Innodata发布AI网络安全代码训练套件，但未披露客户、订单或收入增量

AI Cyber Training Suite
- twelve datasets and evaluation systems that train AI coding agents to write code that avoids known security flaws, to avoid introducing new ones, and to patch existing vulnerabilities in the software companies already run. The suite addresses what has become a central barrier to trusting AI-written code: the risk that an agent, while adding a feature or modernizing a legacy system, quietly opens a security hole. The AI Cyber Training Suite works across the stack of coding agents - the models, the harnesses, and the tools - to help ensure the code they produce is not just functional, but secure. It is available to model builders and enterprises beginning today.
The suite is built on thousands of real security flaws discovered over the past ten years across Python, TypeScript, JavaScript, Rust, C, Go, and other languages, spanning a wide range of platforms and service integrations including Linux, macOS, Android, Windows, AWS, GCP, and many others. Each flaw was untangled by hand by Innodata's cybersecurity engineers and rebuilt, with a targeted attack, inside a sealed offline copy of the vulnerable software. That construction is what makes the suite unusually rigorous: it measures an AI's ability to patch a vulnerability by verifying that the original attack can no longer succeed against the fixed code, while confirming at the same time that the software still works as intended. The result is data and evaluations that both train coding agents to avoid vulnerabilities in the first place and test their ability to repair vulnerabilities that already exist.
"For model builders, these evaluations and data sets enable coding agents - the models, harnesses, and tools - to ensure the code they generate is not just effective, but secure," said Yonatan Brander, who leads the cybersecurity data engineering team at Innodata. "And for enterprises, they provide something equally important: confidence that when teams refactor, add features, or modernize legacy systems with AI agents, they are not reintroducing the very vulnerabilities they had already avoided or patched."
For enterprises, that means they can use AI to modernize legacy systems while minimizing the risk of introducing security flaws and use AI to patch identified vulnerabilities.
Innodata tested the ability of ten leading AI models and agents to repair verified security flaws, finding that the best open-weight AI models repaired at most 23% of these verified flaws - even when shown exactly where each one was. But after a single round of fine-tuning on a portion of the suite's data, the model's ability to patch vulnerabilities without being guided to them more than doubled, rising from 18.4% to 41.2%.
"AI now writes a growing share of the world's code, and the agents writing it have to ensure that code is secure," said Jack Abuhoff, Chief Executive Officer of Innodata. "Otherwise, businesses can't depend on AI-generated code without a professional security team reviewing everything it produces - and that is a real blocker to AI adoption. The Cyber OTS Suite helps companies confidently put agent-generated code into production."
About Innodata
Innodata (Nasdaq:INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.
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Company Contact
Aneesh Pendharkar
investor@innodata.com
(201) 371-8000
SOURCE:
Innodata Inc.
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