Best Detection Methods for Security Risks

Reality check: Your SOC might be missing critical threats while drowning in alert noise. I've learned that robust threat detection isn't about throwing more tools at the problem—it's about mastering the fundamentals of detection engineering that separate reactive SOCs drowning in noise from proactive SOCs identifying and stopping threats in their tracks. So, where do you start? Here are 4 non-negotiable foundational detection engineering practices I’ve used in building SOC teams: 1. Atomic-Level Detections: Zoom in on specific adversary actions with focused, high-quality detections. Think behavioral and signature-based detections that provide actionable signals. 2. Detection-as-Code (DaC): Bring the power of software engineering to your detection pipeline. Version control, deployment pipelines, change control, auditing—you name it, DaC has got it covered for consistency and structure.  3. Contextual Enrichments: Go beyond simple alerts. Tag relevant context like MITRE techniques, threat groups, and entity info to help analysts quickly profile threats and make informed decisions.  4. Structured Detection Outputs: Standardize your detection outputs with consistent naming, data structures, and rich context. Make life easier for downstream analysis and triage. Without these fundamentals, you're building a house on sand. But by focusing on these foundational practices, you can build purpose-driven detections that fuel effective response to sophisticated threats. If you didn’t catch my latest blog on this topic, you can tune in via the link in my comments.

As a SOC Analyst, one of the biggest milestones in my journey was the first time I wrote my own detection rule. Until then, I had been: Investigating alerts Escalating when needed Documenting incidents Learning from the existing rules and playbooks But one day, I saw a pattern: A certain type of PowerShell behavior kept slipping through the cracks—not malicious enough to trigger a default rule, but definitely suspicious. So I asked myself: "What if I created a custom rule to catch this behavior more effectively?" Here’s what I did: I pulled together examples of that PowerShell usage Reviewed existing detection content for similar activity Built a custom query in the SIEM using logical conditions and filters Set up test runs to avoid false positives Documented it, shared with the team, and finally deployed it into production A week later, that rule helped us spot a misconfigured script that had access to sensitive files. It wasn’t a breach—but it could have become one. What I learned: Detection engineering is not just technical, it’s investigative thinking Writing your own rules forces you to understand both attack patterns and normal behavior Small contributions like this make a big difference in a real-world SOC environment I didn’t need to be a senior to create value—just observant and willing to try If you’re early in your cyber career, I encourage you to experiment with detection logic. Start small. Learn how rules work. Ask questions. You might be surprised at what you can build. Every great detection starts with a curious analyst. #Cybersecurity #SOCAnalyst #DetectionEngineering #SIEM #ThreatDetection #BlueTeam #HandsOnSecurity #InfosecGrowth #CyberCareer

Signature-based detection is a relic. The SharePoint "ToolShell" breach is one of the most important case studies this year for why threat detection needs to evolve. Last week, Microsoft issued an emergency fix for CVE-2025-53770, a zero-day vulnerability in on-prem SharePoint servers. Attackers used custom exploit code to gain unauthenticated remote code execution, steal ASP.NET machine keys, and install a modular post-exploitation framework now referred to as ToolShell. The scope is serious-victims include U.S. federal agencies, universities, and major enterprises. Even more concerning: patching may not be enough. If an attacker has already stolen your machine keys, they can maintain access even after updates are applied. This breach highlights a few key realities: 👉 Exploits are increasingly built to evade signature-based detection. 👉 Post-compromise persistence is getting harder to spot, especially in large hybrid environments. 👉 Timely patching is necessary, but no longer sufficient on its own. What's needed is broader visibility and more adaptive detection. The best security teams I know are rethinking their approach to threat hunting. Instead of waiting for alerts, they’re proactively investigating for signs of abuse, especially in gray zones like unusual API behavior, lateral movement, or anomalous key usage. These are hard problems to solve with traditional tools. You need correlation across systems, behavioral context, and the ability to respond faster than human triage alone allows. Whether that’s supported by smarter automation, detection engineering, or emerging AI capabilities, the direction of travel is clear: we’re moving toward more continuous, contextual threat detection. ToolShell won’t be the last reminder. But it’s a timely one.

Today, the Cybersecurity and Infrastructure Security Agency, in collaboration with Australian Cyber Security Agency and other U.S. and international partners, published Best Practices for Event Logging and Threat Detection, a guide to help organizations define a baseline for logging to improve an organization’s resilience and mitigate malicious cyber threats. The guidance is of moderate technical complexity for senior information technology decision makers, operational technology (OT) operators, network administrators, network operators, and critical infrastructure providers within medium to large organizations. Written for those with a basic understanding of event logging, the best practices and recommendations cover cloud services, enterprise networks, enterprise mobility, and OT networks.    The key factors organizations should consider when pursuing logging best practices are:   (1) Enterprise approved logging policy;   (2) Centralized log access and correlation;   (3) Secure storage and log integrity; and   (4) Detection strategy for relevant threats.    Organizations are encouraged to review the best practices in this guide and implement recommended actions which can help detect malicious activity, behavioral anomalies and compromised networks, devices, or accounts. #Cybersecurity #JCDC