Best IT Security Software for Cursor

Josys is an AI-native identity security and governance platform built for the age of enterprise AI. As AI adoption accelerates, identity has become the fastest-growing attack surface and the hardest to govern. Josys discovers, governs, and secures every identity in the enterprise, human, machine, and AI agent, across every application. Its policy-led model lets security and IT teams set access policies once and enforce them autonomously: risk gets surfaced, access gets controlled, and identity threats get remediated in real time, with no manual oversight required. Over 1,000 organizations and MSPs worldwide trust Josys to turn identity from a liability into an autonomously governed advantage. Learn more at josys.com.

Tragentics serves as a robust security platform for AI agents, ensuring that every agent is authenticated, securely retrieves keys from an encrypted Credential Vault—eliminating the need for agents to possess them directly—routes all communications through a content-blind relay, and maintains a metadata-only audit trail that spans various platforms and protocols. This platform does not perform any inference or execute agent logic, nor does it access or store the contents of agent communications. Each agent is assigned a unique permanent ID and an Ed25519 identity, with keys safeguarded at rest using AES-256-GCM encryption, while every interaction is authenticated, subjected to rate limiting, and logged solely as metadata, avoiding any capture of payload data. Moreover, Tragentics is protocol-agnostic, effectively managing traffic for existing agents, including MCP, A2A, ACP, OpenAI, ANP, and DID, providing a comprehensive solution for AI agent security. In this way, it enables organizations to enhance their security measures without compromising the functionality or privacy of their systems.

ZeroPath (YC S24) is an AI-native application security platform that delivers comprehensive code protection beyond traditional SAST. Founded by security engineers from Tesla and Google, ZeroPath combines large language models with deep program analysis to deliver intelligent security testing that finds real vulnerabilities while dramatically reducing false positives. Unlike traditional SAST tools that rely on pattern matching, ZeroPath understands code context, business logic, and developer intent. This enables identification of sophisticated security issues including business logic flaws, broken authentication, authorization bypasses, and complex dependency vulnerabilities. Our comprehensive security suite covers the application security lifecycle: 1. AI-powered SAST 2. Software Composition Analysis with reachability analysis 3. Secrets detection and validation 4. Infrastructure as Code scanning 5. Automated PR reviews 6. Automated patch generation and more... ZeroPath integrates seamlessly with GitHub, GitLab, Bitbucket, Azure DevOps and many more. The platform handles codebases with millions of lines across Python, JavaScript, TypeScript, Java, Go, Ruby, Rust, PHP, Kotlin and more. Our research team has been successful in finding vulnerabilities like critical account takeover in better-auth (CVE-2025-61928, 300k+ weekly downloads), identifying 170+ verified bugs in curl, and discovering 0-days in production systems at Netflix, Hulu, and Salesforce. Trusted by 750+ companies and performing 200k+ code scans monthly.

Dash0 is an OpenTelemetry-native observability platform for developers and SRE teams. Metrics, logs, traces, and resources sit in one place, linked by OpenTelemetry semantic conventions, so you move from a slow trace to the logs around it without switching tools or rebuilding context by hand. Telemetry arrives over OTLP. There is no proprietary agent to install and nothing to re-instrument: send the OpenTelemetry data you already collect, and take it elsewhere unchanged if you ever want to. Dash0 ingests Prometheus metrics alongside OpenTelemetry, supports PromQL, and imports existing Prometheus alerting rules and Grafana dashboards. A Kubernetes operator handles collection across clusters, covering workloads, nodes, and control plane. Dashboards are built on Perses and defined as code, so they live in Git and ship through the same review process as the rest of your infrastructure. Checks and alerts are configured the same way. Heatmap drilldowns and filtering on high-cardinality attributes narrow a broad symptom down to the specific requests behind it. AI works on the data rather than in a chat window. Log AI infers severity for logs that arrive without it, extracts patterns, and groups related records, which makes unstructured output from third-party services searchable and filterable. Trace triage uses the SIFT framework to narrow a failing request toward a likely cause. Spend is visible in the product. You can see which services, attributes, and log volumes drive cost and cut them at the source, rather than reconciling a bill after the fact.

