Aptori Launches AI Triage for Enhanced Vulnerability Management

Sep 23, 2025
Aptori has introduced AI Triage, an AI agent designed to streamline vulnerability management by eliminating false positives and focusing on exploitable flaws.

Aptori has launched AI Triage, an AI agent aimed at transforming vulnerability management by eliminating false positives and focusing on exploitable flaws, announced in a press release. AI Triage mimics a developer's approach by stepping through code, tracing control and data flows, and validating vulnerabilities, thus shifting from scoring to validation.

This new tool is designed to integrate directly into CI/CD pipelines and coding environments, providing real-time feedback without slowing down developers. It offers deterministic results, ensuring that no exploitable flaw is missed, and integrates seamlessly with platforms like GitHub, GitLab, and Azure DevOps. AI Triage is already in use at several Fortune 50 enterprises, helping security teams save weeks of manual review and reducing alert queues significantly.

AI Triage is available as part of the Aptori platform, offering deployment options that include integration with Application Security Posture Management (ASPM) dashboards and coding assistants like Claude Code and Gemini CLI. This flexibility ensures that AI Triage can be consumed in a way that best fits existing workflows, delivering value without adding friction.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Cybersecurity AI Weekly or Daily AI Brief.

Also, consider following us on social media:

Cybersecurity AI AI Brief AI Brief (X)
Free newsletter

Cybersecurity AI Weekly

Weekly newsletter about AI in Cybersecurity.

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.