Best AI Security Software for GitHub Copilot
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Compare the Top AI Security Software that integrates with GitHub Copilot as of July 2026
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This a list of AI Security software that integrates with GitHub Copilot. Use the filters on the left to add additional filters for products that have integrations with GitHub Copilot. View the products that work with GitHub Copilot in the table below.
What is AI Security Software for GitHub Copilot?
AI security software is a technology that uses artificial intelligence (AI) to protect online systems from malicious attacks. AI security software can also ensure that companies are using AI software and generative AI tools safely. It can detect potential threats and blocks them before they cause damage. AI security software provides additional protection beyond traditional methods such as firewalls, antivirus, and intrusion detection systems. AI security software can be used to protect not only corporate networks but also individual computers from cyberattacks. The AI algorithms use machine learning techniques to learn about the changing patterns of malicious behavior in order to identify new threats more quickly and accurately. It also has the ability to adapt its responses over time, making it a powerful tool for combating ever-evolving cyber threats. Many companies now deploy AI security software as part of their comprehensive cybersecurity strategy. Compare and read user reviews of the best AI Security software for GitHub Copilot currently available using the table below. This list is updated regularly.
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Backslash Security
Backslash
The software development lifecycle has fundamentally changed. Developers across engineering organizations are using AI coding tools — GitHub Copilot, Cursor, Windsurf, Claude Code, Gemini CLI — at scale. The security controls built for traditional development were not designed for this environment. Backslash Security addresses this gap directly. The platform gives security teams visibility into AI coding tool usage, the code being generated, MCP server connections made by AI agents, and the risk introduced before it reaches production. Core capabilities: AI coding tool inventory and policy enforcement MCP server visibility and access control Vibe coding security — risk detection in AI-generated code Continuous monitoring without disrupting engineering workflows Purpose-built for AI-native development — not a legacy scanner repositioned for a new market. For security leaders governing an environment they didn't design, Backslash provides the visibility and control you need. -
2
Golf
Golf
GolfMCP is an open source framework designed to streamline the creation and deployment of production-ready Model Context Protocol (MCP) servers, enabling organizations to build secure, scalable AI-agent infrastructure without worrying about boilerplate. It allows developers to define tools, prompts, and resources as simple Python files, after which Golf handles routing, authentication, telemetry, and observability, so you focus on logic, not plumbing. The platform supports enterprise authentication (JWT, OAuth Server, API key), automatic telemetry, and a file-based structure that eliminates decorators or manual schema wiring. With built-in utilities for LLM interactions, error logging, OpenTelemetry integration, and deployment tools (such as a CLI with golf init, golf build dev, golf run), Golf provides a full stack for agent-native services. Included also is the Golf Firewall, an enterprise-grade security layer for MCP servers that enforces token validation.Starting Price: Free -
3
Prompt Security
SentinelOne
Prompt Security enables enterprises to benefit from the adoption of Generative AI while protecting from the full range of risks to their applications, employees and customers. At every touchpoint of Generative AI in an organization — from AI tools used by employees to GenAI integrations in customer-facing products — Prompt inspects each prompt and model response to prevent the exposure of sensitive data, block harmful content, and secure against GenAI-specific attacks. The solution also provides leadership of enterprises with complete visibility and governance over the AI tools used within their organization. -
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Acuvity
Acuvity
Acuvity is the most comprehensive AI security and governance platform for your employees and applications. DevSecOps implements AI security without code changes and devs can focus on AI Innovation. Pluggable AI security results in completeness of coverage, without old libraries or insufficient coverage. Optimize costs by efficiently using GPUs only for LLM models. Full visibility into all GenAI models, apps, plugins, and services that your teams are using and exploring. Granular observability into all GenAI interactions with comprehensive logging and an audit trail of inputs and outputs. AI usage in enterprises requires a specialized security framework that is able to address new AI risk vectors and comply with emerging AI regulations. Employees can use AI confidently, without risking exposing confidential data. Legal would like to ensure there are no copyright, or regulatory issues while using AI-generated content. -
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Aurascape
Aurascape
Aurascape is an AI-native security platform designed to help businesses innovate securely in the age of AI. It provides comprehensive visibility into AI application interactions, safeguarding against data loss and AI-driven threats. Key features include monitoring AI activities across numerous applications, protecting sensitive data to ensure compliance, defending against zero-day threats, facilitating secure deployment of AI copilots, enforcing coding assistant guardrails, and automating AI security workflows. Aurascape's mission is to enable organizations to adopt AI technologies confidently while maintaining robust security measures. AI applications interact in fundamentally new ways. Communications are dynamic, real-time, and autonomous. Prevent new threats, protect data with unprecedented precision, and keep teams productive. Monitor unsanctioned app usage, risky authentication, and unsafe data sharing. -
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Matters.AI
Matters.AI
Matters.AI is the first AI Security Engineer for Data, built for the AI and data layer to autonomously see, understand, and resolve data misuse before the SOC opens a ticket. It protects what truly matters wherever data lives or travels, functioning like an AI security engineer that understands context, monitors behavior, and protects sensitive data autonomously across cloud, SaaS, endpoints, microservices, and AI pipelines. Matters is built on semantic intelligence, nearest neighbor search, data lineage modeling, and predictive behavior analysis, so it does not just detect threats; it understands context, anticipates risk, and takes action proactively. Instead of relying on static rules, regexes, dashboards, and noisy alerts, Matters reads between the lines, traces risk in motion, and never sleeps. It identifies sensitive data not just by how it looks, but by what it represents, tracking data across cloud, SaaS, endpoints, and beyond using fingerprinting and eBPF. -
7
GuardionAI
GuardionAI
GuardionAI is an Agent and MCP Security Gateway that provides unified security for AI agents and Model Context Protocol tools operating on enterprise data. It sits in the execution path to discover, redact sensitive data, enforce protection, and give teams visibility into actions that traditional SIEM, DLP, and identity layers cannot see. Every agent action is inspected, enforced, and logged at the protocol level across AI agents, LLM apps, RAG systems, chatbots, coding agents, MCP servers, internal tools, databases, operating systems, and cloud environments. GuardionAI protects against critical AI threats such as prompt injection, system override, web attacks, MCP tool poisoning, malicious code execution, NSFW content, PII and credential exposure, confidential data leakage, off-topic drift, and unauthorized access, mapped to OWASP LLM Top 10 and agentic AI threat frameworks. Its gateway provides four layers of protection.
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