Best Secure Code Review Software - Page 4

Almanax

The AI Security Engineer LLM-based detection, triaging, and patching of vulnerabilities without the noise. Catch 5x more bugs. Cut 90% of the noise.

Axivion

Axivion Static Code Analysis helps developers check standard compliance, security vulnerabilities, and code quality issues for C and C++ code. It performs automated analysis to identify violations of coding guidelines like MISRA C and detect clones, dead code, and security vulnerabilities. Key features include coding standards compliance checking, metric monitoring, defect analysis, and certification for safety-critical software development.

Bearer

Bearer helps modern teams ship trustworthy products with the help of our code security SAST solution built for security, privacy and engineering teams. We combine sensitive data context with static code analysis to make security and privacy engineering simpler and smarter to maximize the ROI for your DevSecOps and central security team driven programs.

Average Rating: 5.0/5.0

Total Reviews: 1

Black Duck Signal

Black Duck Signal™ is an agentic AI AppSec solution powered by ContextAI™, with 20+ years of human-curated intel, to help you quickly find and fix issues without noise or AI hallucinations.

CodeAnt AI Code Security Platform

CodeAnt AI covers code, cloud, and runtime security in one platform. Code security: AI SAST detects vulnerabilities during development and establishes which are reachable before surfacing them, with 95% fewer false positives than pattern-matching scanners and findings mapped to OWASP and CWE. Software composition analysis identifies vulnerable and malicious packages across direct and transitive dependencies, protecting more than 2 billion monthly package downloads. Secret detection scans full commit history for hardcoded credentials, API keys, and tokens. SBOM generation runs continuously across every repository. Cloud security: Cloud security posture management detects misconfigurations across your cloud accounts and maps them to compliance frameworks. Threat detection surfaces active adversary behavior in the cloud environment. Container scanning inspects images and registries for vulnerable packages and embedded secrets. Virtual machine scanning covers running workloads and their installed dependencies. Runtime security: Dynamic application security testing probes running applications for exploitable behavior. Attack surface management continuously discovers exposed assets, domains, and services outside the perimeter. Grey box AI pentesting runs more than 500 AI agents against that surface, chaining weaknesses into complete attack paths. Remediation arrives as a fix inside the pull request. Continuous AI learning draws on more than 1 billion lines of codebase history. Our security research team has discovered over 150 CVEs in production software, and CodeAnt has pentested more than 1,000 companies.

CodeCanary

CodeCanary is an AI product engineer that continuously improves your product based on product analytics. CodeCanary connects to your Github repo(s), your product analytics database, and your Slack channels. Automatically every morning it runs and suggests improvements based on real user behavior that increase KPIs and decrease negative experiences with your product. https://www.codecanary.ai/

CodeCritic

Codegrip

Codegrip is an automated code review SaaS platform that helps developers to save time in code reviews and to tackle technical debt efficiently.

depthfirst

depthfirst is an AI-native security platform offering continuous cyber defense. It reasons through code, infrastructure, and business logic to understand how systems work and build a threat model. That context helps depthfirst find and verify vulnerabilities, prioritize what is exploitable, block malicious dependencies, and help teams remediate security issues. The platform covers three broad areas: Code Security reviews repositories and pull requests for vulnerabilities, secrets, insecure dependencies, and business-logic flaws. It connects findings to application context so security and engineering teams can focus on the issues that matter and fix them in the code. Agentic Pentesting uses autonomous agents to attack running applications like a team of elite security researchers. It supports black-, gray-, and white-box testing for new vulnerability discovery, but can also confirm whether code scan findings are exploitable and replay attacks to verify that fixes work. Dependency Firewall blocks malicious packages before installation to prevent supply chain attacks. It applies a shared security policy at the artifact-repository layer and on managed devices, protecting both people and AI agents. depthfirst routes each task to the best-suited AI model to optimize performance and cost. It also includes dfs-large1, depthfirst’s own frontier cybersecurity model, which performs comparably to frontier general-purpose models on vulnerability detection tasks at a fraction of the cost. depthfirst works with enterprises such as ServiceNow, government agencies, and innovative AI and fintech companies including Lovable, Supabase, Ripple, Listen Labs, fal, and MoonPay.

esChecker MAST (SAST, DAST & IAST)

esChecker combines many years of penetration testing experience with a unique dynamic engine simulating attack techniques, such as reverse-engineering or code tampering. No source code is needed, only the app binary (Android apk or iOS ipa). esChecker provides immediate feedback about the way your app reacts against many hacking techniques. You can now spare your pentest budget for in-depth vulnerability analyses.

