Introducing ÆSIR: Finding Zero-Day Vulnerabilities at the Speed of AI

TrendAI™’s ÆSIR platform combines AI automation with expert oversight to discover zero-day vulnerabilities in AI infrastructure – 21 CVEs across NVIDIA, Tencent, and MLflow since mid-2025.

Artificial Intelligence (AI)

Introducing ÆSIR: Finding Zero-Day Vulnerabilities at the Speed of AI

TrendAI™’s ÆSIR platform combines AI automation with expert oversight to discover zero-day vulnerabilities in AI infrastructure – 21 CVEs across NVIDIA, Tencent, and MLflow since mid-2025.

By: Peter Girnus

Jan 15, 2026

Read time: ( words)

Save to Folio

Overview

Executive summary

The scale of the challenge

Securing AI at the speed of AI

Why library security matters

Responsible AI security research

Executive summary

TrendAI™ introduces ÆSIR, an AI-empowered security research platform that combines advanced automation with human expertise to proactively identify and remediate zero-day vulnerabilities in foundational AI infrastructure. Since mid-2025, ÆSIR has uncovered 21 critical CVEs across industry-leading platforms including NVIDIA, Tencent, MLflow, and MCP tooling, which underscores ÆSIR’s ability to operate at the scale and speed required to protect the rapidly evolving AI ecosystem.

The platform leverages two core components: MIMIR for real-time threat intelligence and FENRIR for zero-day vulnerability discovery. Together, these enable TrendAI™ to scan massive codebases in hours, prioritize the highest-impact vulnerabilities, and ensure robust, continuous protection for customers. Powered by ÆSIR, TrendAI™’s responsible disclosure process sees to it that all vulnerabilities are not only reported but also fully remediated, including patch bypass verification, to further strengthen customers' defenses.

ÆSIR closes the gap between the speed of AI development and the pace of security research: By combining machine-speed automation with our researchers’ expert oversight, it helps TrendAI™ experts deliver rapid, high-quality vulnerability discovery and lifecycle management for critical AI infrastructure.

Every step involves human direction of ÆSIR's AI resources: While AI agents accelerate codebase analysis, human experts direct research, validate ÆSIR findings, and manage disclosure of discovered vulnerabilities: Researchers investigate issues flagged by ÆSIR, assess their real-world impact, and drive responsible vendor coordination. This way, patch effectiveness is verified by both AI and human analysis to ensure full remediation and identify any bypasses.

TrendAI™ unveils ÆSIR

"AI factories will be the critical infrastructure of the 21st century."  –  Jensen Huang, CES 2025

To secure the future, TrendAI™ unveils ÆSIR (AI-Enhanced Security Intelligence & Research): It supercharges TrendAI™ analysts, researchers, and threat researchers with AI agents that operate at machine speed – scanning codebases in hours instead of weeks, correlating threat intelligence across thousands of sources, and surfacing the highest-priority targets for human and agentic investigation, all while creating protections for TrendAI™ customers.

ÆSIR is our answer to questions every security professional should be asking:

• Who secures the AI that will power the next generation of compute?

• What is the future of AI and humans in vulnerability research?

The answer involves AI itself, but not the way you might think.

The scale of the challenge

In 2025, more than 48,000 CVEs were published – a 38% increase from 2023. The scale of vulnerabilities continues to rise in our increasingly connected world. Huang himself acknowledged the acceleration at the GTC 2025 event: "The computation we need at this point is easily 100 times more than we thought we needed." At the same time, global AI spending is projected to reach US$1.5 trillion in 2025 and exceed US$2 trillion by 2026, according to the World Economic Forum. Enterprise spending on generative AI alone jumped from US$11.5 billion in 2024 to US$37 billion in 2025, increasing by 3.2 times in a single year. This explosion of AI investment and the computation needed to supply the AI ecosystem creates attack surfaces faster than traditional security research can address – beyond even the increased number of bugs in more traditional software.

The surge in AI-specific vulnerabilities tells an even more dramatic story. Analysis of 2,986 AI CVEs verified by large language models (LLM) reveals an unmistakable inflection point (Figure 1). From 2018 to 2022, AI vulnerabilities grew at a steady but manageable pace, with roughly 50 CVEs in 2018 climbing to approximately 275 by 2022.

Then came the ChatGPT era, and the mainstreaming of LLMs triggered an exponential acceleration beginning in late 2022. AI CVEs jumped from around 300 in 2023 to over 450 in 2024, and reached over 1,000 in 2025 – a 70% year-over-year increase that shows no signs of slowing. The correlation is clear: as AI systems move from research labs into production environments, their vulnerabilities move from theoretical concerns to active threats.

[Figure 1. Number of AI-related vulnerabilities (CVEs) from 2018 to 2025]

Figure 1. Number of AI-related vulnerabilities (CVEs) from 2018 to 2025

download

The cybersecurity implications are profound. The AI cybersecurity market reached US$26.29 billion in 2024 and is projected to hit US$109.33 billion by 2032.  The question remains: who's finding the vulnerabilities in the AI systems themselves?

ÆSIR: Securing AI at the speed of AI

ÆSIR represents TrendAI™'s strategic investment in agentic security research.

The platform consists of two specialized components – MIMIR and FENRIR, named after figures from Norse mythology who embody the capabilities they provide – working in concert under human oversight.

MIMIR

MIMIR, named after guardian of the Well of Wisdom (Mímisbrunnr) beneath Yggdrasil, from which Odin sacrificed an eye to drink and gain knowledge. MIMIR, which serves as the intelligence backbone of ÆSIR, continuously monitors the global vulnerability landscape. It tracks thousands of CVEs published annually and uses AI agents to perform autonomous security research, correlate threat intelligence, and prioritize vulnerabilities. This system filters signal from noise by providing actionable intelligence to teams of vulnerability researchers, threat researchers, and detection engineers within Trend.

FENRIR

FENRIR, named after the great wolf of Norse legend whose hunting prowess was unmatched, handles zero-day vulnerability discovery and agentic triage. FENRIR analyzes source code to identify patterns consistent with known vulnerability classes (like deserialization flaws, authentication weaknesses, and injection points), surfacing candidates for further review, then analyzes and prioritizes this vulnerability intelligence by potential severity, exploitability, and internal metrics.

[...]

Original source