Scalekit is the MCP gateway for AI agents. Developers and platform teams use it when an agent must call business tools as the user, not through a shared service account. One endpoint reaches 500+ connectors and 20,000+ tools, including Salesforce, Gmail, Slack, Notion, HubSpot, Jira, and GitHub. When the agent requests a tool, Scalekit finds that user's credentials, checks that the agent is allowed to call it, runs the call, and returns a clean response. Tokens stay in an AES-256 vault, isolated per tenant, and out of application code, logs, and the model prompt. Venu Madhav Kattagoni, Head of Engineering at Von, describes it this way: "Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer." Scalekit works with Anthropic, OpenAI, LangChain, Google ADK, Vercel AI, and Mastra. Managed cloud runs in the US (Los Angeles) or the EU (Frankfurt). EU data residency on Growth is a $99 a month add-on. Enterprise can run in a VPC or self-hosted, including air-gapped. Scalekit is SOC 2 Type II and ISO 27001 certified. A HIPAA BAA is available on Enterprise. The Free plan is $0 a month and includes 10,000 tool calls and 10,000 trigger events. Growth is $99 a month for 100,000 tool calls, then $0.50 per 1,000 calls. Enterprise pricing is custom, and includes SSO and SCIM for the Scalekit dashboard

Sitelemetry serves as a comprehensive hosted platform for auditing websites, catering to developers, web agencies, founders, and teams that manage business sites. It evaluates various aspects including security, technical SEO, AI-search optimization, accessibility, performance metrics, and tag integrations, delivering insights through evidence-backed scores, prioritized issues, and detailed remediation recommendations. Users can access audit results via a web dashboard or link compatible AI clients through a secure Model Context Protocol (MCP) server for requesting checks and generating prompts for fixes. While Google Search Console offers read-only access to search data, performance evaluations utilize Google PageSpeed Insights to gauge efficiency. The platform offers paid subscription options that encompass all six audit domains, along with scheduled monitoring and enhanced usage capacity, whereas the free plan restricts users to security assessments only. It’s important to note that Sitelemetry identifies and reports issues without automatically making changes to the websites it audits. This ensures that users maintain control over their site modifications while benefiting from the platform's insights.

Modern engineering teams have a math problem: AI coding assistants now produce the majority of new code, but the security stack underneath was built for an era when humans typed every line. Plexicus rewires that equation. We're an AI-native ASPM platform with Vibe Coding Security at its core — the first end-to-end solution that meets developers where they actually work, whether they're writing code by hand or pair-programming with Cursor, Claude Code, Copilot, Windsurf, Devin, Replit, Zed, or VS Code (JetBrains coming). What sets Plexicus apart isn't another dashboard of findings. It's the autonomous remediation loop: every detected risk arrives with a GenAI-generated pull request that fixes the root cause, lands in the developer's normal Git workflow, and clears triage queues before they form.

VibeSecurity is an advanced platform that employs artificial intelligence to conduct vulnerability scans, aimed at safeguarding code generated by AI by persistently evaluating, identifying, and addressing security weaknesses throughout the entire development process. This solution specifically targets contemporary “vibe coding” practices, where developers utilize AI tools to swiftly create code, often inadvertently incorporating concealed vulnerabilities such as insecure authentication methods, exposed tokens, or risks of injection attacks. It leverages intelligent agents to execute real-time analyses of the code, pinpointing security concerns prior to their deployment and offering automated recommendations for fixes along with guidance for implementation. By seamlessly integrating with developer environments via IDE plugins, GitHub applications, and CI/CD pipelines, it facilitates ongoing surveillance of repositories, pull requests, and deployments while ensuring that workflows remain uninterrupted. Additionally, VibeSecurity empowers developers by providing them with the tools they need to enhance the security of their code as they work, ensuring a proactive approach to vulnerability management.

