Top 8 Product Security Tools in 2025
Product security tools should offer developer-centric automation, contextual risk prioritization, tool correlation and seamless integrations, and effective scalability to match a growing organization. The best tools that offer these features include Jit, Wiz, and Aikido.
Updated September 8, 2025
Product security has never been more critical than in 2025. The average cost of a data breach for U.S. companies jumped 9% to an all-time high of $10.22 million in 2025, while cybercrime is set to cost businesses up to $10.5 trillion by 2025. As development teams push code faster than ever and threat actors leverage AI to launch increasingly sophisticated attacks, traditional security approaches are failing to keep pace.
Product security tools address this challenge by embedding security throughout the entire product lifecycle from initial design and development through deployment and runtime. Unlike reactive security measures, these tools enable teams to identify vulnerabilities, misconfigurations, and threats before they reach production, significantly reducing both risk exposure and remediation costs. For organizations building software in 2025's threat landscape, investing in the right product security toolchain isn't just best practice but business survival.
8 Best Product Security Tools at a Glance
- Best overall product security tool in 2025: Jit
- Best tool for cloud-first organizations: Wiz
- Best for merged static & dynamic code scanning: Aikido
- Best for runtime application & endpoint protection: CrowdStrike Falcon
- Best tool for heavy open-source dependency usage: Mend
- Best for deep static analysis and compliance auditing: Checkmarx
- Best for strong code integrity and supply chain protection: Cycode
- Best for unified risk view across design, code, and deployment: Apiiro
Seamless integration with existing tools
Inline fixes and real-time feedback
Comprehensive security scanning including SAST, SCA, secrets detection, IaC, & DAST
Seamless integration with CI/CD pipelines and cloud providers
Automated asset discovery with AI-enhanced risk scoring
Cloud workload protection across containers, serverless functions, and VMs
Simple, developer-friendly interface
Seamless integration with popular IDEs and development tools
Centralized management simplifies security oversight across teams
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Key Features of the Best Product Security Tools in 2025
- Developer-centric automation: Seamlessly integrates into IDEs and CI/CD pipelines to provide real-time, actionable security feedback. This reduces friction for developers, accelerates fixes, and ensures security is part of daily workflows without slowing down delivery.
- Contextual risk prioritization: Uses runtime data, asset sensitivity, and exploitability to highlight the most critical vulnerabilities. This focuses remediation efforts on the highest impact risks, improving security posture while minimizing alert fatigue.
- Comprehensive multi-tool correlation: Aggregates and normalizes findings from SAST, DAST, SCA, and secrets detection tools. This holistic view reduces blind spots and provides clear, unified insights for faster, more informed decisions.
- Policy-as-code enforcement: Enables security policies to be embedded directly into CI/CD pipelines, automating compliance checks and preventing insecure configurations from progressing. This shifts security left and standardizes governance.
- AI-assisted remediation: Leverages machine learning to suggest or automate fixes for vulnerabilities. This accelerates remediation, reduces manual effort, and empowers developers to resolve issues confidently and quickly.
- Scalable software supply chain validation: Continuously verifies the integrity of dependencies and container images against known vulnerabilities and malicious code. This protects against supply chain attacks and ensures trusted software delivery.
» Here are our picks for the top container scanning tools
8 Best Product Security Tools in 2025
1
Jit
The all-in-one platform for product security
Developer-centric automation
AI Agents automate vulnerability triage, ticket creation, and remediation workflows directly in developer environments, with seamless integration into GitHub, GitLab, CI/CD pipelines, and popular IDEs. Automated alerting and remediation based on contextual factors like production status and internet exposure.
Contextual risk prioritization
Context Engine prioritizes vulnerabilities based on runtime factors like production deployment, internet exposure, and sensitive data access. Risk scores calculated by summing weights of all relevant Priority Factors, with customizable scoring systems.
Tool correlation
Integrates with tools like Cyera, Wiz, Orca, and Checkmarx to provide unified visibility across your security stack, then correlates data from source code managers, cloud environments, and existing security tools.
