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Free Security Assessment

AI Security Services

Protect LLMs, Models & Workflows

Securify’s AI Security Services safeguard LLMs, machine learning pipelines, and AI workflows against adversarial attacks, data poisoning, and compliance gaps. We combine ethical AI frameworks like NIST AI RMF with technical defenses—hardening cloud-hosted models (AWS SageMaker, Azure ML), auditing for bias in training data, and blocking prompt injection exploits. From generative AI to predictive analytics, our solutions ensure personalized innovation for our clients. 

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Secure AI Implementation & Integration

AI Penetration Testing

Stress-test LLMs, APIs, and ML pipelines against:

  • Prompt Injection Attacks: Jailbreaking ChatGPT-style models
  • Data Poisoning: Detecting tampered training datasets
  • Model Inversion: Preventing extraction of sensitive training data

Hosting & Access Security

Fortify AI deployments across environments:

  • Cloud AI Security: Hardened AWS SageMaker, Amazon Bedrock and Azure ML setups
  • Zero Trust for APIs: MFA for LLM endpoints, rate limiting
  • Data Lineage Tracking: Audit trails for training data (GDPR/PDPA)

AI Governance & Compliance

Ethical AI Frameworks

Align with global standards:

  • NIST AI RMF (Risk Management Framework)
  • EU AI Act compliance readiness
  • ISO 42001 (AI Management Systems)

Risk & Policy Management

Build trust through transparency:

  • Bias/Fairness Audits for ML models
  • Custom AI Acceptable Use Policies
  • Third-Party Vendor AI Risk Assessments

Proactive AI Threat Modeling

Map Attack Surfaces

We catalog risks across data ingestion pipelines, model inference APIs, and third-party AI plugins, identifying exposure points like unencrypted training datasets or overprivileged API endpoints.

 
Simulate Advanced Threats

Using various tools, we simulate evasion attacks (e.g., perturbing inputs to fool computer vision models) and membership inference attempts to isolate data privacy leaks.

Build Defense Strategies

Deploy Fiddler for real-time model monitoring, automate red teaming pipelines to test defenses iteratively, and isolate critical models in secure enclaves with hardware-backed encryption.

Compliance Alignment

Validate adherence to EU AI Act transparency mandates and ISO 42001 controls, ensuring audit trails for training data lineage and ethical AI use case approvals.

Continuous Adaptation

Update threat models quarterly with MITRE ATLAS intelligence, retrain models on sanitized datasets, and enforce MLOps security gates for CI/CD pipeline integrity.

Why Securify for AI Security?

Deep AI Expertise

  • Highly qualified ML engineers
  • OWASP Top 10 for LLM contributors

Full-Lifecycle Protection

  • Data collection → Model retirement
  • CI/CD security for MLOps

Compliance Across Jurisdictions

  • GDPR, CCPA, AI Act readiness
  • SOC 2 Type II for AI systems

FAQs

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