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18/08/2026 2:36 pm
TL;DR: Vulnerability exploitation has become the leading initial access vector at 31% of breaches, while only 26% of critical KEV items were fully remediated in 2025, according to Cycode’s analysis of Verizon’s DBIR and CISA data. The security problem is no longer finding more issues, but closing the gap between discovery, code change, and fix before attackers use it.
NHIMG editorial — based on content published by Cycode: Top Continuous Application Security Monitoring Tools as of 2026
By the numbers:
- Only 26% of critical vulnerabilities in CISA’s Known Exploited Vulnerabilities catalog were fully remediated in 2025.
- Cycode’s 2026 research found that 81% of organisations lack full visibility into how and where AI is being used across the SDLC.
Questions worth separating out
Q: What breaks when continuous application security monitoring is not in place?
A: When continuous monitoring is missing, vulnerabilities, exposed secrets, and pipeline weaknesses are discovered too late to matter.
Q: Why do exposed secrets and vulnerable dependencies create access risk for security teams?
A: Because they turn code into a credential distribution channel.
Q: How do you know if continuous risk monitoring is actually working?
A: It is working when risk signals lead to timely action, not just more alerts.
Practitioner guidance
- Map identity-bearing assets across the SDLC Inventory service accounts, tokens, API keys, CI/CD credentials, and AI-assisted development tools across repositories, pipelines, and runtime environments so ownership and lifecycle controls are visible.
- Shift scanning into every code event Run secrets detection, dependency scanning, and policy checks on each commit, pull request, and build so vulnerable changes are blocked before release rather than discovered later.
- Correlate findings to owner and blast radius Tie each alert to a named owner, reachable systems, and likely impact so remediation is prioritised by exposure and exploitability instead of by scanner output volume.
What's in the full article
Cycode's full article covers the operational detail this post intentionally leaves for the source:
- Side-by-side product distinctions across ten continuous monitoring tools, including where each tool fits in the stack.
- Vendor-specific capabilities such as AI code security, runtime monitoring, and pipeline controls that are not unpacked here.
- Cycode's performance claims, customer examples, and implementation context for choosing between AppSec platforms.
- The article's deeper explanation of how the Agentic Development Security Platform changes monitoring for AI-assisted development.
👉 Read Cycode's guide to continuous application security monitoring tools for 2026 →
Application security monitoring in 2026: are your controls keeping up?
Explore further
18/08/2026 3:21 pm
Continuous application security monitoring is now an identity and access problem, not just an AppSec problem. The article correctly shows that exposed secrets, CI/CD compromise, and runtime abuse are all access issues once software systems can create or consume credentials at speed. That means IAM, PAM, and NHI governance have to extend into the software factory, where service accounts, tokens, and automation identities are introduced and used. The practitioner conclusion is simple: if security monitoring stops at code quality, it stops too early.
A question worth separating out:
Q: Should organisations prioritise runtime detection or pre-production controls first?
A: Pre-production controls should come first when the goal is prevention, because they block insecure changes before they become live exposure. Runtime detection still matters, but it is a containment layer. Teams with limited capacity should start with secrets detection, dependency checks, and CI/CD policy gates before expanding into observability-linked response.
👉 Read our full editorial: Continuous application security monitoring is now an access-control problem