Scalability
Cloud-native AI Agents designed to handle scale and complexity, working around the clock to analyze and correlate context across systems. Centralized vulnerability backlog unifies findings across multiple scanners for enterprise-scale deployment.
Brief overview
Jit was created to address the fundamental challenge of fragmented application security across modern development workflows. The platform was built with a developer-first philosophy, recognizing that traditional security tools often create friction and slow down delivery cycles. Jit's main purpose is to provide unified application security coverage from code to cloud to runtime, using AI-powered automation to reduce noise and accelerate remediation without disrupting developer productivity.
Jit's vision centers on making security seamless and continuous throughout the entire software development lifecycle, eliminating the traditional trade-offs between speed and security that many organizations face.
Key features
- AI-powered orchestration engine that prioritizes findings by risk context and automates remediation suggestions
- Full SDLC coverage from pre-commit scanning to post-deployment runtime monitoring
- Comprehensive security scanning including SAST, SCA, secrets detection, IaC, DAST, and runtime telemetry
- Reachability-based prioritization to focus on vulnerabilities that are actually exploitable
- Developer workflow integration with major IDEs (VS Code, IntelliJ), Git platforms (GitHub, GitLab, Bitbucket), and CI/CD systems
- CI-native feedback loops providing inline fixes and real-time security guidance
- Cloud-native architecture with API-driven workflows for enterprise scalability
- Multi-team collaboration and policy enforcement capabilities
- Runtime behavior analysis for continuous post-deployment monitoring
Pros and cons
Seamless integration with existing developer tools and workflows
Inline fixes and real-time feedback accelerate remediation
Developer-first design minimizes learning curve and adoption friction
Single platform eliminates need to juggle multiple security tools
Full feature set might be overwhelming for smaller development teams
Pricing structure may be prohibitive for early-stage companies
2
Wiz
Cloud security for the modern enterprise
Developer-centric automation
Generate 1-click fixes in code with pull requests in version control systems and provide developers cloud and security context in their IDE.
Contextual risk prioritization
Security Graph provides context-driven insights into critical exposure, using reachability analysis, runtime context, and asset criticality. AI Issues correlate multiple risk factors including misconfigurations, external exposure, sensitive data, and identities.
Tool correlation
Unified platform aggregates findings from SAST, SCA, IaC, DAST scanners and correlates with cloud environment context. Also integrates with Event Threat Detection and Security Command Center to add correlation and context to security events.
Scalability
Agentless cloud-native architecture connects to every cloud environment and scans every layer with comprehensive approach; API connectors also enable scanning and inventory of entire cloud environment within minutes for enterprise deployment.
Brief overview
Wiz was created to solve the growing complexity of securing cloud-native applications and infrastructure at scale. Founded by former Microsoft Azure security leaders, the company recognized that traditional security tools weren't designed for the dynamic, distributed nature of cloud environments. Wiz's main purpose is to provide comprehensive cloud workload protection and security posture management, offering unified visibility across multi-cloud environments from code repositories to running workloads.
The platform was built specifically for cloud-first organizations that need to secure containerized applications, serverless functions, and virtual machines while maintaining the speed and agility that cloud adoption promises.
Key features
- Cloud workload protection across containers, serverless functions, and VMs
- Cloud Security Posture Management (CSPM) for continuous configuration monitoring
- Automated asset discovery with AI-enhanced risk scoring
- SCA and IaC scanning at repository level before deployment
- Runtime vulnerability correlation linking code-level issues to cloud deployments
- Multi-cloud support for AWS, Azure, and GCP environments
- GitHub App auto-scanning for seamless repository integration
- CI/CD pipeline integration for infrastructure deployment security checks
- Comprehensive cloud risk visibility with configuration issue detection
- Proactive threat prioritization to reduce alert fatigue
Pros and cons
Seamless integration with CI/CD pipelines and cloud providers
AI-enhanced risk scoring reduces alert fatigue and false positives
Scalable architecture grows with enterprise cloud adoption
Limited on-premises support
Advanced features may be complex for smaller development teams
Dependency on cloud provider APIs for full functionality
3
Aikido
Simplified security for modern development teams
Developer-centric automation
AI AutoFix generates pull requests to fix SAST, IaC, dependency, and container issues automatically, or switch to hardened base images.
