Services
AI security
& secure LLM integration
LLMs in industrial systems are only viable when risks such as prompt injection are designed in from the start. We review your architecture against the OWASP LLM Top 10, harden LLM interfaces, and run firmware security audits.
LLM integration
Secure LLM systems
OpenAI GPT API
Chat Completions, structured outputs, streaming
Function/tool calling
Deterministic tool execution with validation
MCP (Model Context Protocol)
Secure context handoff to agents
Agent orchestration
Multi-step pipelines with supervisor control
Prompt injection defense
Input sanitization, output filtering, allowlists
Rate limiting & audit logs
Monitoring all LLM requests and responses
Firmware security
Critical threats
Unauthorized instruction execution via crafted inputs — business‑critical for AI agents in industrial processes.
Unfiltered LLM output can lead to XSS, SQL injection, or unauthorized code execution.
OTA updates without signature verification allow malicious firmware to be deployed to field devices.
Hardcoded passwords in firmware — one of the most common findings in IoT security audits.
Reference project
AUTO-004: Firmware security audit
200+ IoT modules in the field — firmware security audit, hardened OTA rollout, and technical NIS2 readiness evidence documentation prepared.
View case study →Review LLM or IoT security?
We analyze your architecture for prompt injection risks and firmware vulnerabilities.
Request a free assessment