Indirect prompt injection attacks are an architectural security problem in transformer models that cannot be solved through training alone and can lead to significant losses in production environments.
AI agents require a rethinking of Zero-Trust strategies because classical onboarding processes do not work for short-lived, autonomous systems and have already led to database losses.
SIEM, SOAR, and specialized AI-SOC vendors use identical marketing terms for fundamentally different product categories with diverging impact on security outcomes.
Skill Engineering defines design commands like “bolder” or “quieter” for agents through concrete operational parameters instead of vague instructions to increase quality and consistency.
Valmis addresses the security challenge of AI agents through a proxy architecture where containerized agents can only make API requests via secure credential management.
Existing IGA tools fail to recognize that AI agents operate without personnel records, assigned managers, and defined end dates — a fundamental governance problem for increasingly autonomous AI systems in the enterprise.
Cursor is massively scaling its Forward Deployed Engineering division to meet growing demand for enterprise specialists who integrate AI agents into complex company-wide development processes.
Poisoned MCP tool descriptions can trick AI agents into exfiltrating business-critical data to external systems while each individual step appears legitimate.
Agents with explicit rules are suited for known patterns and deterministic decisions, while LLMs demonstrate their value in interpretation-intensive tasks without predefined solution paths.