Contextual risk prioritization
Auto-ignore capability and reachability analysis help prioritize issues that need to be addressed quickly while reducing false positives; intelligent risk analytics also prioritize high-impact issues, cutting alert fatigue.
Tool correlation
Consolidates multiple security tools in one platform, filtering out false positives and reducing noise through contextualizing vulnerabilities. Limited advanced correlation compared to enterprise-focused platforms.
Scalability
Highly scalable solution that aggregates multiple controls in one place; the platform fee structure with included users makes it more suitable for mid-market focus.
Brief overview
Aikido was created to simplify application security for development teams overwhelmed by complex, fragmented security tools. The company recognized that many security solutions create more noise than value, leading to alert fatigue and poor adoption among developers. Aikido's main purpose is to provide comprehensive static and dynamic analysis with intelligent filtering, focusing on continuous security testing that integrates seamlessly into existing development workflows.
The platform was designed with the philosophy that security should be simple, effective, and developer-friendly, eliminating the traditional complexity that often makes security tools difficult to adopt and maintain.
Key features
- Combined SAST/DAST coverage for comprehensive vulnerability detection
- Infrastructure as Code (IaC) analysis for early configuration issue detection
- AI-powered detection for subtle security issues and improved accuracy
- Automated scanning triggers integrated into CI/CD pipelines
- Continuous security testing focused on pre-deployment phases
- Deep code quality assessments alongside vulnerability scanning
- Software Composition Analysis (SCA) for dependency risk management
- Centralized dashboard for unified security visibility across projects
- IDE and Git repository integration for seamless developer adoption
- Policy enforcement to prevent vulnerable code from reaching production
Pros and cons
Simple, developer-friendly interface reduces adoption friction
Seamless integration with popular IDEs and development tools
Centralized management simplifies security oversight across teams
Smaller ecosystem of integrations than established competitors
Limited customization options for complex enterprise workflows
4
CrowdStrike Falcon
AI-powered cybersecurity for endpoint and runtime protection
Developer-centric automation
Enables automated vulnerability remediation workflows with ServiceNow and Jira integrations, reducing remediation time through ticketing automation; 20+ built-in quick actions accelerate SecOps workflows to resolve misconfigurations without code.
Contextual risk prioritization
AI-powered risk prioritization combines predictive exploitability, business-aware asset context, and attacker behavior modeling. Prioritizes vulnerabilities before they are exploited-in-the-wild using comprehensive threat intelligence.
Tool correlation
Unified platform consolidates point products to eliminate complexity, with Signal AI intelligently grouping related events and alerts into actionable insights.
Scalability
Single-agent, cloud-native platform designed for enterprise deployment with unified console management across security and IT. AI-powered exposure management built on pioneering adversary intelligence for enterprise-scale attack surface visibility.
Brief overview
CrowdStrike Falcon was created by security experts who recognized that traditional signature-based security solutions were inadequate against sophisticated, evolving cyber threats. Founded with the mission to stop breaches through next-generation endpoint protection, CrowdStrike built Falcon as a cloud-native platform that leverages AI and behavioral analysis to detect and respond to threats in real time. The platform's main purpose is to provide comprehensive endpoint detection and response (EDR) and runtime application protection, focusing primarily on post-deployment security monitoring.
CrowdStrike pioneered the concept of cloud-delivered endpoint protection, moving away from legacy on-premises solutions to provide real-time threat intelligence and automated response capabilities at enterprise scale.
