Your cloud tools disagree on 2% of findings, and those are the ones that stall

The consensus deficit in cloud security

The central promise of cloud native application protection platforms (CNAPPs) is the consolidation of signals to provide a definitive view of risk. However, the definition of risk remains subjective even among leading tools. Data from the 2025 State of Cloud Remediation report, which analyzed over 4.76 million alerts, shows that severity levels for the same finding differed across CNAPPs in nearly 2% of the Top 35 dataset.

In one instance, a security group misconfiguration was categorized as "Informational" by two platforms while being flagged as "Critical" by three others. For the operator, this lack of consensus creates a prioritization dilemma. When platforms such as Wiz, Orca, or Prisma Cloud assign different weights to the same vulnerability, the burden of verification shifts back to the security engineer. This negates the efficiency gains promised by a single view of the environment.

The math of the backlog

The operational challenge is further complicated by the volume of high severity alerts. Data indicates that while "Critical" alerts account for 1.36% of total volume, "High" alerts constitute roughly 34%. The High severity queue is 17 times larger than the Critical queue.

By 2026, the situation worsened. The 2026 State of Cloud Remediation report, covering 14.86 million detections across 800 accounts, shows that 53% of detections now remain open, up from 41% in 2025. The mean time to remediate (MTTR) for critical alerts has risen to an average of 150 days, up from under 40 days in 2024. During this period, critical alert volume grew 10 fold, while the speed of remediation slowed, reflected in a 17% increase in MTTR.

Organizations are losing ground. Vulnerability management closure has also slowed by 22%, now taking an average of 282 days. When nearly one fifth of total alert volume is tied to vulnerabilities that take three quarters of a year to resolve, the risk posture of the enterprise becomes fragile.

Restoring a defensible queue

To resolve the discrepancy between tools and the paralysis of the backlog, organizations are shifting toward a remediation centric architecture. Tamnoon functions as an abstraction layer above the CNAPP. By integrating with platforms including AWS Security Hub, Microsoft Defender for Cloud, and CrowdStrike Falcon Cloud Security, Tamnoon deduplicates findings and applies a uniform risk scoring model.

The objective is to move from tool centric severity to asset centric criticality. Only 6.3% of detections touch a "Crown Jewel" asset. By focusing remediation efforts strictly on these high value targets, teams can achieve a defensible posture even if total alert volume remains high.

Tamnoon uses specialized AI agents that answer operational questions: What is the asset? What are its dependencies? Who is the actual owner? What has broken in the past? This context is synthesized into a "Remediation Confidence Score," which classifies a proposed fix as SAFE, RISKY, or AWAITING DATA. This analysis is necessary for moving beyond detection into actual closure.

The role of supervised AI in remediation

The transition from detection to remediation is often stalled by the fear of breaking production environments. CNAPPs surface issues like the failure to enforce IMDSv2 (the most prevalent alert in 2025 at 14.7% of volume), but they rarely provide the operational certainty required to automate the fix.

Tamnoon addresses this through Tami, an AI cloud security agent. Tami uses a multi agent system trained on remediation history, operating under guardrails. To ensure safety, human experts verify the AI logic on demand. This human in the loop model generates CLI commands, Infrastructure as Code templates, and validation scripts, which handles 90% of the manual remediation effort.

A Fortune 1000 healthcare company reported an 87% reduction in cost per remediation by using this supervised approach. Across every remediation Tami has executed to date, there have been zero production incidents.

Moving toward outcomes

The primary metric for a cloud security program is the number of risks retired. The current trajectory, where critical alerts stay open for 150 days, is unsustainable.

Operationalizing a CNAPP requires a mechanism to resolve the 2% of findings where tools disagree and a strategy to manage the "High" queue. By employing cross tool enrichment and ownership resolution through layered signals, organizations can close the gap between visibility and security. Every remediation should ship with a prevention plan to ensure misconfigurations do not reappear in the next deployment cycle.