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AI Component Security

AI Component Security

Healthcare / Life Sciences

34%

Finance / Banking

29%

E-commerce / Retail / Marketing Tech

22%

Vulnerabilities Closure Rate

Critical vulnerabilities Closure Rate

Common Security Risks

Model Inversion & Extraction

Adversarial Examples

Dependency & Supply Chain Vulnerabilities

Unprotected Endpoints & APIs

Poisoned Training Data

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).
Cyber Shakthi Benefits

Benefits of Choosing Cyber Shakthi

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.

Fintech & Banking
SAAS & B2B
Healthcare
Education Technology
E-commerce & Retail
Logistics & Supply Chain

Cyber threats bankrupt businesses every day. Be wise. Defend yours now.

Schedule time with me