Key features
- Endpoint Detection and Response (EDR) with behavioral monitoring
- AI-powered threat detection for sophisticated attack identification
- Runtime application protection for post-deployment security
- Automated response capabilities to rapidly contain and remediate threats
- Lightweight agent architecture with minimal performance impact
- AI risk scoring for intelligent threat prioritization
- Cloud and on-premises environment monitoring for hybrid infrastructure
- Real-time threat intelligence from global security operations
- SIEM and orchestration tool integration for security workflow automation
- API-based automation for enterprise-wide scalability
Pros and cons
AI-powered detection excels at identifying sophisticated, unknown threats
Seamless integration with existing security infrastructure
Enterprise-grade scalability with API-based automation
Primarily focused on runtime/post-deployment
Focus on endpoint protection may not address all application security needs
5
Mend
Open source security and compliance automation
Developer-centric automation
AI-powered fixes delivered directly in repositories with automated dependency updates through Mend Renovate; automated pull requests for version updates and vulnerability remediation integrated into developer workflows.
Contextual risk prioritization
Priority scoring between 0-100 based on CVSS score, business impact, fix availability, and Effective Usage Analysis technology. Market-leading reachability engine identifies when vulnerabilities are exploitable and specifies whether they're reachable.
Tool correlation
Platform-native consolidation eliminates data silos and inconsistencies to achieve contextual risk-based prioritization across AppSec tools. Full security visibility across code, open source, containers, and AI through one scalable platform.
Scalability
Unified data lake and data structures with platform-level labeling for deeper segment insights and optimized workflow across enterprise application portfolios.
Brief overview
Mend (formerly WhiteSource) was created to address the growing challenge of securing open source dependencies in modern software development. As organizations increasingly relied on open source components—with some applications containing 80% or more open source code—the founders recognized the need for comprehensive software composition analysis that goes beyond basic vulnerability scanning. Mend's main purpose is to provide deep software composition analysis (SCA) with automated license management and vulnerability detection, focusing on the early- to mid-SDLC stages where dependency decisions have the greatest impact.
The platform was built to help organizations embrace open source innovation while maintaining security and compliance, automating the complex task of tracking and managing thousands of open source components across enterprise portfolios.
Key features
- Deep Software Composition Analysis (SCA) for comprehensive dependency scanning
- Open source license management with automated compliance checking
- Continuous vulnerability detection across all open source components
- CVE and license tracing with detailed impact analysis
- Auto-remediation bots for automated dependency updates and fixes
- Priority scoring to focus remediation efforts on critical vulnerabilities
- CI/CD pipeline integration for continuous dependency monitoring
- Policy enforcement across enterprise projects and teams
- Automated vulnerability intelligence with real-time threat updates
- SCM platform integration with major development tools
Pros and cons
Comprehensive open source license management
Priority scoring helps developers focus on critical vulnerabilities first
Seamless CI/CD integration fits naturally into existing development workflows
Limited coverage of custom code security
Limited application security testing beyond open source components
6
Checkmarx
Enterprise-grade static application security testing
Developer-centric automation
Automatically creates bug tickets for vulnerabilities with detailed remediation guidance and leverages GenAI capabilities for faster remediation. Seamlessly integrates into developer ecosystem and pipelines to make fixing vulnerabilities faster and easier
Contextual risk prioritization
Checkmarx Fusion prioritizes vulnerabilities based on real impact and risk, correlating insights across pre-deployment to runtime. Prioritizes vulnerabilities based on factors such as severity, exploitability, and application criticality with minimal false positives.
Tool correlation
Context-aware correlation engine leverages holistic view of application security scan results across all stages of software lifecycle. Orchestrates AST tools, correlates Checkmarx and 3rd-party data, then ranks and prioritizes results.
Scalability
Enterprise-grade solution designed for large-scale application portfolios, unified cloud-native platform integrates and automates multiple AppSec capabilities within SDLC to simplify management and reduce TCO.
Brief overview
Checkmarx was founded to address the critical need for comprehensive static application security testing in enterprise environments. The company recognized that as applications grew more complex and organizations scaled their development teams, traditional security approaches couldn't keep pace with modern development velocities. Checkmarx's main purpose is to provide enterprise-grade SAST with extensive language and framework support, focusing on early SDLC phases to detect vulnerabilities before they reach production.
