Prompt injection is the “SQL Injection” of the AI era. It occurs when malicious actors craft inputs that trick a Large Language Model (LLM) into ignoring its system instructions, leaking data, or executing unauthorized actions. At AONIQ Security, we don’t rely on fragile, “black-box” filters. We provide a comprehensive defense-in-depth strategy that combines architectural guardrails, robust input/output sanitization, and adversarial testing to ensure your models follow your rules—and only yours.
Modern injection attacks come in many forms, and a truly secure system must account for all of them:
Direct Injection (Jailbreaking): Users attempting to bypass safety filters to generate prohibited content or reveal system prompts.
Indirect Injection: Malicious instructions hidden in external data sources—like websites, emails, or documents—that the LLM “reads” and inadvertently executes.
Recursive Injection: Multi-step attacks designed to gradually wear down model constraints over a conversation.
AONIQ helps you move away from reactive “cat-and-mouse” filtering toward a defensible security architecture.
We implement architectural patterns that separate "User Content" from "System Instructions." By using delimiters and specialized data-handling layers, we reduce the model’s tendency to confuse data with commands.
We deploy and tune specialized "Guardrail Models"—lightweight, high-speed classifiers that inspect inputs and outputs in real-time to intercept malicious intent before it reaches your core LLM.
The threat isn't just what goes in—it's what comes out. We ensure that model outputs are treated as untrusted data, preventing the AI from being used as a vector for XSS, SSRF, or unauthorized API execution in your backend.
Automated defenses are only as good as the threats they’ve seen. Our experts conduct manual, adversarial simulations—using "Grandmaster" level injection techniques—to identify the edge cases that standard filters miss.
We move past simple keyword blocking (which is easily bypassed by "leet-speak" or translation attacks) toward semantic intent analysis.
Our defense strategies are optimized to ensure security doesn't introduce latency or degrade the user experience.
As new injection techniques (like "Many-Shot" or "ASCII-art" injections) emerge, our research-led approach keeps your defenses ahead of the curve.
