Uncovering record vulnerabilities every single day
100+
Targets Added
20k+
Vulnerabilities Detected
200+
Scans Completed
Even with small changes, the safety & security alignment of LLMs changes dramatically and hence red teaming needs to be iterative and automated.
Unidentified vulnerabilities in AI Systems
Processes such as fine tuning can induce unpredictable vulnerabilities in AI models. Identification of these vulnerabilities is only possible with comprehensive red teaming.
Selecting the better model
Understanding the safety & security posture of custom or foundational models can help enterprises chose the right model for deployment, one that is safer and more secure.
Policy Violation Disclosure
While everything cannot be prevented from Day 1, red teaming ensures that you can create a prioritised Vulnerability Disclosure Report of your genAI application. This helps in building a trustworthy AI roadmap.
Continual Improvement of LLM security
A probabilistic model requires to be tested for security every time a change is deployed. Regular red teaming of LLM systems identifies vulnerabilities in every version of the experimental endpoint.
AI Agent scanning your system for vulnerabilities will provide richer insights into what needs urgent fixing and inform on the ease of manipulating your GenAI application.
Business relevant vulnerability detection
SydeAgent can create attack objectives on the fly. But you can add goals specific to your business use case to get more focussed insights into the top-of-the-mind problem statements you are solving for.
Customisable context window
Whether you want the agent to remember the last 5 or 10 messages in the conversation, whether you want to establish an upper cap on the output tokens, customise the environment for the agent to represent your actual use case.
Mimics a Bad Actor
An attacker will modify every subsequent attack based on the previous response from the LLM integrated application. Our Agent mimics this behavior but is built to outsmart the smartest attackers.
Use with or without SydeBot
SydeAgent is a part of SydeBox, packaged alonsgside SydeBot(red teaming based on a static attack library). Run scans using both to get the best insights.
How SydeBox Works
SydeLabs follows a two-pronged approach to red teaming LLM integrated applications. Our attack Library based red teaming is called SydeBot and AI agent based red teaming called SyedAgent.
Features
Essential Requirements of a Red-Teaming Solution Fulfilled
Seamless integration with your custom endpoints and async tests allow you to red team your AI hassle-free.