Average Rating: 4.3/5.0

Total Reviews: 2

Gitar

Gitar is Sonar’s AI code verification solution for pull requests and CI workflows. It reviews code changes with awareness of repository context, team conventions, and the intent behind a change; diagnoses CI failures; and generates verified fixes that it can commit directly to the branch. Gitar does not stop at flagging: it iterates until CI passes, resolving functional bugs, logic errors, behavioral issues, and build failures before merge, and delivering a green, ready-to-merge pull request. Merge blocking, auto-approve, and auto-merge run under rules you define, inside your existing review controls. Gitar complements SonarQube’s deterministic, full-codebase analysis with an agentic, PR-scoped review layer. Together, they provide multilayered verification: SonarQube sets the standard; Gitar enforces it at merge speed.

Hikaflow

Hikaflow is a deeply integrated, AI-powered engineering assistant that automates code reviews, detects security issues, maps regressions, and accelerates onboarding—without forcing any changes to your workflow. It connects to your GitHub or Bitbucket repositories, scans your codebase in real-time, and delivers expert-level insights, documentation, and test cases—all with full project context. Whether you're managing internal teams or external contractors, Hikaflow becomes your embedded senior engineer, QA tester, and onboarding coach.

Hyrax AI

Hyrax is a GitHub-native code review and remediation platform for software engineering teams. It reviews code, finds problems, writes the fix, and submits a pull request for the team to merge. Background: AI coding tools have increased how much code teams produce, but review and remediation have not kept pace, so issues accumulate faster than engineers can address them. Hyrax handles the work between finding an issue and merging a fix. How it works: a team installs the Hyrax GitHub App on a repository. Hyrax runs a discovery pass that maps the codebase, its conventions, and its architecture, then stores that context in a .hyrax directory. From there it operates through four workflows: Scan: audits the whole repository for issues across six domains (security, correctness, maintainability, performance, architecture, and operations) before a pull request exists. Fix: writes a change using the repository's own conventions, runs the project's tests, reviews the diff, and submits a pull request. The linked ticket closes when the pull request merges. Improve: reviews incoming pull requests and re-checks existing findings against the latest commits. Govern: writes repository context back so other AI coding tools work from the same rules. Safety and control: Hyrax does not merge changes on its own. Every change runs through a 13-step verification process, and if a change cannot pass the project's tests, no pull request is created. All changes stay reviewable and reversible, and the engineering team approves every merge. Scope: Hyrax reviews all of a team's code, every commit and every pull request, not only AI-written code. It supports 18 programming languages and integrates with GitHub for source control and Linear for issue tracking. Plans and deployment: a free plan covers one repository with a monthly audit and a capped number of fixes. Paid plans add the full audit pipeline, pull request reviews, and shared usage credits billed by usage rather than per seat. Inference runs on AWS Bedrock, and Hyrax does not use customer code to train models.

