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Penetration testing is critical to uncovering real-world security weaknesses. With the shift into continuous testing and validation, it is time we automate the delivery of these results. The way results are delivered hasn't kept up with today's fast-moving threat landscape. Too often, findings are packaged into static reports, buried in PDFs or spreadsheets, and handed off manually to already-overloaded IT and engineering teams. By the time remediation begins, days or even weeks may have passed since the issues were first discovered. As we explored in our recent article on how automation is redefining pentest delivery , static, manual processes no longer cut it. Security teams need faster insights, cleaner handoffs, and more consistent workflows if they want to keep pace with modern exposure management.  That's where automation makes the difference, ensuring findings move seamlessly from discovery to remediation in real time. Where Should You Start? Knowing automation matters...

Running a SOC often feels like drowning in alerts. Every morning, dashboards light up with thousands of signals; some urgent, many irrelevant. The job is to find the real threats fast enough to keep cases from piling up, prevent analyst burnout, and maintain client or leadership confidence. The toughest challenges, however, aren't the alerts that can be dismissed quickly, but the ones that hide in plain sight. These tricky threats drag out investigations, create unnecessary escalations, and quietly drain resources over time. Why Detection Gaps Keep Opening What slows SOCs down isn't the flood of alerts alone but the way investigations get split across disconnected tools. Intel in one platform, detonation in another, enrichment in a third; every switch wastes time. Across hundreds of cases, those minutes add up to stalled investigations, unnecessary escalations, and threats that linger longer than they should. Action Plan That Delivers 3× SOC Efficiency in Threat Detection SOC tea...

AI is changing automation—but not always for the better. That's why we're hosting a new webinar, " Workflow Clarity: Where AI Fits in Modern Automation ," with Thomas Kinsella, Co-founder & Chief Customer Officer at Tines, to explore how leading teams are cutting through the hype and building workflows that actually deliver. The rise of AI has changed how organizations think about automation. But here's the reality many teams are quietly wrestling with: AI isn't a silver bullet. Purely human-led workflows buckle under pressure, rigid rules-based automations break the moment reality shifts, and fully autonomous AI agents risk introducing black-box decision-making that's impossible to audit. For cybersecurity and operations leaders, the stakes are even higher. You need workflows that are fast but reliable, powerful but secure, and—above all—explainable. So where does AI really fit in? The Hidden Problem with "All-In" Automation The push to automate everythi...

The Problem: Legacy SOCs and Endless Alert Noise Every SOC leader knows the feeling: hundreds of alerts pouring in, dashboards lighting up like a slot machine, analysts scrambling to keep pace. The harder they try to scale people or buy new tools, the faster the chaos multiplies. The problem is not just volume; it is the model itself. Traditional SOCs start with rules, wait for alerts to fire, and then dump raw signals on analysts. By the time someone pieces together what is really happening, the attacker has already moved on, or moved in. It is a broken loop of noise chasing noise. Flipping the Model: Context Over Chaos Instead of drowning in raw events, treat every incoming signal as a potential opening move in a bigger story. Logs from identity systems, endpoints, cloud workloads, and SIEMs do not just land in separate dashboards; they are normalized, connected, and enriched to form a coherent investigation. A brute-force login attempt on its own is easy to dismiss. But when enh...

Security leaders are embracing AI for triage, detection engineering, and threat hunting as alert volumes and burnout hit breaking points. A comprehensive survey of 282 security leaders at companies across industries reveals a stark reality facing modern Security Operations Centers: alert volumes have reached unsustainable levels, forcing teams to leave critical threats uninvestigated. You can download the full report here . The research, conducted primarily among US-based organizations, shows that AI adoption in security operations has shifted from experimental to essential as teams struggle to keep pace with an ever-growing stream of security alerts. The findings paint a picture of an industry at a tipping point, where traditional SOC models are buckling under operational pressure and AI-powered solutions are emerging as the primary path forward. Alert Volume Reaches Breaking Point Security teams are drowning in alerts, with organizations processing an average of 960 alerts per ...

