AI & ML Security
Security for models, prompts, and data pipelines — aligned to the OWASP Top 10 for LLM Applications.
Overview
AI systems introduce risks traditional testing misses: manipulated prompts, poisoned training data, leaked model outputs, and insecure ML pipelines. We assess your AI features and infrastructure against these emerging threats.
What we cover
The ground a typical engagement covers — always tailored to your scope.
Prompt injection and jailbreak testing
Training-data poisoning and integrity risks
Model theft, inversion, and output leakage
Insecure ML-Ops pipelines and supply chain
Sensitive-data exposure through model responses
OWASP LLM Top 10 alignment
What every engagement delivers
Impact-rated findings
Every issue rated by real-world impact and mapped to OWASP & MITRE ATT&CK — not just a raw CVSS score.
Developer-ready fix guidance
Practical, specific remediation steps for each finding, written for the engineers who'll fix it.
Executive summary
A board-readable view of risk and posture alongside the full technical detail.
Free retest
We re-test your fixes and issue a clean report you can hand to customers and regulators.
Related
Secure Code Review
Practitioner-led review of your source — not just SAST output — tracing untrusted input to dangerous sinks, mapped to exact file and line.
Learn moreAPI Security Testing
REST, GraphQL, gRPC, and SOAP endpoints tested against the OWASP API Security Top 10 — where modern breaches increasingly begin.
Learn moreArchitecture Review
Design-level threat modeling of trust boundaries, authentication flows, and data handling — catching whole classes of risk before a line ships.
Learn moreReady to get started
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