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The Beginning of AI-Native Security Research

Application Detection and Response (ADR) technologies are essential for identifying and mitigating runtime attacks. Yet, many existing approaches struggle to detect nuanced, logic-based vulnerabilities effectively.

Understanding domestic and international regulatory landscapes is crucial to ensuring compliance and enhancing security postures. This blog post explores key software security mandates worldwide, including those from the United States, European Union, and Asia-Pacific, providing a comprehensive guide on navigating these complex regulations for a secure software development lifecycle.

By someone who used to review every PR, and now reviews AI-generated diffs. Software development is about to look very different.

Application Detection and Response (ADR) is emerging as the next evolution in application security, aiming to catch and stop attacks from within the application itself at runtime. Recent incidents like the Next.js middleware vulnerability CVE-2025-29927 – an authentication bypass triggered by a single HTTP header – underscore why traditional approaches often fall short.

Kodem unified data model allows reasoning about “what’s happening” in the app—at every layer, in every stage—at once.

Agentic red teams, AI-powered multi-agent systems capable of offensive security testing, have arrived as a timely and necessary innovation to fill this critical gap in the cybersecurity landscape.

Pinpoint real exposure with Kodem’s unique approach, as seen in real-world example of CVE-2025-29927 in Next.js.

The Next.js team disclosed – CVE-2025-29927 vulnerability – that allows attackers to bypass authorization checks implemented in Next.js Middleware by manipulating the x-middleware-subrequest header.

Remote Code Execution CVE-2025-24813 vulnerability - See how Kodem runtime SCA and ADR can identify and block these attacks without specific CVE signatures

Vulneraiblity in the GitHub tj‑actions/changed‑files Action—employed by over 23,000 repositories—has been compromised by an attacker.

As organizations increasingly adopt AI, the demand for standardized frameworks to manage AI risks has grown - enter ISO 42001.