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Detox Technologies

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AI Security Testing & Red Teaming Services

Secure GenAI applications, LLM-powered products, RAG pipelines and autonomous AI agents before adversaries turn prompts, data, tools or excessive permissions into a business-impacting attack.


Test What Your AI Can Say, Access and Do

AI-enabled applications introduce attack paths that conventional application testing alone may not uncover. A prompt can become an instruction, retrieved content can become an attack vector, and an over-privileged agent can turn a model error into a real action.

Detox combines manual adversarial testing with targeted automation to evaluate the complete AI application stack: user interfaces, model APIs, system prompts, RAG data stores, agent memory, plugins, tools, MCP integrations, identity boundaries and the surrounding cloud and application infrastructure.

Testing is tailored to your use case and risk profile. We map realistic abuse scenarios, safely demonstrate impact and give engineering teams reproducible evidence and practical remediation guidance. Coverage can be aligned with the OWASP Top 10 for LLM and Agentic Applications, NIST AI RMF guidance and MITRE ATLAS techniques.

For conventional components around the AI system, combine this engagement with web application VAPT, API penetration testing and cloud penetration testing.

How We Test AI Applications and Agents

AI Threat Modelling

We identify models, prompts, data sources, trust boundaries, users, agents, tools, connectors and high-impact business actions. The result is a focused test plan built around realistic attackers and misuse cases.

Prompt Injection & Jailbreaks

We test direct and indirect prompt injection, instruction hierarchy conflicts, system-prompt disclosure, multi-turn manipulation, jailbreaks and encoded or obfuscated attacks.

RAG, Data & Memory Security

We assess retrieval pipelines, vector stores, uploaded files, tenant separation, citations and agent memory for poisoning, unauthorized retrieval, sensitive-data leakage and context manipulation.

AI Agent, Tool & MCP Testing

We validate tool selection, parameter controls, authorization, approval gates, secrets handling and least privilege, including goal hijacking, tool misuse and malicious connectors.

Model, API & Application Abuse

We evaluate insecure output handling, access controls, rate limits, denial-of-wallet risks, sensitive information disclosure and weaknesses in supporting web, API and cloud layers.

Evidence, Remediation & Retest

You receive business impact, reproducible evidence and prioritized fixes. After remediation, Detox retests agreed findings to provide clear closure evidence.

AI SECURITY FAQ

Frequently Asked Questions

AI security testing is an adversarial assessment of an AI-enabled application and its surrounding components. It evaluates models, prompts, data, RAG, agents, tools, APIs, identity and infrastructure for data leakage, unauthorized actions, unsafe output and disruption.

Traditional penetration testing focuses mainly on software and infrastructure vulnerabilities. AI red teaming also evaluates model behaviour, prompt and context manipulation, safety controls, agent decision-making and abuse cases. A complete engagement combines both disciplines.

Yes. We test agent goals, memory, tool calls, delegated permissions, human approval gates, cross-agent communication and MCP servers or connectors, including whether manipulated components can exceed their intended authority.

You receive an executive summary and technical report with verified findings, risk ratings, business impact, reproduction steps, evidence and prioritized remediation. Retesting can confirm that agreed issues have been fixed.

Why Detox for AI Security Testing?

AI risk becomes real when model behaviour connects to sensitive data, identities, APIs, cloud resources and business workflows. Detox tests those connections as one attack surface. Our security specialists combine structured AI test cases with manual reasoning and multi-step attack chains, then translate each verified weakness into clear engineering action.

Need broader assurance? Explore our penetration testing services or request a scoped assessment for your GenAI application, RAG system, copilot or autonomous agent.

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Testimonial

“The application layer attack surface continues to grow in size and complexity, with nearly 30 percent of breaches analyzed in the most recent Verizon Data Breach Investigations Report (DBIR) involving an application layer attack. And since finding and retaining staff who possess the IT cybersecurity skills required to deal with these realities seems to be a universal problem for companies of all sizes.”

Gartner
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