Run by the team at workflow orchestration and AI platform Tines, the Tines library features over 1,000 pre-built workflows shared by security practitioners from across the community - all free to import and deploy through the platform's Community Edition. The workflow we are highlighting streamlines security alert handling by automatically identifying and executing the appropriate Standard Operating Procedures (SOPs) from Confluence. When an alert triggers, AI agents analyze it, locate relevant SOPs, and perform required remediation steps - all while keeping the on-call team informed via Slack. It was created by Michael Tolan, Security Researcher L2 at Tines, and Peter Wrenn, Senior Solutions Engineer at Tines. In this guide, we'll share an overview of the workflow, plus step-by-step instructions for getting it up and running. The problem - manual alert triage and SOP execution For security teams, responding to alerts efficiently requires quickly identifying the threat ty...

Phishing-as-a-Service (PhaaS) platforms keep evolving, giving attackers faster and cheaper ways to break into corporate accounts. Now, researchers at ANY.RUN has uncovered a new entrant: Salty2FA , a phishing kit designed to bypass multiple two-factor authentication methods and slip past traditional defenses.  Already spotted in campaigns across the US and EU, Salty2FA puts enterprises at risk by targeting industries from finance to energy. Its multi-stage execution chain, evasive infrastructure, and ability to intercept credentials and 2FA codes make it one of the most dangerous PhaaS frameworks seen this year. Why Salty2FA Raises the Stakes for Enterprises Salty2FA's ability to bypass push, SMS, and voice-based 2FA means stolen credentials can lead directly to account takeover. Already aimed at finance, energy, and telecom sectors, the kit turns common phishing emails into high-impact breaches.  Who is Being Targeted? ANY.RUN analysts mapped Salty2FA campaigns and fo...

Artificial intelligence is reshaping cybersecurity on both sides of the battlefield. Cybercriminals are using AI-powered tools to accelerate and automate attacks at a scale defenders have never faced before. Security teams are overwhelmed by an explosion of vulnerability data, tool outputs, and alerts, all while operating with finite human resources. The irony is that while AI has become a dominant theme in cybersecurity, many enterprises still struggle to apply it effectively within their programs.  The problem isn't access to information, as teams already have more data than they can process. It's cutting through the noise and focusing on what truly matters. AI is crucial here. Not only can it make security teams more efficient, it can generate insights that would be impossible to gather at scale or in real time without machine assistance. If adversaries are already weaponizing AI, then defenders must embed it into their strategies as well or risk falling further be...

Security Information and Event Management (SIEM) systems act as the primary tools for detecting suspicious activity in enterprise networks, helping organizations identify and respond to potential attacks in real time. However, the new Picus Blue Report 2025 , based on over 160 million real-world attack simulations , revealed that organizations are only detecting 1 out of 7 simulated attacks , showing a critical gap in threat detection and response. While many organizations believe they're doing everything they can to detect adversary actions, the reality is that a large number of threats are slipping through their defenses unnoticed, leaving their networks far too vulnerable to compromise. This gap in detection creates a false sense of security when attackers have already accessed your sensitive systems, escalated their privileges, or are actively exfiltrating your valuable data. Which begs the question: why, after all this time, money, and attention, are these systems still ...

Pentesting remains one of the most effective ways to identify real-world security weaknesses before adversaries do. But as the threat landscape has evolved, the way we deliver pentest results hasn't kept pace. Most organizations still rely on traditional reporting methods—static PDFs, emailed documents, and spreadsheet-based tracking. The problem? These outdated workflows introduce delays, create inefficiencies, and undermine the value of the work. Security teams need faster insights, tighter handoffs, and clearer paths to remediation. That's where automated delivery comes in. Platforms like PlexTrac automate pentest finding delivery in real time through robust, rules-based workflows. (No waiting for the final report!) The Static Delivery Problem in a Dynamic World Delivering a pentest report solely as a static document might have made sense a decade ago, but today it's a bottleneck. Findings are buried in long documents that don't align with how teams operate day-to-day. Aft...

Security operations have never been a 9-to-5 job. For SOC analysts, the day often starts and ends deep in a queue of alerts, chasing down what turns out to be false positives, or switching between half a dozen tools to piece together context. The work is repetitive, time-consuming, and high-stakes, leaving SOCs under constant pressure to keep up, yet often struggling to stay ahead of emerging threats. That combination of inefficiency, elevated risk, and a reactive operating model is exactly where AI-powered SOC capabilities are starting to make a difference. Why AI SOC is gaining traction now The recent Gartner Hype Cycle for Security Operations 2025 (download a complimentary copy ) recognizes AI SOC Agents as an innovation trigger, reflecting a broader shift in how teams approach automation. Instead of relying solely on static playbooks or manual investigation workflows, AI SOC capabilities bring reasoning, adaptability, and context-aware decision-making into the mix. SOC teams r...