Knostic functions as a comprehensive platform for enterprise AI security and governance, aiming to safeguard against data leaks and regulate the manner in which large language models utilize and disseminate information within businesses. It implements access controls based on a “need-to-know” principle, which adaptively decides what data an AI can disclose according to the user's role, the context, and their intent, instead of depending solely on conventional file permissions. By concentrating on the knowledge layer that exists between unprocessed data and AI-generated outputs, it scrutinizes how information is inferred, merged, and presented to guarantee that sensitive material is not inadvertently shared. Knostic also ensures ongoing monitoring of AI operations across various applications, including Copilot and other assistants powered by large language models, while pinpointing potential threats like semantic oversharing, exposure through inference, and unauthorized access to knowledge. Furthermore, it conducts simulations of practical prompts to reveal unnoticed vulnerabilities prior to their implementation, assigns numerical risk evaluations, and empowers organizations to apply detailed policies effectively. This dual focus on proactive risk assessment and ongoing governance positions Knostic as an essential tool for safeguarding organizational integrity in the evolving landscape of AI technology.

Weave is an engineering intelligence platform that helps organizations measure software delivery performance, developer output, code quality, AI adoption, and the economics of AI-assisted development. It analyzes engineering activity from AI prompts and token consumption through commits, pull requests, reviews, deployments, and production outcomes. The platform combines AI-specific measurements with established engineering frameworks such as DORA and SPACE to provide a unified view of software development performance. Token intelligence shows how spending is distributed across AI models, providers, engineers, and development tools while evaluating efficiency and quality alongside raw consumption. Organizations can use these metrics to compare AI-assisted output with historical baselines and identify where AI is contributing to measurable improvements or unnecessary costs. Weave Router automatically classifies prompts and sends them to models selected for an appropriate balance of cost, latency, and output quality. The router can work with AI providers including Anthropic, OpenAI, and Google while learning from feedback at both the user and organizational level. Wooly provides an AI interface for asking questions about engineering performance, AI usage, deployment bottlenecks, and team effectiveness using connected internal records as evidence. Weave is intended for engineering executives, development managers, platform teams, AI transformation leaders, and enterprises seeking greater visibility into the productivity and financial impact of AI coding tools.

Enkrypt AI is an AI security and compliance platform built to protect generative AI applications, autonomous agents, models, data, and AI infrastructure. It provides security agents and controls for detecting vulnerabilities, preventing threats, continuously monitoring AI systems, and automating compliance processes. Enkrypt AI's red teaming capabilities dynamically generate use-case-specific attacks that adapt during testing to uncover security, safety, and brand risks that static evaluations may miss. The platform addresses threats including prompt injection, jailbreaking, data leakage, model inversion, adversarial attacks, policy violations, hallucinations, model drift, bias, toxic content, deceptive behavior, and unmonitored agent actions. Real-time guardrails inspect AI interactions and can stop threats as they occur while continuously adapting based on prompts and observed activity. Monitoring capabilities provide ongoing visibility into AI risk and compliance so organizations can identify issues, track protection effectiveness, and maintain evidence for audits. Enkrypt AI can translate internal organizational policies and external regulatory requirements into automated guardrails to reduce manual compliance work. Its product portfolio includes Agent Red Teaming, Agent Guardrails, an Agent Policy Engine, AI Data Risk Audit, MCP Scanner, and MCP Gateway, with solutions for customer-facing agents, frontier models, third-party AI risk, AI compliance, MCP security, and secure AI development. The company also maintains an LLM Safety Leaderboard that continuously red teams and benchmarks more than 200 AI models to help organizations evaluate model security and safety.

