Data leakage
Sensitive data flows out through prompts, retrieval, training, or agent tool calls.
Data Runtime People
Shadow AI
Employees and teams adopt ungoverned AI tools, agents, and MCP servers.
Enterprise Runtime People
Hallucination & grounding failure
Confident, wrong output presented as fact — and acted on.
Models Applications
Prompt injection
Attacker instructions — typed directly or hidden in content the AI reads — hijack behavior.
Applications Agents Runtime
Unsafe or off-brand content
AI systems produce harmful, offensive, or reputation-damaging output.
Models Applications Runtime
IP & copyright exposure
Training-data provenance, output infringement, and ownership ambiguity.
Enterprise Data Models
Bias & discrimination
AI decisions create disparate impact — and legal liability — at scale.
Enterprise Models
Model supply chain
Poisoned weights, unsafe formats, unvetted models, and silent version churn.
Models Runtime
Agent autonomy failure
AI that acts — wrongly, destructively, or beyond its mandate.
Agents Runtime
Unauthorized access & identity
Humans, workloads, and agents reaching AI systems — or data — they shouldn't.
Data Agents Runtime
Regulatory non-compliance
Obligations attach to deployers, not just AI builders — and dates are set.
Enterprise
Runaway cost
Unbounded usage — human or agentic — turns AI economics upside down.
Enterprise Agents Runtime