Skip to content
Prompt injection detection software monitors prompts sent to AI tools, whether entered by employees or generated by AI agents, to identify potentially malicious instructions and prevent unauthorized data exposure. However, many tools on the market are built for developers securing their own AI applications, rather than organizations looking to protect employees who use AI tools across the business.
This guide covers what to look for when protecting a whole organization from prompt injection attacks.
Why Do Businesses Need Different Prompt Injection Detection Than Developers?
Most prompt injection detection tools fall into three groups, all of which protect an AI application that a team is building and controls:
- Guardrail libraries that screen inputs to an application
- Open-source detectors
- Testing tools that probe an application for weaknesses
Businesses face a different challenge. Employees use third-party assistants, AI features embedded in approved software and unsanctioned tools. Increasingly they also use agents capable of taking actions on their behalf. Because organizations do not control the underlying code of these tools, they cannot simply integrate a guardrail into the applications.
Open-source prompt injection detectors are useful for teams building their own AI applications, but they do not give security teams visibility or enforcement across the company. While builder-side controls are still important, they are best treated as requirements for AI vendors. Ask each vendor how it separates trusted instructions from external content, screens inputs and tests its product against prompt injection.
What To Look For In Prompt Injection Detection Software
These five criteria separate tools that protect a whole organization from those that protect a single application.
1. It Covers Every AI Tool, Not Just Approved Ones
Effective detection sees every AI tool on the device, approved or not. Detection software limited to sanctioned services or browser traffic misses unapproved apps, desktop software and AI features built into other products, which is where shadow AI is hardest to spot.
Question to ask vendors: Does the technology detect AI use outside the browser and outside our approved list?
ADX Vision 2.0 runs on the endpoint and monitors popular large language models (LLMs), AI-powered productivity tools, browser-based AI interfaces and AI embedded in enterprise applications on Windows and macOS.
2. It Inspects Prompts From AI Agents As Well As People
Agent-generated prompts need the same scrutiny as typed ones because humans don’t read them before they are sent. An agent that summarizes a web page or processes an email can carry hidden instructions straight into its next action, a route known as indirect prompt injection. This makes agent prompts central to agentic AI security.
Question to ask vendors: Are prompts from agents and connected tools inspected with the same checks as prompts typed by staff?
ADX Vision 2.0 applies the same protections whether a prompt is written by an employee or generated by an AI agent.
3. It Uses Layered Detection, Not Keyword Lists
Reliable detection combines several methods as attackers rephrase or disguise instructions to pass simple filters. The Open Worldwide Application Security Project (OWASP) LLM01:2025 entry describes attackers using multiple languages or encodings such as Base64 to evade filters.
Look for prompt injection detection that combines pattern matching with structural and context-switch checks, and that also flags jailbreak attempts, where a prompt tries to talk the model out of its safety rules.
Question to ask vendors: Which detection methods does the tool combine, and how does it handle encoded or rephrased instructions?
ADX Vision 2.0 uses seven layers of prompt protection: context switching protection, obfuscation protection, jailbreak detection, data exfiltration protection, dangerous prompt pattern detection, fuzzy keyword detection and structural anomaly detection.
4. It Blocks Data From Leaving, Not Just Raises An Alert
Detection alone is not enough. Organizations need controls to prevent sensitive data from leaving the business if a prompt injection attack succeeds. OWASP notes that it is unclear whether any method can fully prevent prompt injection, making it essential to stop unauthorized data exfiltration in real-time. An alert issued after data has been exposed cannot reverse the damage.
Question to ask vendors: Can the tool block sensitive data from being sent or does it only alert after the fact?
ADX Vision 2.0 lets organizations set company or department-level controls for sensitive information, such as credit card numbers, Social Security numbers and domain-specific terms. When it stops an interaction, the data is not sent and administrators can see the blocked action.
5. It’s Simple To Deploy And Leaves An Audit Trail
Security teams need detection that deploys quickly, works wherever staff are and produces records for compliance. Proxy-based tools route traffic through a gateway and can miss devices not going through it, while browser extensions only see browser activity. Audit logs of AI interactions support governance reporting as regulation evolves.
Question to ask vendors: What does deployment involve, does it work off the corporate network and what audit records does it produce?
ADX Vision 2.0 deploys with BlackFog’s lightweight agent, with no proxies or browser plugins, and analysis happens on the device without requiring cloud connectivity. Optional prompt auditing for leading frontier LLMs records what is shared with AI systems.
How BlackFog ADX Vision 2.0 Detects Prompt Injection
ADX Vision 2.0 is an independent control layer for AI that runs on the endpoint, inspecting prompts before they leave the device and reach an AI service. It can also redirect requests from personal AI accounts to the company’s sanctioned LLM service, keeping corporate data in approved environments.
It forms part of the ADX Platform, alongside ADX Protect, BlackFog’s ransomware and exfiltration protection. ADX Vision 2.0 governs how AI and agents use data, while ADX Protect prevents unauthorized data exfiltration on the endpoint. Together they help organizations protect sensitive data from AI-related risks and traditional cyberattacks.
Before choosing a tool, see where AI and agents touch your data. ADX Vision 30, a 30-day AI exposure audit, shows how AI is used across your organization and gives you the evidence to apply these criteria.
