AI Red Teaming Overview

Adversarial testing built specifically for large language models and GenAI applications

AI Red Teaming simulates real-world attacks against your GenAI and LLM-based applications — exposing vulnerabilities before they reach production.

Traditional penetration testing wasn't built for large language models. Cloudserve Systems combines automated AI-driven attack campaigns with hands-on expert testing to uncover prompt injection, jailbreaks, data leakage, and unsafe agent behavior.

Our certified security engineers deliver clear, evidence-backed findings with actionable remediation guidance — so your team can ship AI products with confidence.

GenAI Risks We Uncover

Mapped to OWASP Top 10 for LLMs and real-world attack patterns

Prompt Injection

Direct prompt injection attacks
Indirect injection via RAG
System prompt hijacking
Instruction override attempts

Jailbreak & Bypass

Role-play and persona exploits
Token obfuscation techniques
Guardrail circumvention
Multilingual evasion testing

Data Exposure

PII leakage from training data
Credential extraction attempts
Confidential context retrieval
Vector store data probing

Unsafe Agents

Privilege escalation in chains
Tool call manipulation
Goal hijacking attacks
Memory & context poisoning

Hallucination Risk

False citation generation
Factual accuracy testing
Confidence calibration checks
Domain-specific reliability

Model Poisoning

Backdoor attack simulation
Fine-tuning pipeline integrity
Training data corruption
Hidden trigger detection

Supply Chain

Third-party model risk review
Plugin & tool integration audit
Model serving security check
API dependency assessment

Compliance Coverage

OWASP LLM Top 10 mapping
NIST AI RMF alignment
EU AI Act readiness
SOC 2 AI control mapping

Our Red Teaming Process

A clear, repeatable methodology from scoping to continuous monitoring

Scope & Model

Define attack surface, identify AI assets, and build adversary profiles for your architecture.

Automated Attacks

Run thousands of adversarial prompt variations across your LLM endpoints using AI tooling.

Human Expert Testing

Senior engineers craft novel exploits and probe agentic workflows automated tools cannot reach.

Risk Report

Every finding scored by severity with evidence artifacts and clear remediation guidance.

Continuous Re-Testing

Scheduled re-evaluations after model updates keep your AI secure as it evolves.

AI Red Teaming