Solutions
A controlled, auditable and evolving security framework, from risk assessment and architecture design to ongoing operations.
Cybersecurity
MLPS Compliance
Aligned with MLPS 2.0 — consulting, design, remediation and assessment to meet compliance and strengthen real defense.
Security operations
Build SOC capability for monitoring, analysis, response and review — 24×7 duty and continuous improvement.
Security assessment
Penetration testing, scanning, baseline checks and hardening — validate defenses and deliver actionable remediation.
IoT Security
Device onboarding security, edge protection and IoT platform hardening for connected environments.
Data security
Key work across the data lifecycle: discovery and assessment, protection and auditing, governance and improvement.
Data discovery & classification
Map where data resides, who owns it and how it moves, then connect classification to access, sharing and outbound protection.
Data security risk assessment
Assess technical and organizational weaknesses across collection, storage, use, transfer, sharing and disposal, with prioritized remediation and verification.
Data loss prevention
Connect sensitive-content detection, risk-based policies and audit response across endpoints, applications and sharing channels.
Data masking and privacy
Design data minimization, masking and access protection for testing, analytics, sharing and display, validating usability and residual exposure.
Data access and audit
Connect account privileges, access activity and approval records to support least privilege, anomaly detection and traceability.
Data governance
Align business ownership, data policies and technical controls, connecting discovery, assessment, loss prevention, masking and auditing into continuous improvement.
AI security
LLM Application Security
A unified security control point for prompt-injection defense, input/output inspection, sensitive-data protection, access control and model-call audit.
AI Data Leakage Prevention
Based on Xingshu’s three-tier architecture to control AI tool data egress — sensitive data stays controllable, auditable and traceable.
Model Security Assessment
Red-team models, APIs, plugins and supply chains for jailbreaks, backdoors, model theft, resource abuse and dependency risk, with verifiable remediation.
AIGC content security
An operational loop for multimodal risk detection, policy decisions, human review, sample feedback and audit across generated content.
RAG security
Protect retrieval and generation against unauthorized access, knowledge poisoning, sensitive-fragment leakage and ungrounded responses.
AI Agent Security
Control autonomous tool use through agent identity, least privilege, instruction isolation, allowlists, human approval and complete action audit.
Project delivery process
Discovery
Clarify scenarios, asset boundaries, compliance needs and priorities.
Design
Define architecture, product selection and implementation roadmap.
Implementation
Deploy, configure policies and accept tested, usable capabilities.
Operations
Continuous monitoring, response and iteration for long-term assurance.