Governance · 1 minute read
Securing AI Systems: A Practical Guide
Securing AI systems means covering both normal software security and AI-specific risks: prompt injection, data leakage through prompts and outputs, model and API abuse, poisoned training data, and over-permissioned agents. Defend with strict access control, input and output filtering, guardrails, least-privilege for agents, secure data handling, and monitoring. AI adds new attack surfaces on top of standard risk, so security must be designed into the system, not bolted on after launch.
AI systems add new attack surfaces on top of normal software risk. Here are the AI-specific threats and how to defend against them—beyond the security basics.
AI-specific threats
| Threat | What it is |
|---|---|
| Prompt injection | Malicious instructions in input/content |
| Data leakage | Sensitive data via prompts, outputs, logs |
| Model/API abuse | Cost attacks, scraping, misuse |
| Poisoned data | Corrupted training data |
| Over-permissioned agents | Agents taking unintended actions |
These sit on top of standard software security—see enterprise AI security and the AI security checklist.
Prompt injection
Malicious instructions hidden in input or retrieved content can trick an LLM into ignoring rules or leaking data. Defend with input/output filtering, guardrails, least-privilege, and never trusting model output for sensitive actions without checks.
Securing agents
An over-permissioned agent is a major risk because it takes real actions, not just answers. Give it least-privilege, scope actions tightly, require approval for sensitive operations, and log everything—see AI agent security risks and agent human oversight.
Protect data
Minimize sensitive data in prompts and logs, encrypt it, and enforce access control—the discipline behind AI data privacy compliance and data security offshore.
Design security in
AI security can't be bolted on after launch—it's designed into access, data flow, and agent permissions from the start.
Why FISTA
FISTA Solutions builds AI with security designed in—access control, guardrails, least-privilege agents, and secure data handling—through AI enablement and enterprise security, backed by a verified 99.9% uptime record.
Securing your AI systems? Talk to FISTA.
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01What are the main security risks in AI systems?
Standard software risks plus AI-specific ones: prompt injection, data leakage through prompts and outputs, model and API abuse, poisoned training data, and over-permissioned agents taking unintended actions. Each needs specific defenses.
02What is prompt injection?
An attack where malicious instructions hidden in input or retrieved content trick an LLM into ignoring its rules or leaking data. Defend with input/output filtering, guardrails, least-privilege, and not trusting model output for sensitive actions without checks.
03How do I secure an AI agent?
Give it least-privilege access, scope its actions tightly, require approval for sensitive operations, log everything, and validate its actions. An over-permissioned agent is a major risk because it can take real actions, not just answer.
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