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Cekura Red Teaming: Stress-test your AI agents for Jailbreaks, Bias, Toxicity and more

Break your AI agents security before your customers do

Hi Everyone! We are Sidhant, Shashij, and Tarush, co-founders of Cekurađź‘‹

TL;DR: We have launched Cekura Red Teaming for enterprises and startups building Conversational AI in compliance-heavy sectors like BFSI, Healthcare, Legal, etc

Watch our launch video here or book a call here

Problem:. Enterprise security teams are blocking deployments because manual, vibe-based testing doesn’t provide enough assurance against adversarial users. Whether it’s a user bypassing a paywall, tricking a bot into giving legal advice, or social-engineering it into leaking company secrets - the attack surface of conversational AI is massive.

Solution:

Scalable, Automated Red Teaming: Cekura allows you to run thousands of adversarial simulations in minutes. We act as the "bad actor," pushing your agent's logic to its limits across every major vulnerability category:

  • 🔓 Jailbreaking: We simulate sophisticated "prompt injection" attacks to see if your agent will ignore its instructions or reveal its system prompt.
  • ⚖️ Bias & Fairness: We test for hidden biases in financial, medical, or recruitment advice to ensure your agent stays compliant and fair.
  • 🤬 Toxicity: We try to provoke your agent into unprofessional or offensive behaviour.
  • 🛡️ PII & Data Leakage: We attempt to extract sensitive data like credit card numbers, internal keys, or user data that your agent shouldn't have the authority to share

Red Teaming as a Service (RTaaS): Beyond our standard library of thousands of scenarios, we also deploy our Forward Deployed Engineers to build personalised adversarial test cases tailored to your specific industry and use case (HIPAA compliance for healthcare, PCI DSS for fintech, etc)

Ready to Security Test your Voice & Chat AI Agents?

The Team:

We met over eight years ago during our undergraduate studies at IIT Bombay.

Tarush comes from quantitative finance, where he worked on simulations for ultra-low latency trading strategies (think nanoseconds!).

Shashij has previously researched NLP at Google Research and is the first author of a paper on testing AI systems reliably, which has 50+ citations from his work at ETH Zurich.

Sidhant comes from a consulting background advising CXOs at Fortune 500 companies in FMCG and medical devices. He managed P&L in a leading contact centre.