreign embassies with a man-in-the-middle (MITM) attack that bypassed MFA. Instead of sending phishing emails or dropping malware, they compromised the root of trust on embassy systems — the mechanism that determines which connections and certificates are trusted. By controlling local internet infrastructure inside Russia, Secret Blizzard: Used that certificate to impersonate legitimate websites without triggering browser warnings. Intercepted "secure" traffic to harvest session tokens, cookies, and credentials — without detection. High-signal takeaway: A root-of-trust compromise undermines all Transport Layer Security (TLS)-based protections, including FIDO-based MFA. Why Traditional MFA and FIDO Fail Against This Attack Seemingly secure MFA assumes secure TLS connections. When TLS is compromised via a rogue root certificate, the browser happily connects to an attacker-controlled endpoint. This break...

AI-powered coding assistants now play a central role in modern software development. Developers use them to speed up tasks, reduce boilerplate snippets, and automate routine code generation. But with that speed comes a dangerous trade-off. The tools designed to accelerate innovation are degrading application security by embedding subtle yet serious vulnerabilities in software. Nearly  half of the code snippets generated by five AI models contained bugs that attackers could exploit, a study showed. A second study confirmed the risk, with nearly one-third of Python snippets and a quarter of JavaScript  snippets produced by GitHub Copilot having security flaws . The problem goes beyond flawed output. AI tools instill a false sense of confidence. Developers using AI assistance not only  wrote significantly less secure code than those who worked unaided, but they also believed their insecure code was safe, a clear sign of automation bias. The Dangerous Simplicity of AI-...

Imagine joining a video call with your CEO, only to find out later the CEO participant was actually an AI-generated fake. Welcome to the new digital battlefield.  Adversarial AI and deepfakes have created an identity attack surface that is not just digital, but is also based on reality itself . These technologies are no longer science fiction or theoretical. They are actively being used to spoof identities, manipulate political perceptions, and circumvent even the best cybersecurity training initiatives. , and circumvent even the best cybersecurity training initiatives.  If your cybersecurity defenses rely solely on human perception, voice recognition, or even visual evidence, you are vulnerable to an attack.  From Cat and Mouse to Machine vs. Machine Cybersecurity has always been a game of cat and mouse. As defenders (mice), we have historically been able to adapt our defenses for phishing, malware , ransomware, and insider threats . Today, we're also strategizing ...

Device and software vulnerabilities pose an increasing risk to modern security. However, patch management is an infamously difficult (and downright Sisyphean) task for IT and security teams, who are faced with an ever-growing list of CVEs to remediate. This task was difficult enough in the days of on-premise environments, but a modern distributed workforce has to contend with all the users, devices, and applications that may exist outside the purview of traditional security solutions, like MDM. Overall, with the ever-growing number of CVEs and the ever-growing sprawl of shadow IT, patch management has become both more urgent and more daunting than ever. IT and security teams need to adopt zero trust methods to ensure that only healthy and patched devices are able to access their critical systems. With the help of SaaS management and employee-remediation tactics, teams can do even more to improve efficacy and support for their company-wide patch management programs.  French philo...

Automated tools give you visibility. Adversarial testing gives you clarity. In Salesforce environments, you need both. The Problem with Checkbox Security in a Platform-Centric World Salesforce has become more than just a CRM—it's the backbone of how many organizations operate. It holds customer data, governs workflows, drives revenue, and connects to dozens of internal and third-party systems. But that complexity is exactly what makes it hard to secure. And too often, security teams rely solely on generic scans or scheduled audits that were never designed to handle the nuance of Salesforce's layered permissions, custom logic, and evolving integrations. The result? A lot of surface-level findings—and a lot of assumptions about what those findings actually mean. Automation Is Essential—But It's Only One Layer There's no question that modern scanning tools play a vital role in Salesforce security. The right platforms can surface deeply nested permissions, cross-object access paths,...

Generative AI has quietly become a part of the SaaS ecosystem that businesses use every day. Platforms like Zoom, Slack, Microsoft 365, and Salesforce now have AI assistants. You can use these tools to do things like write summaries of meetings or perform routine tasks. A recent  survey found that 95% of U.S. businesses now use generative AI. This is a big increase from last year. But this quick growth of AI features is making security leaders worried. Sensitive information could be leaked or used in the wrong way if there aren't enough controls in place. Shadow AI and Its Far-Reaching Risks When employees use AI apps without the knowledge or approval of IT, it creates shadow AI . This is akin to the shadow IT problem of unsanctioned cloud apps, but now with AI services. The unauthorized use of AI platforms can unknowingly expose organizations to data privacy issues, compliance violations, and even disinformation risks. We're already seeing these risks play out. Samsung engin...