Risks of using LLMs

Common advanced LLM powered systems can have severe security risks.

Common security risks are:

• AI systems can malfunction when exposed to untrustworthy data, and attackers are exploiting this issue.

• New guidance documents the types of these attacks, along with mitigation approaches.

• Prompt injection.

• Leakage of personally identifiable information (PII)

• Harmful prompts. Relevant when you develop your ‘own’ LLM or LLM powered application.

No foolproof method exists for protecting ML/AI systems from security hacks. This is problematic when ML/AI systems are used for health systems, transport systems or weapons. Misdirection is a common threat.

Using LLMs for health saving systems or software that is used for safety applications (cars, trains, plains):

Danger

The outcome of LLMs should never be trusted. Despite imense progress on LLMs and their applications: Transparency is often absent and outcomes should never ever be trusted without a SOLID and GOOD human assessment!