The platform was built specifically for large enterprises that require deep static analysis capabilities, comprehensive compliance auditing, and the ability to manage security across multiple development teams and complex application portfolios.
Key features
- Comprehensive SAST with extensive programming language and framework support
- Data flow analysis for deep vulnerability detection and root cause identification
- AI-powered false positive reduction to improve scan accuracy and developer experience
- Integrated remediation guidance with actionable fix recommendations
- IDE and source control integration for seamless developer workflow adoption
- CI/CD pipeline orchestration with automated scan triggering and policy enforcement
- Policy-as-code enforcement for consistent security standards across teams
- Multi-team workflow management designed for complex enterprise environments
- Compliance auditing capabilities for regulatory and industry standard adherence
- Scalable enterprise architecture supporting large application portfolios
Pros and cons
Tight IDE integration enables early vulnerability detection during coding
Comprehensive compliance auditing supports regulatory requirements
Scalable architecture designed for large, multi-team enterprise environments
Complex setup and configuration may require dedicated security expertise
Enterprise-focused pricing may be discourage smaller organizations
7
Cycode
Software supply chain security and code integrity protection
Developer-centric automation
AI-powered Auto Fix and Remediation enables developers to resolve vulnerabilities in record time with precise, context-driven fixes and no-code automation workflows triggered in real-time thanks to code visibility and integration with developer workflows.
Contextual risk prioritization
Advanced Risk Score leverages contextual factors including business impact, runtime intelligence, and code usage to focus on meaningful risks. Intelligent risk scoring engine based on CVSS, CISA KEV, EPSS, and key impact factors.
Tool correlation
ASOC solution automatically discovers tooling across SDLC, analyzes and correlates data from different modules, and deduplicates vulnerabilities.
Scalability
AI-native platform combining proprietary scanning with AI-powered prioritization designed for enterprise scale with role-based access controls. Complete ASPM platform replaces existing AST tools or integrates with them while providing visibility, prioritization, and remediation at scale
Brief overview
Cycode was founded to address the emerging threats targeting software supply chains and source code integrity. As high-profile supply chain attacks like SolarWinds and CodeCov demonstrated the devastating impact of compromised development environments, Cycode's founders recognized the critical need for comprehensive protection of the software development process itself. The platform's main purpose is to provide source code integrity monitoring, secrets detection, and supply chain security, focusing on early SDLC phases to prevent unauthorized changes, exposed secrets, and policy violations before they reach production.
Cycode was built specifically for organizations that understand that securing the development pipeline is as critical as securing the applications it produces, providing visibility and control over the entire software factory.
Key features
- Source code integrity monitoring with unauthorized change detection
- Comprehensive secrets detection across repositories and development environments
- Supply chain security protection against malicious code injection and tampering
- Policy enforcement automation with real-time violation detection
- Repository activity monitoring for continuous oversight of code changes
- Drift alerts for detecting configuration and code deviations
- Git platform integration with major source control systems
- CI/CD pipeline monitoring for build and deployment security
- Chat tool integration for immediate alerting and incident response
- Enterprise-grade access controls for multi-repository environments
Pros and cons
Automated policy enforcement reduces manual oversight and human error
Seamless Git platform integration fits naturally into existing workflows
Enterprise-grade access controls enable fine-grained security management
Focus on early SDLC phases may miss runtime security issues
Pricing structure may be significant for organizations with extensive codebases
8
Apiiro
Code-to-runtime application security posture management
Developer-centric automation
Risk-based policy engine and automated workflows enable embedding guardrails into PRs and builds with seamless remediation triggering; brings actionable context and prioritized risks to developers to empower secure application development without slowdown.
Contextual risk prioritization
Risk Graph layers findings on application inventory using code and runtime context to surface likelihood and impact factors; multidimensional prioritization uses contextual likelihood and impact factors to cut through backlogs and focus on business-critical risks.
