What early-stage threat indicators look like before incidents become breaches, scandals, or policy crises.
Threat Intelligence
Early Warning
Jan 12, 2026
AI Risk Signals
Modern cyber threats no longer announce themselves.
They emerge quietly — through small, unusual signals hidden inside massive volumes of AI-generated activity.
These are known as AI risk signals.
And detecting them early is the difference between prevention and catastrophe.
What Are AI Risk Signals
AI risk signals are subtle indicators that an AI system, model, or agent is being used in a harmful or malicious way.
They are not full attacks — they are the warning signs that something dangerous is forming.
Examples include:
Repeated attempts to bypass model safeguards
Prompts that escalate from benign to harmful
Unusual automation patterns
Coordinated AI activity across multiple platforms
On their own, these signals look harmless.
Together, they form a threat.
Why Traditional Security Misses Them
Most security tools are built to detect:
Malware
Network intrusions
Data breaches
They are not built to understand:
Prompt behaviour
Agent logic
AI-driven workflows
As a result, organisations are blind to the early stages of AI-enabled attacks.
How Fortaris Detects Risk Signals
Fortaris continuously monitors multiple platforms for:
Prompt manipulation patterns
Automated agent behaviour
Model exploitation techniques
Cross-site AI coordination
Our system connects these weak signals into a single risk picture — allowing security teams to see threats before they fully materialise.
Why This Matters
By the time a traditional alert fires, damage has already begun.
AI risk signals provide something far more valuable:
early warning.
This gives governments, enterprises, and AI providers the time they need to intervene.
Final Thought
The future of cybersecurity will not be about reacting to breaches.
It will be about detecting intent — before it becomes action.
AI risk signals are where that future begins.