Professional Cyber Security Services
A security assessment of where your models, data and AI components come from, and of the pipelines that train, package and deploy them.
Modern AI systems are assembled from many parts: pre-trained models downloaded from public hubs, open-source libraries, datasets from internal and external sources, fine-tuning pipelines, vector databases, model provider APIs and a growing list of AI vendors. Each part is a place where an attacker can introduce a backdoor, steal intellectual property or interfere with how the system behaves.
Model files can contain executable code that runs when they are loaded. Training data can be poisoned to create hidden triggers. A compromised pipeline credential can let an attacker replace a production model. The AI Supply Chain & Pipeline Assessment examines these risks across the full lifecycle of your AI systems.
How pre-trained and third-party models are selected, verified and stored, including checks for unsafe serialization formats, provenance and signing.
How training, fine-tuning and retrieval data is collected, labeled, validated and protected against poisoning, leakage and unauthorized modification.
Open-source ML libraries, notebooks, containers and plugins, including known vulnerabilities, typosquatting risk and version control.
Access controls, secrets, build integrity, artifact registries and promotion gates in the pipelines that train and deploy models.
How models are versioned, approved and deployed to production, and whether an attacker could substitute or tamper with a model undetected.
Data handling, security commitments, access controls, isolation and incident notification terms for model providers, AI platforms and AI-enabled SaaS.
We combine architecture review, configuration analysis and hands-on testing. Our engineers bring experience from CI/CD pipeline penetration testing and malicious developer threat assessments, which we apply to ML-specific tooling such as experiment trackers, feature stores, notebook environments and model registries. Where appropriate, we attempt realistic attacks, such as introducing a malicious model artifact or abusing pipeline credentials, to show impact.
Findings are mapped to MITRE ATLAS, OWASP Top 10 for LLM Applications, the NIST Secure Software Development Framework and/or ISO/IEC 42001 controls.
We document how models and data move from source to production, including every tool, service and credential involved.
We review pipeline definitions, access controls, registry settings and dependency management.
We test key controls with targeted attacks agreed in advance.
We deliver prioritized findings and a hardened reference pipeline design.
AI supply chain map with trust boundaries
Findings on model, data, dependency and pipeline risks
Third-party AI provider risk summary
Recommendations for model signing, provenance tracking and AI bill of materials (AI-BOM)
Hardened MLOps reference architecture
Our risk reduction strategy melds unparalleled technical acumen with a client-focused approach to deliver targeted, cost-effective, and accessible solutions that fortify your organization against the ever- evolving cyber threat landscape.
We leverage our cybersecurity expertise to safeguard your business integrity, ensuring you operate securely, move forward confidently, and build trust in an interconnected digital world.
We deploy cutting-edge cybersecurity measures and personalized strategies to offer unwavering data protection, reinforcing our commitment to preserving your company’s invaluable digital assets.
Reach out to us today and discover the potential of bespoke cybersecurity solutions designed to reduce your business risk.