Tool correlation
Integrates and enriches security findings from any security tools including SAST, SCA, CSPM, and runtime API security.
Scalability
Open platform integrates with application and cloud security tools while providing native solutions for enterprise-scale unified risk visibility
Brief overview
Apiiro was founded to solve the challenge of managing application risk across increasingly complex, interconnected software environments. The company recognized that traditional security tools provided fragmented visibility, making it difficult for organizations to understand how risks in code translate to real-world exposure in production. Apiiro's main purpose is to deliver comprehensive risk and compliance management with a focus on Infrastructure as Code (IaC) and application configuration throughout the SDLC, providing continuous policy enforcement and contextual risk scoring from design through deployment.
The platform was built specifically for enterprise-scale organizations that need unified visibility and control across their entire application attack surface, connecting the dots between code-level risks and runtime exposure.
Key features
- Code-to-runtime risk graph connecting vulnerabilities to their real-world impact
- Infrastructure as Code (IaC) analysis for Terraform, CloudFormation, and Kubernetes manifests
- Contextual risk prioritization based on actual exposure and business impact
- Policy-as-code enforcement with automated compliance checking
- Secrets validation with runtime context for comprehensive credential security
- LLM-guided remediation providing intelligent fix recommendations
- Continuous policy enforcement across the entire SDLC
- Application configuration management throughout deployment pipeline
- Enterprise governance and audit capabilities for regulatory compliance
- CI/CD pipeline integration with major orchestration platforms
Pros and cons
LLM-guided remediation accelerates fixes with intelligent recommendations
Unified risk view eliminates blind spots between development and operations
Enterprise governance capabilities satisfy audit and compliance requirements
Enterprise focus may be overwhelming for smaller development teams
Integration complexity may require dedicated resources for initial setup
How Product Security Tools Address Modern Development Challenges
In 2025, product security tools are designed to address fragmented visibility across cloud-native stacks and development pipelines. They solve challenges such as disconnected security signals from infrastructure, code, and runtime; lack of actionable context for developers; and misaligned ownership between AppSec and cloud teams.
These tools unify security findings from SAST, SCA, IaC, CSPM, and runtime sources, correlating them with code ownership and cloud environments. This helps bridge the gap between application security and cloud security by offering full-stack context, enforcing policies earlier in the SDLC, and enabling automated, developer-friendly remediation.
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The Product Security Tool Workflow: From Code to Runtime
The typical workflow of a product security tool incorporates the following aspects:
- Initial code commit: The product security tool scans source code for vulnerabilities using SAST and secrets detection as developers push changes. It provides immediate feedback via IDE plugins or pre-commit hooks, enabling early fixes before code enters the main repository.
- CI/CD integration: The tool integrates into CI/CD pipelines to automate comprehensive scans (SAST, SCA, DAST) on pull requests and builds, enforcing security gates. It prioritizes findings based on risk context and blocks deployments if critical issues remain unresolved.
- Post-deployment monitoring: After deployment, the tool continuously monitors runtime behavior and external threat intelligence feeds. It detects anomalies, exploits, or configuration drifts, alerting teams to emerging risks and facilitating rapid incident response.
Choosing the Right Product Security Tool for Your Organization
Selecting the right product security tool depends on your organization's specific needs, development maturity, and existing infrastructure. Consider factors like your team size, cloud environment complexity, current toolchain, and whether you need comprehensive platform consolidation or targeted point solutions.
For teams seeking developer-first automation with AI-powered risk prioritization, enterprise-scale tools like Jit, Wiz, and Cycode offer robust ASPM capabilities. Smaller teams might find Aikido's simplified approach more suitable, while organizations with heavy compliance requirements may benefit from Checkmarx's governance features or CrowdStrike's threat intelligence integration.
The key is finding a solution that balances comprehensive coverage with developer productivity; reducing noise while providing actionable insights that fit naturally into existing workflows.
» Ready to see how contextual risk prioritization and AI-driven automation can transform your product security program? Book a demo with Jit
