Cloud security teams are entering 2025 facing a new kind of imbalance-one where attackers aren’t necessarily getting louder, they’re getting quieter. In a recent Forbes feature, “Threat Hunting Vs. Threat Detection: The Unseen Battle In The Cloud In 2025,” Anshu Bansal, CEO of CloudDefense.AI, outlines why many organizations still struggle to protect cloud assets even after investing heavily in modern security stacks. His central argument is that the problem isn’t the absence of tools, but the overreliance on reactive security that waits for alerts while adversaries increasingly operate in ways that don’t look obviously malicious.
Anshu explains that threat detection remains the foundation of cloud defense because it provides continuous monitoring and automated alerting across infrastructure. It helps identify common threats like malware, phishing, suspicious network activity, and injection attempts, and it is typically powered by systems such as SIEM platforms, intrusion detection and prevention capabilities, and endpoint protections. But while detection is essential, it often depends on known patterns and rule-driven signals-an approach that can fall short when threat actors use living-off-the-land techniques, exploit valid credentials, or blend into normal behavior to move laterally without raising alarms.
Threat detection tells you what’s already obvious; threat hunting reveals what’s trying hard to stay invisible—and in 2025, that difference is everything”
— Anshu Bansal, CEO of CloudDefense.AI
That gap is exactly where threat hunting becomes decisive. In the Forbes piece, Anshu positions threat hunting as a proactive, hypothesis-led discipline that shifts security teams from waiting on alerts to actively investigating what might have been missed. Rather than assuming the environment is safe until proven otherwise, hunting starts with the possibility that something subtle is already underway and works backward through data, context, and behavior to confirm or disprove it. It pushes teams to ask sharper questions-about abnormal API call sequences, privilege misuse, and suspicious patterns that don’t match known signatures-and it is particularly effective against advanced persistent threats, stealthy persistence, and early-stage indicators of sophisticated intrusions.
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Importantly, Anshu does not frame threat hunting as a replacement for detection, but as the missing counterpart that makes cloud security resilient in 2025. Detection offers coverage and rapid notification, while hunting provides depth, context, and the ability to uncover threats designed to evade automated guardrails. He stresses that organizations gain the most by treating the two as complementary layers of the same strategy, supported by cross-team collaboration between security, incident response, and development functions so investigations translate into stronger prevention, better telemetry, and faster containment.
Anshu also highlights a practical reality that many teams feel every day: the volume of signals is increasing, and the margin for error is shrinking. In that environment, simply adding more alerts doesn’t create better security-it creates fatigue. His view is that organizations must build a hunter’s mindset across the security function while leveraging AI and automation to reduce noise, accelerate analysis, and help teams focus on what truly matters. As cloud security programs mature, success will come from combining always-on detection with continuous, curiosity-driven hunting that challenges assumptions and closes blind spots before attackers can exploit them.
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