Сайт Redteaming Tool от Raft Digital Solutions

Преимущества

  • What is Red Teaming for GenAI applications?

    Red Teaming for LLM systems involves a thorough security assessment of your applications powered by generative AI.

  • Mitigate Risks

    Avoid costly data breaches, financial losses, and regulatory penalties.

  • Enhance User Trust

    Deliver secure and reliable AI-driven experiences to protect your brand reputation.

  • Comprehensive Security Testing

    Evaluate resilience against both traditional and emerging AI-specific threats.

  • Tool Integration Expertise

    Our experts analyze potential risks arising from plugins, function calls, and interactions with external services.

  • Innovation in Attack Simulation

    We simulate real-world threats, including prompt injection and jailbreak attempts, to test your AI's robustness.

Cases

  • dollar image

    A chatbot flaw
    enabled unauthorized booking of a hotel room
    for just $1

  • medical staff

    Prompt injection
    caused a medical AI to mistakenly recommend
    beer as a health tonic

  • multi-story building

    A system prompt exposure
    revealed a retail company's internal operational algorithms

  • planet Earth

    LLM bias testing
    highlighted critical safety issues across different AI models

Red Teaming
Process

Risk Assessment & Threat Modeling

Test Planning & Preparation

LLAMATOR Scanning

Rescan & Validation

Security Guardrails Implementation

Comprehensive Report Delivery

CI/CD Pipeline Integration

LLAMATOR: Automated AI Red Team Tool

LLAMATOR report example

Available via pip for easy integration into your workflow

Test for vulnerabilities across multiple languages and attack scenarios

Automatically refine and adapt attack methods for maximum coverage

Compatible with WhatsApp, Telegram, LangChain, REST APIs, and more

Generate Word reports and export attack logs to Excel for easy analysis

Use LLM-as-a-judge to evaluate your AI's performance and resilience

Supported by ITMO University &
AI Talent Hub

Download LLAMATOR Telegram Logo Product Chat in Telegram

Testing Vectors

OWASP Top 10 for Large Language Model Applications

LLM ID
Title
Description
Available in LLAMATOR
Red teaming audit

LLM01:
2025

Prompt Injection

User interference in requests to alter results and functions of the model.

LLM02:
2025

Sensitive Information Disclosure

Risks of PII, business info, or algorithms disclosure.

LLM03:
2025

Supply Chain

Security breaches and data manipulation vulnerabilities.

LLM04:
2025

Data and Model Poisoning

Manipulating training data for model reliability impact.

LLM05:
2025

Improper Output Handling

Lack of checks on outputs causing application vulnerabilities.

LLM06:
2025

Excessive Agency

Overuse of LLM in decision-making, exceeding safe limits.

LLM07:
2025

System Prompt Leakage

Leakage of internal system prompts revealing confidential settings.

LLM08:
2025

Vector and Embedding Weaknesses

Vulnerabilities in vector and embedding causing unpredictable errors.

LLM09:
2025

Misinformation

Generation of false or misleading information.

LLM10:
2025

Unbounded Consumption

Unlimited resource usage leading to system overload.

LLAMATOR Usage Options

  • Want to Test Your AI Application?

    Use OWASP Top 10 for LLM 2025 and LLAMATOR

    Download

  • Need an AI Application audit?

    Our experts will assess your threat model and create a tailored testing plan

Publications

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