Security Built for the Age of AI
LLMs, autonomous agents, and AI-generated code have created an entirely new attack surface. Traditional scanners were not built for it. NexusVoid was. We map your AI assets, test your models adversarially, and track your AI supply chain - continuously.
AI Unlocked New Attacks. Your Scanner Missed the Memo.
Prompt injection does not show up in a CVE. Model poisoning does not have a CWE entry. The threat landscape shifted, and most security tooling has not caught up.
Most teams ship LLM-powered features without ever testing what happens when someone tries to break them.
Hugging Face, PyPI, and npm are full of poisoned packages and backdoored models. Nobody is tracking them.
CVE databases were not built for prompt injection or model exfiltration. Your existing tools are flying blind.
From AI Asset Discovery to Adversarial Testing
Map Your AI Attack Surface
Connect your repos, model registries, and inference endpoints. Argus builds a complete inventory of every AI asset - models, prompts, agents, and data pipelines - in under 30 minutes.
Run AI-Specific Red Teaming
Phantom launches targeted adversarial campaigns against your LLMs. It tests for jailbreaks, prompt injections, model extraction attempts, and supply chain tampering - automatically, on a schedule.
Remediate with Context
Every finding comes with a severity score, a reproduction case, and a specific fix recommendation. Not just "this is broken" but exactly what to do about it.
Everything AI Security Demands
Six capabilities purpose-built for the threats that emerge when intelligence is a feature, not just a layer.
LLM Security Testing
Automated red-teaming for your language models - jailbreaks, prompt injection chains, system prompt leakage, and output manipulation. We throw 500+ adversarial prompts so you find the gaps before your users do.
AIBOM Tracking
An AI Bill of Materials that catalogs every model in your stack - the base model, fine-tuned layers, third-party adapters, and inference endpoints. If it runs inference, it is in the inventory.
AI Supply Chain Visibility
Track model provenance from Hugging Face to production. Get alerted when a model you depend on gets updated, and see whether the change introduces new risk.
Prompt Injection Detection
Continuous scanning of your agent inputs and tool-call chains. Catch indirect injection attacks in RAG pipelines, multi-agent workflows, and external data feeds before they execute.
Model Poisoning Simulation
Test your fine-tuning and training pipelines against data poisoning attacks. We simulate adversarial training data injection so you know exactly how robust your model actually is.
Agent Sandboxing Analysis
Autonomous agents can take real actions - browse, write code, call APIs. We map every tool a given agent can reach and score the blast radius if it gets hijacked.
Built for Teams That Ship AI
AI-First Companies
If your product is powered by LLMs, your product is a target. You need continuous security testing built into the same workflow you use to ship models.
Teams Using Copilot or ChatGPT APIs
Plugging OpenAI or Anthropic into your product creates data flows, prompt surfaces, and trust boundaries you may not have mapped. We map them for you.
Security Teams at AI-Adjacent Enterprises
Your developers are adding AI features faster than your security team can audit them. You need automated coverage, not more manual reviews.
AI threats need AI-native security
See Your AI Attack Surface Before an Attacker Does
Book a 30-minute session. We will map your AI assets live, run a sample adversarial prompt suite, and show you exactly what is exposed.