Palo Alto Networks Cortex Agentic Endpoint Security (AES) is an endpoint protection and AI security governance platform designed to secure autonomous agents, developer tools, and software components across enterprise devices. The software provides continuous discovery of AI applications, local language models, MCP servers, browser extensions, IDE plugins, and open-source packages that may introduce security risks. Its AI-native visibility capabilities help security teams identify unauthorized software and previously unmanaged AI tools operating within their environments. Context-aware risk analysis evaluates application behavior, permissions, software supply chain relationships, and access to sensitive resources. The platform maintains an AI Context Graph that connects discovered assets with relevant security information to support risk assessment and investigation. Governance tools allow administrators to establish security policies, restrict unsafe interactions, and remove insecure packages or extensions. Runtime protection monitors autonomous agent activity and blocks prohibited actions, malicious downloads, prompt injection attempts, and potential data exfiltration. Cortex AES integrates with Cortex XDR and Prisma AIRS to combine endpoint monitoring with AI application security and threat prevention capabilities. Organizations can deploy the solution as a standalone security product or alongside existing endpoint security infrastructure, with optional managed protection and investigation services from Palo Alto Networks Unit 42.

Keycard is an advanced identity and access management platform tailored for the era of agent-driven technology, facilitating secure connections among AI agents, users, services, and APIs through real-time identity controls driven by policies. Instead of relying on static secrets, it generates dynamic, short-lived access tokens and accommodates federated identity systems to unify users, agents, and workloads within a decentralized authorization structure. Developers can leverage convenient SDKs compatible with popular frameworks, enabling them to create applications aware of agents without needing extensive IAM knowledge. The platform’s data architecture encompasses identity-validated agents, tasks, tools, and resources, which facilitate the establishment of logical zones equipped with permissions that are context-aware and subject to auditing. Additionally, security teams have the capability to formulate deterministic, task-oriented policies that clarify who (whether a user or agent) is permitted to perform certain tasks on specific resources under designated conditions, ensuring complete transparency in access control. This comprehensive approach not only enhances security but also improves operational efficiency across various systems.

Singulr is a comprehensive platform designed for enterprise AI governance and security, providing a cohesive control framework that aids organizations in discovering, securing, and optimizing their AI implementations on a large scale. By tackling the widening gap between the rapid deployment of AI technologies and the constraints of governance, it offers unparalleled visibility into all AI systems utilized within the organization, which includes custom applications, integrated AI solutions, public tools, and shadow AI that often evade detection by security teams. It systematically identifies and catalogs AI resources throughout the organization, creating a real-time inventory of agents, models, and services while evaluating their associated risks through thorough contextual assessments of data management, model lineage, vulnerabilities, and compliance requirements. The platform's intelligence layer, Singulr Pulse, processes millions of AI systems, assigns risk ratings, and facilitates automated onboarding processes that significantly shorten approval timelines from weeks to mere hours, all while ensuring robust security measures are in place. This innovative approach not only enhances the efficiency of AI adoption but also empowers organizations to maintain a strong governance framework as they navigate the complexities of AI integration.

Matters.AI stands out as the pioneering AI Security Engineer for Data, specifically designed to autonomously detect, comprehend, and address instances of data misuse before any ticket is generated by the Security Operations Center (SOC). This innovative solution safeguards what truly matters, overseeing sensitive data as it exists or moves across various platforms, functioning similarly to a human security engineer that comprehends context, monitors activities, and protects sensitive information independently across environments such as cloud services, SaaS, endpoints, microservices, and AI pipelines. Built upon advanced technologies like semantic intelligence, nearest neighbor search, data lineage modeling, and predictive behavior analysis, Matters goes beyond mere threat detection; it interprets context, foresees potential risks, and takes proactive measures. Rather than depending on outdated static rules, regex patterns, cumbersome dashboards, and incessant alerts, Matters adeptly reads nuanced data signals, tracks risks in real-time, and operates around the clock. By identifying sensitive data based not solely on appearance but also on its significance, Matters employs techniques like fingerprinting and eBPF to monitor data across cloud environments, SaaS applications, endpoints, and beyond, ensuring comprehensive protection and awareness. In this way, Matters.AI not only enhances data security but also transforms the landscape of risk management in the digital age.