Just as triathletes know that peak performance requires more than expensive gear, cybersecurity teams are discovering that AI success depends less on the tools they deploy and more on the data that powers them The junk food problem in cybersecurity Imagine a triathlete who spares no expense on equipment—carbon fiber bikes, hydrodynamic wetsuits, precision GPS watches—but fuels their training with processed snacks and energy drinks. Despite the premium gear, their performance will suffer because their foundation is fundamentally flawed. Triathletes see nutrition as the fourth discipline of their training that can have a significant impact on performance and can even determine race outcomes. Today's security operations centers (SOCs) face a similar issue. They're investing heavily in AI-powered detection systems, automated response platforms, and machine learning analytics—the equivalent of professional-grade triathlon equipment. But they're powering these sophistic...

Security Operations Centers (SOCs) are stretched to their limits. Log volumes are surging, threat landscapes are growing more complex, and security teams are chronically understaffed. Analysts face a daily battle with alert noise, fragmented tools, and incomplete data visibility. At the same time, more vendors are phasing out their on-premises SIEM solutions, encouraging migration to SaaS models. But this transition often amplifies the inherent flaws of traditional SIEM architectures. T he Log Deluge Meets Architectural Limits SIEMs are built to process log data—and the more, the better, or so the theory goes. In modern infrastructures, however, log-centric models are becoming a bottleneck. Cloud systems, OT networks, and dynamic workloads generate exponentially more telemetry, often redundant, unstructured, or in unreadable formats. SaaS-based SIEMs in particular face financial and technical constraints: pricing models based on events per second (EPS) or flows-per-minute (FPM) ca...

Run by the team at workflow orchestration and AI platform Tines, the Tines library features over 1,000 pre-built workflows shared by security practitioners from across the community - all free to import and deploy through the platform's Community Edition. A recent standout is a workflow that handles malware alerts with CrowdStrike, Oomnitza, GitHub, and PagerDuty. Developed by Lucas Cantor at Intercom, the creators of fin.ai , the workflow makes it easier to determine the severity of a security alert and escalate it seamlessly, depending on the device owner's response. "It's a great way to reduce noise and add context to security issues that are added on our endpoints as well," Lucas explains. In this guide, we'll share an overview of the workflow, plus step-by-step instructions for getting it up and running. The problem - lack of integration between security tools  For security teams, responding to malware threats, analyzing their severity, and identifying the device owner so...

If you're evaluating AI-powered SOC platforms, you've likely seen bold claims: faster triage, smarter remediation, and less noise. But under the hood, not all AI is created equal. Many solutions rely on pre-trained AI models that are hardwired for a handful of specific use cases. While that might work for yesterday's SOC, today's reality is different. Modern security operations teams face a sprawling and ever-changing landscape of alerts. From cloud to endpoint, identity to OT, insider threats to phishing, network to DLP, and so many more, the list goes on and is continuously growing. CISOs and SOC managers are rightly skeptical. Can this AI actually handle all of my alerts, or is it just another rules engine in disguise? In this post, we'll examine the divide between two types of AI SOC platforms. Those built on adaptive AI, which learns to triage and respond to any alert type, and those that rely on pre-trained AI, limited to handling predefined use cases only. Understanding t...

Security operations centers (SOCs) are under pressure from both sides: threats are growing more complex and frequent, while security budgets are no longer keeping pace. Today's security leaders are expected to reduce risk and deliver results without relying on larger teams or increased spending. At the same time, SOC inefficiencies are draining resources. Studies show that up to half of all alerts are false positives, with some reports citing false positive rates as high as 99 percent . This means highly trained analysts spend a disproportionate amount of time chasing down harmless activity, wasting effort, increasing fatigue, and raising the chance of missing real threats. In this environment, the business imperative is clear: maximize the impact of every analyst and every dollar by making security operations faster, smarter, and more focused. Enter the Agentic AI SOC Analyst The agentic AI SOC Analyst is a force multiplier that enables organizations to do more with the team an...