Traceable AI raises $60 million for unique API security platform

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Today, API security provider Traceable AI announced that it has raised $ 60 million as part of the Series B funding round. The new fund is valued at more than કંપની 450 million and will be used to invest in product development and research, while expanding its sales and marketing teams to enhance its growth.

The solution of Traceable AI collects data from user-based transactions as it flows through the API, and stores it within the platform. The application then uses machine learning to convert business logic into a logistic model.

This logistics model is processed with machine learning, which learns to detect changes from normal application behavior over time.

For the enterprise, the platform provides a tool for detecting API-level attacks that often slip under the radar of understaffed or resourced security teams in environments with cloud-native applications.

Difficulties securing APIs in the cloud age

Today, many organizations are in a position where their API attack surface is expanding, but they do not have access to the skills or tools needed to mitigate these risks. For example, research has shown that incorrectly configured APIs create two-thirds cloud breaches.

At the same time, attackers know that Enterprise APIs are not ready to be protected, with API attacks increasing by 348% in the first six months of this year, as 94% of companies report that they have API-related security incidents in the last 12 months. Is. .

The reason for the increase in security incidents is that the increase in the number of cloud apps has created a mountain of security vulnerabilities that legacy security tools are unsuitable to deal with.

“Organizations do not have adequate security tools to protect their expanding API attack surface. Current application security tools that rely on signatures built on regular expressions to capture exploits generate a large number of false positives. The widespread use of APIs that power today’s business success is being thwarted by traditional security solutions while allowing malicious cyber attacks to exploit API applications and extract sensitive data, “said Jyoti Bansal, CEO and co-founder of Traceable AI. Said.

“Modern API-powered applications move very fast, releasing new features while inadvertently exposing API vulnerabilities and business logic flaws. Existing security tools such as WAFs, RASP and API Gateway alone are not moving fast enough to meet the speed of API application development and their security requirements, ”Bansal said.

The purpose of the Traceable API is to enable security teams to keep up with API-level threats by offering user attribution and distributed tracing for each recorded transaction, providing a view of the entire user activity storyline of the risky actor across systems and overtime.

The activities of these threatening actors, and the level of risk they pose to the enterprise, provide a holistic view, making it easier for human analysts to understand what the most significant risks are and how to block them.

API Management Market

Traceable API is part of a fast-growing global API management market, with researchers estimating that it will grow from $ 4.1 billion in 2021 to $ 8.41 billion in 2027 as organizations invest more in API and solutions to prevent application-layer attacks.

The provider is competing against a number of other established API security vendors, including No Name Security, which recently raised $ 135 million as part of a Series C funding round and achieved a 1 billion valuation.

No Name Security offers API security posture management solutions that can inventory APIs and identify misconceptions and security vulnerabilities through the use of AI and ML models.

Another competitor is Salt Securities, which raised $ 140 million earlier this year as part of the Series D funding round, raising its total to $ 271 million. Salt Security provides users with an API reference engine that can continuously detect APIs, identify vulnerable APIs, test Apis in pre-production, and block API attacks.

Although these solutions are well-established, Bansal argues that traceable AI emphasizes highlighting the aggressive journey to the analyst so that they can “understand the unique business logic, user attribution, and context of each API, from product development to context.”

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