Securely Enable AI
Your teams are already shipping LLM features and buying AI-powered tools. The question is no longer whether to adopt AI. It's whether you can show it hasn't opened doors an attacker can walk through. We test AI systems the way adversaries attack them, secure the pipelines that ship them, and put guardrails around the data that feeds them.
Talk to an Expert01 - The Challenge
AI adoption creates attack surface faster than most teams can review it
Every LLM feature, copilot rollout, and AI vendor integration adds new inputs an attacker can manipulate, and new paths for your data to leave. Traditional application testing was not designed to cover them.
Prompt injection and adversarial inputs
LLM applications can be manipulated through the content they consume. We test for prompt injection, model extraction, adversarial inputs, and data poisoning, aligned to the OWASP LLM Top 10.
Sensitive data flowing into models
Personal data pasted into prompts or wired into AI integrations is still regulated data. GDPR and India's DPDP Act don't stop applying because the processor is a model.
AI features ship through the same pipelines as everything else
A secure model behind an insecure CI/CD pipeline is still an insecure product. SAST, DAST, dependency, and IaC scanning need to cover AI services the same as any other release.
APIs are the delivery surface
Most LLM functionality is exposed through APIs. Authentication, authorization, rate limiting, and business-logic flaws on those endpoints decide who can reach, and abuse, your model.
02 - How We Deliver It
The services behind this solution
Each solution is delivered through our standing services, scoped together as one program rather than sold as separate line items.
- 01
AI / LLM Security Testing
Security testing for AI models and LLM-powered applications: prompt injection, model extraction, adversarial inputs, and data poisoning.
- 02
API Security Testing
Deep testing of authentication, authorization, injection, and business-logic flaws across REST, GraphQL, and SOAP APIs.
- 03
DevSecOps Implementation
SAST, DAST, SCA, IaC scanning, and container security embedded directly into the CI/CD pipeline that ships your AI features.
- 04
Data Privacy & Protection
Data mapping, DPIAs, and privacy program design so the data feeding your AI stays inside GDPR, CCPA, and DPDP obligations.
Common Questions
We test AI models and LLM-powered applications for prompt injection, model extraction, adversarial inputs, and data poisoning, aligned to the OWASP LLM Top 10, the same adversarial approach we apply to web and API testing, adapted to how language models fail.
START YOUR
ENGAGEMENT.
Speak with our engineering team to define scope, understand our methodology, and secure your environment against advanced threats.
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