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AI & Machine Learning Security

Secure your AI systemsfrom data to deployment

As AI adoption accelerates, so do the risks. Our specialized assessments identify vulnerabilities in your ML pipelines, models, and training data that traditional security tools miss.

500+

AI Models Assessed

85%

Models Vulnerable to Extraction

100%

OWASP ML Top 10 Coverage

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Typical Assessment Timeline

Capabilities

Comprehensive AI security assessment

From adversarial machine learning to supply chain attacks, we evaluate every component of your AI infrastructure against the latest threat vectors.

Model Extraction Testing

Assess susceptibility to model stealing attacks through API enumeration, side-channel analysis, and distillation techniques.

Training Data Security

Evaluate data leakage risks, poisoning vulnerabilities, and privacy violations in your training datasets.

Adversarial Attack Simulation

Test model robustness against evasion attacks, perturbation techniques, and adversarial examples.

ML Pipeline Security

Comprehensive review of ML Ops pipelines, including CI/CD for models, feature stores, and experiment tracking systems.

Model Registry & Versioning

Assess security controls around model registries, versioning systems, and model deployment artifacts.

Inference API Security

Test model endpoints for information disclosure, rate limiting bypass, and denial-of-service vulnerabilities.

AI/ML Attack Vectors

Emerging threats to intelligent systems

AI systems introduce a new attack surface. We assess your resilience against these novel threats.

01

Data Poisoning

Attackers manipulate training data to corrupt model behavior or introduce backdoors.

  • Label flipping attacks
  • Trigger-based backdoors
  • Training data injection
02

Model Inversion

Reconstruct sensitive training data by exploiting model predictions and confidence scores.

  • Membership inference
  • Attribute inference
  • Training data extraction
03

Evasion Attacks

Craft adversarial inputs that cause misclassification while appearing normal to humans.

  • Adversarial perturbations
  • Physical-world attacks
  • Black-box evasion
Our Process

Specialized methodology for AI systems

Built on emerging frameworks like MITRE ATLAS and OWASP ML Top 10, our methodology combines data science expertise with offensive security techniques.

01

AI Asset Discovery

Identify all ML models, training pipelines, data stores, and inference endpoints across your organization.

02

Threat Modeling

Map potential attack vectors using MITRE ATLAS framework, considering data, model, and infrastructure layers.

03

Adversarial Testing

Simulate real-world attacks including model inversion, poisoning, and evasion techniques.

04

Remediation & Hardening

Provide model-specific defenses, adversarial training techniques, and architectural improvements.

Why Cynical?

Data scientists who think like attackers

Framework Agnostic

TensorFlow, PyTorch, scikit-learn, and custom models

Full Stack Coverage

Data, models, pipelines, and infrastructure

ML Ops Integration

Secure your entire ML development lifecycle

Data Science Expertise

Assessments by ML engineers and security researchers

Privacy Preserving

Differential privacy and federated learning assessments

Compliance Ready

GDPR, CCPA, and AI regulatory compliance

Coverage

Complete OWASP ML Top 10 coverage

Our assessments map directly to industry-standard frameworks for machine learning security, ensuring comprehensive coverage.

ML01: Input Manipulation Attacks
ML02: Data Poisoning
ML03: Model Inversion
ML04: Membership Inference
ML05: Model Theft
ML06: AI Supply Chain Attacks
ML07: Transfer Learning Attacks
ML08: Model Skewing
ML09: Output Integrity Violations
ML10: Model Poisoning
Protect your competitive advantage

Secure your AIbefore it's exploited

Get a specialized security assessment for your machine learning models, training pipelines, and AI infrastructure.

Response within 24 hours
NDA-protected briefing
Free exposure report included
No sales pitch, just findings

Trusted By Critical Industries

Banks

Governments

Healthcare

Fintech

Critical Infrastructure

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