AI & LLM SECURITY VALIDATION

AI Systems Expand Enterprise Attack Surfaces.

Redbot validates exploitable AI exposure affecting agents, integrations, retrieval systems, APIs, workflows, and connected enterprise infrastructure.

DISCUSS YOUR AI EXPLORE CAPABILITIES

AI Systems

Agents, models, data exposure

Applications

Apps, APIs, logic flaws

Cloud

Configs, trust paths, exposure

Network

Internal & external surface

Red Team

Adversary simulation

WHO WE ARE

Redbot Security, established in 2016, is a manual penetration testing firm specializing in adversarial security validation, advanced red team operations, and hands-on senior-level security testing. Our team performs more than 100 security assessments yearly across enterprise applications, AI systems, cloud infrastructure, APIs, and connected operational environments.

WHY AI TESTING MATTERS

AI adoption is accelerating faster than any technology shift in enterprise history. Employees are connecting AI systems directly into sensitive workflows, internal data, automation platforms, APIs, customer systems, and operational infrastructure often without understanding the exposure being created. The security implications of insecure AI systems will be severe, and validating AI environments has never been more critical.

Redbot Security operates with a focused operational model designed around direct collaboration between clients and senior security engineers, tightly controlled project scoping, proof-of-concept reporting, and actionable remediation guidance designed to move the security needle in the right direction quickly without unnecessary assessment noise, automated fluff, or checklist-driven security theater.

OSCP CRTO ARTA eMAPT GPEN CISSP CCSP CCSK SecurityX CySA+ PenTest+ Security+ Network+ AZ-900 CEH AWS ITIL

Red Team Operations Cloud Security AI Security Research Offensive Security Threat Intelligence Machine Learning In Cybersecurity

Cloud Security Application Security Network Penetration Testing Red Team Operations

TEST THE TRUTH WITH REDBOT

HOW AI SYSTEMS GET COMPROMISED

Attackers Target The Systems Surrounding The Model.

AI compromise increasingly occurs through connected integrations, unsafe retrieval workflows, excessive trust relationships, and exposed operational systems.

Prompt Injection

Attackers manipulate prompts, instructions, and contextual trust to influence AI behavior and downstream actions.

Retrieval Poisoning

Unsafe retrieval pipelines and manipulated knowledge sources can alter outputs and expose sensitive information.

Connected Integrations

APIs, plugins, agents, and orchestration layers expand the enterprise attack surface around AI systems.

Workflow Abuse

AI systems connected to internal workflows may expose sensitive systems, automate unsafe actions, or inherit excessive trust.

AI EXPOSURE IS EVOLVING

AI Systems Are Already Connected To Business-Critical Operations. Most Organizations Haven’t Validated The Exposure.

AI tools increasingly influence enterprise workflows, operational decisions, internal systems, APIs, and sensitive business data. Redbot Security identifies exploitable attack paths affecting connected environments, integrations, retrieval pipelines, and inherited trust relationships before attackers uncover them first.

Prompt Injection

Retrieval Poisoning

Workflow Abuse

Connected System Exposure

ASSESSMENT OUTCOMES

Redbot Delivers Clear Validation Across AI Attack Surfaces.

Redbot Security delivers manually validated findings, operational risk analysis, attack-path visibility, and actionable remediation guidance across connected AI environments.

FINDINGS

Manually Validated Exposure

Every finding is manually verified to identify realistic attack paths affecting AI systems, integrations, workflows, APIs, and operational trust relationships.

RISK ANALYSIS

Operational Impact Visibility

Redbot maps how exploitable AI exposure may affect sensitive business workflows, internal systems, enterprise data, and connected infrastructure.

REMEDIATION

Actionable Security Guidance

Findings include prioritized remediation guidance designed to reduce exposure across AI workflows, integrations, retrieval systems, and connected environments.

REPORTING

Executive & Technical Reporting

Redbot delivers clear reporting designed for both technical teams and leadership stakeholders requiring operational visibility into AI-related risk.

AI ATTACK SURFACE COVERAGE

Operational AI Exposure Extends Across Connected Enterprise Systems.

Redbot validates exploitable conditions affecting AI workflows, retrieval systems, integrations, agents, APIs, and operational trust relationships across enterprise environments.

Manual Validation Human-Led Testing

Real-World Attack Paths

Actionable Security Intelligence

ADVERSARIAL

AI TESTING

Prompt Injection

Jailbreak Testing

Behavioral Manipulation

Workflow Abuse

AI SECURITY

VALIDATION

RAG Security

Memory Exposure

Vector Database Risk

Context Poisoning

ENTERPRISE

AI RISK

Agent Security

Cloud AI Workflows

Operational Trust

AI Integration Risk

What is AI penetration testing?

AI penetration testing is a security assessment designed to identify exploitable vulnerabilities affecting AI systems, large language models, AI agents, retrieval pipelines, APIs, integrations, and connected enterprise workflows. Redbot performs manual adversarial testing to validate how attackers may manipulate AI behavior, expose sensitive data, abuse operational trust, or pivot into connected infrastructure.

Can AI systems be hacked?

Yes. AI systems can be manipulated through prompt injection, jailbreak attacks, insecure plugins, retrieval abuse, workflow manipulation, memory exposure, poisoned context data, excessive permissions, and vulnerable integrations. Attackers increasingly target connected AI infrastructure rather than models alone.

What does Redbot test during an AI security assessment?

Redbot validates exploitable exposure across AI workflows, RAG pipelines, AI agents, cloud AI infrastructure, vector databases, orchestration systems, APIs, enterprise integrations, authentication trust relationships, and operational automation connected to AI-enabled environments.

What is prompt injection testing?

Prompt injection testing evaluates whether attackers can manipulate AI instructions, bypass operational controls, override trust boundaries, leak sensitive data, influence downstream workflows, or trigger unintended system behavior through crafted prompts or malicious context inputs.

What is RAG security testing?

RAG security testing focuses on retrieval augmented generation systems connected to enterprise knowledge sources, vector databases, document pipelines, internal search systems, and operational data stores. Redbot validates whether retrieval workflows can be poisoned, manipulated, abused, or leveraged to expose sensitive information.

Why are AI agents considered high risk?

AI agents often maintain elevated operational permissions across APIs, cloud systems, automation workflows, internal applications, and enterprise infrastructure. If compromised, attackers may gain indirect access to connected systems capable of performing sensitive business actions at scale.

What industries require AI security testing?

Organizations operating in healthcare, finance, SaaS, critical infrastructure, legal services, manufacturing, defense, logistics, insurance, and enterprise technology increasingly require AI security validation to reduce operational exposure and protect sensitive enterprise workflows.

What is the difference between AI red teaming and AI penetration testing?

AI penetration testing focuses on identifying exploitable technical vulnerabilities affecting AI systems and connected infrastructure. AI red teaming expands beyond technical validation to simulate realistic adversarial behavior, operational abuse, workflow compromise, manipulation techniques, and enterprise attack paths.

Does AI security testing include APIs and cloud integrations?

Yes. Modern AI systems depend heavily on APIs, cloud services, orchestration platforms, plugins, external tools, retrieval systems, and third-party integrations. Redbot validates how exploitable exposure across connected infrastructure may impact operational security and enterprise trust relationships.

Why is manual AI security testing important?

Automated scanners cannot accurately simulate adversarial reasoning, workflow abuse, operational manipulation, or realistic AI attack chains. Redbot performs manual adversarial validation to identify complex attack paths affecting connected AI-enabled enterprise environments.