Secure Your Models. Defend Your Data. Stay Ahead of Evolving AI Threats.
AI is revolutionizing industries, but it’s also expanding the attack surface in ways traditional security tools can’t fully address. As businesses adopt machine learning, large language models (LLMs), and generative AI, they face new risks like prompt injection, adversarial input, model tampering, and data leakage—all of which require specialized testing and protection.
Our AI/ML Security Services are designed to tackle these threats head-on. We simulate real-world attacks to test your AI systems for vulnerabilities, providing clear, actionable insights to strengthen your defenses. Whether you’re deploying custom models or integrating APIs like OpenAI or Anthropic, we help you secure your AI stack and move forward with confidence.
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What Is AI/ML Security?
AI/ML security protects artificial intelligence systems from threats like prompt injection, model manipulation, and data leakage.
AI/ML Security focuses on protecting artificial intelligence and machine learning systems from exploitation, manipulation, and misuse. As organizations deploy models for decision-making, automation, and customer interaction, these systems become attractive targets for attackers.
AI/ML security involves identifying vulnerabilities like adversarial inputs, prompt injection, model tampering, data leakage, and API abuse. It’s about testing not just the code—but the behavior, logic, and outputs of your models. Whether you’re building with OpenAI, deploying custom ML pipelines, or integrating AI into products, securing these assets is now mission-critical.
Who Needs AI/ML Security?
Organizations deploying AI or machine learning models—across industries like tech, finance, healthcare, and SaaS.
Our clients include:
Tech companies deploying LLM-powered apps
Fintech firms using AI for credit scoring or fraud detection
Healthcare providers relying on diagnostic ML models
SaaS platforms embedding AI assistants or copilots
Enterprises using AI to automate sensitive decisions
Whether you’re building in-house AI, using third-party models, or embedding APIs like OpenAI or Anthropic, we’ll help you test and secure it.
What Our AI/ML Security Services Include
Our AI/ML security services include expert-led testing for prompt injection, adversarial attacks, model tampering, insecure APIs, and data leakage.
| Service | Description |
|---|---|
| Adversarial ML Testing | Craft and deliver adversarial inputs to test model robustness and resilience. |
| Prompt Injection Testing | Identify vulnerabilities in LLMs (e.g., ChatGPT, Claude, Gemini) through malicious prompts. |
| Model Tampering Detection | Analyze models and APIs for unauthorized changes or poisoned training data. |
| LLM Misuse Simulation | Simulate real-world misuse scenarios, including jailbreaks and unintended outputs. |
| AI API Security Testing | Review access controls, API key handling, and input/output sanitization. |
| Bias & Hallucination Audits | Evaluate fairness, explainability, and risk of inaccurate or misleading outputs. |
Supported Platforms & Models
We secure AI/ML systems built on all major platforms including vector databases.
Open AI (GPT-4, GPT-4o)
Anthropic (Claude)
Meta Llama
Google Gemini
Mistral
Custom PyTorch
TensorFlow models
Pinecone
Weaviate
Milvus
LangChain
Llama Index
Haystack
ColBERT
OpenSearch
Compliance-Aligned, Expert-Led
AI/ML systems are increasingly under the microscope of regulators and customers.
NIST AI Risk Management
guidelines to identify, assess, and manage risks associated with AI systems for trustworthy and reliable deployment.
EU AI Act Readiness
Helps organizations prepare for compliance with the European Union’s upcoming regulations on safe and ethical AI use.
ISO 42001 AI Management
Establishes best practices for implementing effective management systems specific to AI technologies and processes.
SOC 2 & ISO 27001
Aligns AI security controls with widely recognized standards for data security, privacy, and operational excellence.
Why AI/ML Security Matters
AI/ML security matters because it protects your models and data from sophisticated attacks that can compromise accuracy, privacy, and trust.
| Outcomes | Description |
|---|---|
| Protects Against Model Manipulation | Prevents attackers from altering AI outputs or training data to cause errors or biased results. |
| Prevents Data Leakage | Safeguards sensitive training data from being exposed through model responses or API misuse. |
| Mitigates Prompt Injection Risks | Stops malicious inputs that can bypass AI safeguards or leak confidential information. |
| Ensures Compliance with Regulations | Helps meet emerging AI-related legal and ethical standards to avoid penalties and reputational harm. |
| Maintains Trust and Reliability | Builds user and stakeholder confidence by delivering consistent, accurate, and secure AI outputs. |
| Addresses Adversarial Attacks | Detects and defends against inputs designed to confuse or mislead AI models, ensuring robustness. |
| Protects Intellectual Property | Prevents unauthorized access or copying of proprietary AI models and data. |
| Supports Safe AI Adoption and Innovation | Enables organizations to confidently deploy AI solutions with minimized security risks. |
Why Choose Us for AI/ML Security?
Get expert-led, real-world testing, clear remediation guidance, free retesting, and tailored solutions built to protect your models and move fast.
Human-led Testing
Our human-led testing simulates real-world attacks with expert precision—far beyond what automated scanners can catch.
AI threat research
Our team stays ahead of evolving risks with cutting-edge AI threat research applied directly to your models, systems, and applications.
Clear Reporting
We deliver clear, actionable reports that translate complex AI vulnerabilities into practical fixes for developers, executives, and compliance teams.
Certifications
Our team holds industry-recognized certifications that reflect hands-on expertise across offensive security, cloud, incident response, and compliance.
Offensive Security Certified Professional (OSCP)
Certified Information Systems Security Professional (CISSP)
GIAC Penetration Tester (GPEN)
GIAC Cloud Penetration Tester (GCPN)
GIAC Cloud Penetration Tester (GCPN)
CompTIA Security+, Network+, A+, Pentest+
GIAC Certified Incident Handler (GCIH)
AWS Certified Cloud Practitioner (CCP)
Microsoft AZ-900, SC-900
Certified Cloud Security Professional (CCSP)
Certified Ethical Hacker (CEH)
Burp Suite Certified Practitioner (Apprentice)
eLearnSecurity Junior (eJPT)
Web App Penetration Tester (eWPT)
Systems Security Certified Practitioner (SSCP)
Palo Alto PSE Certifications
FAQs: AI/ML Security
Learn more information about the most frequently asked questions
What are the biggest security risks in AI/ML systems?
The most common risks include adversarial inputs, prompt injection, model tampering, data leakage, insecure APIs, and lack of access control—many of which traditional security tools can’t detect.
Do I need AI/ML security if I’m using third-party models?
Yes. Even when using third-party models, risks like prompt injection, over-permissioned APIs, and data exposure remain your responsibility—especially when integrating LLMs into your apps or workflows.
What types of models or platforms do you test?
We test models and integrations built on OpenAI, Claude, Gemini, Llama, custom PyTorch/TensorFlow, and platforms using LangChain, LlamaIndex, Pinecone, Weaviate, and other RAG frameworks.
Can you help us meet compliance for AI security?
Absolutely. We align your AI/ML environment with emerging frameworks like the NIST AI RMF, ISO 42001, and EU AI Act—and we integrate AI security into SOC 2 and ISO 27001 strategies.
How is AI/ML security testing vary from traditional testing?
AI/ML security focuses on model behavior, logic manipulation, and data misuse—testing risks that live outside the scope of traditional app or network penetration testing. It’s a new layer of security you can’t afford to ignore.