Prompt Security

Prompt Security is a specialized cybersecurity platform designed to help organizations manage the unique risks associated with generative AI and large language models (LLMs). As businesses increasingly integrate LLMs into their workflows and applications, they face new vectors of vulnerability, such as prompt injection, data leaks, and compliance issues. This platform addresses these challenges by offering tools to identify, analyze, and secure vulnerabilities within LLM-based applications. It serves developers, security teams, and enterprise administrators who need to ensure that their AI deployments remain safe and compliant with industry standards. By monitoring interactions and system integrations, the tool provides visibility into potential threats, helping teams proactively defend their infrastructure before exploits can occur. Ultimately, it bridges the gap between rapid AI adoption and robust enterprise security, allowing organizations to leverage generative AI technologies with greater confidence and reduced operational risk.

Key Features

  • Live developer prompt injection detection
  • Real-time secure code leakage protection
  • Open-source AI vulnerabilities testing tools
  • Custom agent safety governance managers
  • Automated malicious output text filtering

Use Cases

Use Case 1: Securing AI Coding Environments

Problem: Software teams risk leaking proprietary source code and sensitive API keys into third-party AI coding environments.
Solution: The scanner monitors developers' system prompts to prevent credentials and core IP from leaving the local machine.
Example: A compliance manager blocks an accidental upload of a secured database key into an AI coding workspace.

Use Case 2: Red-Teaming Enterprise Custom Models

Problem: Enterprises deploy customer-facing chat bots that can be easily manipulated to leak internal records via prompt injections.
Solution: Automated vulnerability assessment systems check deployed models to flag security flaws and toxic output triggers.
Example: A security engineer fuzz-tests a new customer support chatbot to prevent system prompt extraction attacks.

Target audience: Best for: Chief Information Security Officers, DevSecOps teams, Compliance managers

Pricing: Open Source · Categories: Developer Tools, Startup tools

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Tags: AI, developer tools, Generative AI

Visit Prompt Security

What does Prompt Security do?

Prompt Security monitors and defends generative AI applications and development environments against cybersecurity vulnerabilities. It identifies prompt injection attacks, blocks confidential source code and credentials from leaking into external models, detects malicious outputs, and supplies governance controls to manage AI agents safely across enterprise workflows.

How much does Prompt Security cost?

Prompt Security is an open-source tool. Organizations, developers, and DevSecOps teams can access and implement its security capabilities without paying commercial licensing fees. Because it is distributed as open source, teams can deploy the code, inspect its safety mechanisms, and adapt vulnerability testing directly to their existing infrastructure.

Who should use Prompt Security?

The platform is primarily designed for Chief Information Security Officers, DevSecOps engineers, and enterprise compliance managers. It is suitable for technical teams building customer-facing chatbots, deploying custom AI agents, or overseeing developer environments where proprietary source code might accidentally be shared with external language models.

How does Prompt Security prevent data leaks?

Prompt Security scans developer prompts and system interactions in real time to stop sensitive data from leaving the local workspace. By actively monitoring prompts, it prevents accidental exposure of proprietary code bases, secured database keys, and private API credentials before they are sent to third-party AI models.

How does Prompt Security handle prompt injection attacks?

The software delivers live detection tools to identify prompt injection attempts in AI coding workflows and deployed applications. It also includes automated testing utilities to red-team enterprise models, helping security engineers fuzz-test conversational interfaces, uncover toxic triggers, and block system prompt extraction before attackers exploit them.

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