What cybersecurity services does CRIS InfoTech offer globally?

CRIS InfoTech provides manual-first VAPT (web, network, API, mobile), AI / LLM security testing, secure code review and SAST, with a free retest on every project. We also offer red team assessments, SOC monitoring, SIEM, incident response and threat intelligence including dark web investigation.

Where is CRIS InfoTech based?

CRIS InfoTech is based in Hitech City, Hyderabad, Telangana, and serves clients across India and worldwide with VAPT, mobile app pentesting, API security testing and secure code review.

What is VAPT and why is it important for my business?

VAPT (Vulnerability Assessment and Penetration Testing) identifies security weaknesses in your applications and infrastructure. It's crucial for businesses to proactively find and fix vulnerabilities before malicious actors exploit them, supporting compliance and protecting sensitive data.

Does CRIS InfoTech provide SOC monitoring services?

Yes. CRIS InfoTech offers SOC monitoring with alert validation, escalation and incident response support, 24/7. Response targets are agreed in writing during scoping.

Securing LLM features: a starter guide

Adding an AI assistant to your product? You’re in good company. Let’s answer the questions teams ask us most before they launch.

Treat model input and output as untrusted?

Anything the model reads — user messages, documents, web pages — can contain instructions. Anything it writes can contain unexpected content. Validate and handle both carefully.

Limit what the AI can reach?

Give the assistant access only to the data and tools it truly needs, scoped to the current user. Require confirmation before actions with real-world impact.

Test against a recognized list?

The OWASP Top 10 for LLM Applications is a good baseline for testing. Combine it with monitoring of usage and cost, and retest whenever prompts, tools or data sources change.

Questions to ask before launch?

What data can the assistant read? What actions can it take? Who reviews its output before it reaches a customer? What happens if it is asked to do something outside its purpose? Clear answers to these four questions prevent most issues.

Keep humans in the loop?

For refunds, account changes or anything with financial impact, require a human or explicit user confirmation. AI should assist decisions, not make irreversible ones on its own.

What you should do

Document which data and tools your AI feature can reach
Scope data access to the current user
Require confirmation before high-impact actions
Set usage and cost limits
Monitor prompts and responses for abuse

What our team does

Review your AI architecture and threat model
Test against the OWASP Top 10 for LLM Applications
Check data access and tool permissions
Recommend practical guardrails
Retest after changes
Run a pre-launch AI threat-modeling session
Test data access separately for each user role
Advise on monitoring of AI usage and cost

Jargon buster

LLM: Large language model — the AI that powers chatbots like the one on your site.
Prompt: The instructions and text given to the AI.
Guardrails: Rules and checks that keep the AI from doing or saying the wrong thing.

AI moves fast. A short test before launch is far cheaper than a public mistake after it.

— The CRIS InfoTech security team

See our AI / LLM security testing