Generative AI is the brand new driving force of recent businesses, but the identical technology has the potential to open up entirely recent attack vectors and put an organization and its popularity in danger in a really short time. SydeLabs, a California-based startup, solves this challenge with an intent-based real-time firewall. The startup raised $2.5 million in seed funding today from RTP Global, Picus Capital and other angels.
Although there are several other players within the AI security space, SydeLabs goals to face out amongst them with its comprehensive suite of solutions and help developers avoid Large Language Model (LLM) vulnerabilities in any respect stages of development, including the lesser-known project lifecycle – from development to deployment.
The company is already working with a number of organizations and plans to make use of the fresh capital to concentrate on research and development and updating its technology stack to remain ahead of malicious actors compromising firms' generative AI systems want.
What does SydeLabs offer?
At its core, SydeLabs has developed three key AI-focused products: SydeBox, SydeGuard and SydeComply. The first solution, currently available in beta, is a self-service red teaming solution that enables teams to emphasize test their AI apps and models to search out out in the event that they are vulnerable to vulnerabilities. The other two, scheduled to go live soon, aim to supply real-time intentional protection and discover/address gaps in AI systems that could lead on to compliance issues in numerous parts of the world.
“During SydeBox beta, we were in a position to uncover various vulnerabilities comparable to training data leaks, system prompt leaks, prompt injections, security alignment bypasses, etc. On the opposite hand, our real-time intent-based protection system SydeGuard can detect this and forestall quick injections, denial-of-wallet attacks, data leak attempts, system prompt leak attempts, misuse of AI systems, etc.,” Ankita Kumari, who co-founded SydeBox with Patwa, told VentureBeat.
The red teaming solution uses an AI agent that creates test attacks (based on internal research and public data) and an LLM that detects the success of the attacks based on the response of the goal system.
Meanwhile, SydeGuard uses a mix of proprietary models that discover end-user intent across different Tactics, Techniques and Procedures (TTPs). The models examine each individual prompt for potential threats and supply a risk assessment for the prompt, the user session, and the user themselves.
However, based on this profile, the user is not going to be blocked immediately. Instead, it shares the information with the corporate's security teams while giving them the choice to either block the prompt/user, monitor it and provides a typical response, or send it to a honeypot to idiot the attacker with dummy data . This gives teams control over how they need to cope with a possible attack.
Kumari hasn't revealed much in regards to the compliance-focused offering, even though it appears it’s going to leverage detection capabilities under development to discover the gaps where an organization could also be violating internal or external regulations.
10,000 vulnerabilities were reported inside a month
Currently, SydeLabs is within the pre-revenue phase and is working quickly to expand its offering and become profitable. The company launched its red teaming solution SydeBox on March 1, 2024 and has since been adopted by greater than 15 firms, discovering over 10,000 vulnerabilities in greater than 50 applications/models. These apps/models are either live in production or still in development, Kumari confirmed.
With the seed round, the startup desires to concentrate on research and development and catch up with to providing SydeGuard and SydeComply to customers. In the long run, the red teaming solution shall be offered freed from charge to firms that need to discover vulnerabilities of their application and monetize SydeGuard using a consumption-based model.
“A key aspect of the success of a cybersecurity product is its accuracy and its ability to remain one step ahead of attackers. Therefore, we place great emphasis on continuously updating our model for brand new attack vectors and recent attack modes,” the co-founder added.
The startup's funding comes at a time when the safety and reliability of genetic AI apps are under scrutiny attributable to multiple cases of prompt injection attacks leading to the generation of deepfakes of high-profile celebrities. Just recently, Microsoft announced a brand new set of Azure AI tools to detect hallucinations and forestall attacks. Skyflow, a startup that gives firms with a knowledge protection vault for secure AI development, has also gained 30 million dollars in a fresh round.
In the world of red teaming and real-time prevention, SydeLabs competes with players like to the lake And Prompt security. However, Kumari emphasized that SydeLabs has more to supply than these players. In addition, she said, early testing shows that the corporate's products significantly outperform all of those tools when it comes to accuracy and performance.