IRIS

CodeEye's IRIS is a next-generation application security posture management (ASPM) platform, offers an all-in-one solution with real-time, AI-powered vulnerability and threat detection, correlation, prioritization, and remediation, easing the tension between time-to-market and risk mitigation. How it Works? Unlike traditional ASPM Solutions, IRIS detects vulnerabilities within the product development lifecycle and application infrastructure, while simultaneously providing continuous penetration testing and attack surface management to production environments. IRIS detects, correlates, provides risk-based analysis, and prioritizes application security findings in real time with automated workflows for remediation – all within one platform. IRIS seamlessly integrates with your tools, pipelines, and workflows, and supports your favourite languages. Unlock the Benefits: 1) Centralize detection, prioritization, and remediation of application threats and vulnerabilities. 2) Real-time actionable insights. 3) Establish resilient DevSecOps processes based on risk management. 4) Implement automated workflows to accelerate the identification and resolution of application risks. 5) Adopt a straightforward licensing model. 6) Ability to measure the effectiveness of your application security program. 7) Deploy within 24 hours with simplicity and ease of operation. 8) Built-in policy compliance measures. Next-Gen ASPM Managed Service In today's digital landscape, organizations grapple with deciphering and prioritizing the criticality of code and application related threats and vulnerabilities. The scarcity and expense of specialized talent capable of bridging the gap between DevOps and SecOps exacerbates this challenge. CodeEye's expertise in Application Security provides a Continuous AppSec Partner, accelerating program maturity with expert guidance and advanced technology. Our IRIS Managed Service centralizes application risk management, helping you define compliance measures and policies for prioritization and remediation, ensuring you grasp and address program risk in real-time. Key Features - Static Application Security Testing (SAST): Scans your source code for security risks before an issue goes to production. - Software Composition Analysis (SCA): Continuously monitors your code for known vulnerabilities and other security risks. - Container Scanning: Scans your container in real time for packages that contain security threats and vulnerabilities. - Dynamic Application Security Testing (DAST): Dynamically tests your production applications for vulnerabilities through simulated attacks. - Attack Surface Management (ASM): Continuously identifies, monitors, and manages external internet-connected assets for potential attack vectors and exposures. - Risk and Compliance: Continuously evaluates regulatory and internal security policy compliance using real-time and historical reporting. Vendor of Record Award CodeEye's IRIS is recognized as a Vendor of Record by the Ministry of Government and Consumer Services for IT Security Products In 2024, NIST updated its Cyber Security Framework (CSF) with significant implications for security by design and secure SDLC. Our Risk and Compliance module supports compliance with NIST CSF 2.0 throughout the software development lifecycle. Gain a comprehensive view of various scanning modules aligned with the CSF's five core functions: Identify, Protect, Detect, Respond, and Recover. Our Difference: An all-in-one platform with straight forward licensing and seamless integration. Your Results: A tool that works with your existing tools and workflows, providing security without hidden costs or complexities. Our Difference: Continuous penetration testing and attack surface management. Your Results: Identify and close gaps before an attacker exploits them across your ever-changing attack surface. Our Difference: Quick and Easy Deployment Your Results: Security monitoring and testing within 24 hours, without extensive setup or training. Our difference: Built-in risk and compliance policy module Your Results: Ensure regulatory and internal compliance with built-in policy measures aligned with industry standards like NIST CSF 2.0. Our Difference: Automated Workflows for remediation. Your Results: Rapid risk mitigation, reducing the time, effort and cost of finding and fixing vulnerabilities to ensure continuous protection. Our Difference: Real-Time, AI-powered vulnerability Your Results: Immediately identify and address security threats with precise, actionable intelligence. Our Difference: Threat and vulnerability detection, correlation, and risk-based analysis. Your Results: Simplified security operations where critical vulnerabilities are addressed first.

Norma

Quality Clouds is an AI Code Governance platform that makes AI-generated code production-ready. As enterprises adopt AI coding assistants and agentic platforms — from ServiceNow Now Assist and Salesforce Agentforce to tools like Cursor, Lovable, Replit, and Claude Code — Quality Clouds scans what they produce before it reaches production, catching configuration drift, security risks, technical debt, and compliance violations across dev, test, and UAT environments. The platform provides a single governance layer that works across multiple enterprise platforms. Rather than relying on post-deployment monitoring, Quality Clouds operates upstream — analysing AI-generated code, configurations, and agent logic in pre-production to ensure they meet organisational standards before go-live. LivecheckAI, the platform's core engine, continuously evaluates code against hundreds of best-practice rules and provides guided remediation so teams can fix issues before they become incidents. Quality Clouds is purpose-built for enterprises in regulated industries — financial services, energy, healthcare, retail, and the public sector — where the speed of AI-generated code must be matched by rigorous governance. The platform is used by global organisations including Barclays, Shell, Nestlé, BP, and Sainsbury's to govern their most critical business platforms at scale.