Red Teaming

Red Teaming Solutions

Red teaming strengthens the overall robustness of the model, making it less susceptible to manipulation and misuse in the real world. By simulating real-world misuse scenarios, red teaming uncovers hidden biases and vulnerabilities the model might not encounter during standard training. It helps improve model accuracy by identifying situations where the model might generate unreliable or fabricated information as well as enhances model safety by catching potential issues like the generation of harmful content.

For generative AI can be partially automated, but human expertise remains crucial. While automation can be used for tasks like generating basic prompts or running repetitive tests, crafting truly effective adversarial prompts requires a deep understanding of the model's architecture, potential biases, and the desired areas of vulnerability testing. This nuanced knowledge is best wielded by human red teamers who can adapt their strategies based on the model's responses and identify subtle weaknesses that might be missed by automated scripts.

Red Teaming

Red Teaming Solutions

Our team of ML engineers and applied data scientists craft prompts designed to trick or exploit your model’s weaknesses. We will help you map the vulnerabilities of your AI systems so you can improve the safety and reliability of your generative models.

Public Safety Adversarial Testing

Our team of experts intentionally try to evade model safeguards to get models to produce harmful or dangerous content. By acting as adversaries, our team will develop various simulations that mimic real world threats to personal safety (e.g. "How do I poison someone?") or public safety (e.g. "How do I launch a cyberattack?").

Compliance Testing

By simulating scenarios such as copywriting infringement or unlawful impersonation, our team can expose weaknesses in a model's ability to detect and prevent these activities. This can involve creating deep fakes or synthetic media that resembles copyrighted material or impersonates real people (e.g. explicit material involving celebrities) to comply with laws and prevent the spread of malicious content.

Privacy Vulnerability Testing

By crafting clever prompts, our team of experts will attempt to trick your model into leaking sensitive information such as passwords, proprietary information (e.g. how your model is built), or other private data. Our team can also help expose vulnerabilities that would reveal PII or other personal data to improve data privacy and compliance

Fairness Evaluation

Our teams help identify unwanted negative biases in your models to improve fairness and trustworthiness. We’ll simulate real-world scenarios where fairness might be compromised and expose vulnerabilities by crafting prompts that could lead to discriminatory or offensive outputs.

Data Security is Our Top Priority

Your data remains protected and private because it’s managed in a secure facility by full-time in-house workforce of data experts. Your Data is Yours – Aimabec Tech does not share or keep any datasets for training or other purposes, unlike crowdsourced alternatives.