AI Component Security
Ensures every layer of your AI infrastructure is resilient against manipulation, leakage, and unauthorized use.
We secure AI components across the entire AI lifecycle, including: Pretrained or Fine-tuned Models, Training Data Sets & Data Lakes, ML Frameworks (TensorFlow, PyTorch, etc.), Model Serving APIs & Endpoints, Inference Engines (ONNX, Triton, etc.), Automation Pipelines (MLflow, Airflow, etc.), Model Marketplaces / HuggingFace Integrations.
Top 3 Industries Most at Risk Without Proper AI Component Security
Vulnerabilities Closure Rate
Critical vulnerabilities Closure Rate
Common Security Risks
Model Inversion & Extraction
Attackers reconstruct training data or steal proprietary models using black-box API calls.
Adversarial Examples
Subtle manipulations to input data fool the model into incorrect outputs—critical in AI used for vision, security, or healthcare.
Dependency & Supply Chain Vulnerabilities
Third-party libraries used for training or inference may contain exploitable code.
Unprotected Endpoints & APIs
Model-serving APIs without proper auth or throttling can be abused, overloaded, or accessed for malicious use.
Poisoned Training Data
Data pipelines compromised to introduce bias, backdoors, or security flaws into model behaviour.
Our AI Security Testing Methodology:
- Static & Dynamic Security Analysis: Code reviews for pipelines, model logic, and framework configs, endpoint scanning for unauthorized access or data leaks.
- Attack Simulation: Adversarial testing (FGSM, PGD, DeepFool), model extraction and fingerprinting tests, inference manipulation and API fuzzing, data poisoning simulations.
- Pipeline Security: CI/CD & MLflow review, storage access validation (S3, GCS, etc.), access control, and logging audits.
WHAT YOU RECIEVE
- AI threat landscape mapping (specific to your stack).
- Model & data-specific vulnerability report.
- Secure model deployment checklist.
- Recommendations for access control, audit logging, encryption, and hardening.
- Compliance alignment (ISO 42001, NIST AI RMF, GDPR).
Benefits of Choosing Canum
Deep expertise in both AI architecture and cybersecurity.
→Tailored testing for production, R&D, or cloud-deployed AI systems.
→Leveraging OpenAI, Vertex AI, SageMaker, and more.
→Focus on confidentiality, integrity, and ethical AI deployment.
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