Pillar Security serves as a comprehensive AI security platform designed to safeguard the agentic workforce throughout the entire AI lifecycle, encompassing stages from development to deployment and ongoing runtime protection. By integrating business context during phases of discovery, testing, and protection, it ensures that security intelligence accumulates across various AI applications, including agents, models, prompts, frameworks, tools, MCP servers, skills, coding agents, and both SaaS and cloud environments. The platform enables organizations to identify and manage AI assets effectively, even those that are unapproved or fall under shadow AI, while also evaluating risks related to supply chain and overall security posture. Additionally, it maps out the attack surfaces associated with agentic systems and verifies critical vulnerabilities that need addressing. With its AI Security Posture Management features, Pillar scrutinizes interconnected agents, tools, permissions, data sources, prompts, models, and supply chain elements to reveal high-risk pathways, policy breaches, misconfigurations, and potential threats posed by coding agents, all of which enhance the understanding of the impact when a single component encounters a breach. Ultimately, Pillar Security empowers organizations to maintain a robust security framework while navigating the complexities of AI technology.

Opal Zero serves as a governance platform for AI agents that provides just-in-time access management by cataloging every agent and linking it with a responsible owner, evaluating access requests, and implementing decisions through the existing MCP gateway. This comprehensive solution allows organizations to maintain a unified inventory across various identity providers and AI platforms, including Okta, Entra, Anthropic, OpenAI, Bedrock AgentCore, and Cursor, revealing the permissions each agent holds and their respective ownership. The Risk Center highlights access that may be misaligned with intended use, unassigned, or excessive, directing concerns to the relevant owner while offering immediate corrective measures. Paladin assesses requests against established policies and contextual information, pinpoints the least-privileged access routes, adheres to ownership boundaries, and elucidates the rationale behind each resolution. By analyzing real user behavior, Policy Insights uncovers instances of redundant access and suggests enhancements to access policies, moving beyond sporadic fixes. Furthermore, Gateway Enforcement ensures that approved access decisions are implemented as specific, temporary policies within the existing gateway infrastructure, thereby fostering a more secure and organized environment for managing AI agents.

Harden AIF serves as a security platform specifically designed for AI coding agents, ensuring agent endpoint security by assessing tool calls prior to execution based on the developer's intent, session context, organizational policy, and the potential impact of the action proposed. This platform effectively safeguards against threats such as harmful commands, unauthorized access, accidental data transfers, exposure of sensitive information, misuse of privileges, and other risky actions undertaken by agents. By allowing legitimate operations to proceed without disruption, it can also safely redact sensitive information during supported workflows while preventing actions that deviate from the developer's intent or exceed their authority from executing. Harden AIF is compatible with a variety of widely used coding agents and development tools, including Claude Code, Codex, Cursor, Antigravity CLI, Kiro, Hermes, and OpenClaw, thus offering a uniform security framework throughout the agent ecosystem. This comprehensive approach not only enhances security but also fosters a safer environment for developers working with AI technologies.

AI Usage Tracker is a macOS application designed for those who keep an eye on the activity of AI coding tools and local models while they work. It features a compact interface that can be positioned at the top, bottom, left, or right edge of the screen, presenting important information such as account limits, reset times, and the activity of various agents. Users are able to track their session and weekly usage statistics, receive notifications about resets, and easily switch back to a tracked session when an agent requires further input. This application supports a range of tools including Claude, Codex, Cursor, Gemini, OpenCode, Kimi, Ollama, and LM Studio, with available metrics differing based on the provider and account specifics. Additionally, for compatible local models, it can provide insights into context utilization and generation speeds, and allows the configuration of separate work and personal profiles for select services. To use this application, users must have macOS 15 or newer, and it is compatible with both Apple silicon and Intel-based Macs. Overall, AI Usage Tracker is an essential tool for anyone looking to optimize their interaction with AI coding technologies.