12 Best SAST Tools for Code Security

Finding security vulnerabilities in your code as early as possible is crucial, and Static Application Security Testing (SAST) is a key practice for that. Choosing between the many available options can be challenging, but understanding what makes the best SAST tools stand out will help you protect your applications efficiently. In this guide, the idea is to show what SAST is, why it matters, and how to choose the right solution for your team.

Understanding Static Analysis

Static analysis is basically the process of looking at your code, whether source code, bytecode, or binary, without having to run the application. The idea is to identify vulnerabilities, bugs, or code patterns that could cause problems later, just by analyzing the structure and logical flow of the code.

It is like an automated code review, but with a full focus on security and technical quality. The tool goes through everything, line by line, trying to predict where the code might break or open a security gap.

How does this work in practice?

Usually, a SAST tool follows a flow more or less like this:

Reads and interprets the code:

First, it parses the code and transforms it into something it can understand better, such as an Abstract Syntax Tree (AST). This is kind of like a map that shows how each piece of the code connects.

Applies a lot of rules on top:

Then it starts checking the code against a set of known rules. This can range from simple things like:

“Is this code using a function that has a history of being insecure?”

To more specific things like:

“Is there any hardcoded password here?”

Analyzes how data moves through the code (Data Flow):

More advanced tools track how information enters, moves through, and exits the application. For example:

“Is this user input going straight to a database without any validation?”

“Is there any variable receiving external data and then being used in an HTTP response without sanitization?”

What kind of problem can Static Analysis catch?

• SQL Injection
• Cross-Site Scripting (XSS)
• Hardcoded secrets (passwords or tokens in the code)
• Path Traversal
• Buffer Overflow (in languages like C/C++)
• Operating system command injection

All of this without having to run the code. The focus is to catch problems directly in the source text analysis, before running any test or build.

And what does SAST not catch?

It will not find problems that only show up when the system is running, such as environment configuration errors or failures that depend on external integrations. That is why SAST is usually only one part of an application security strategy. Ideally, it should be combined with other practices, such as DAST or even manual security testing, depending on the team’s maturity level.

Benefits of using SAST

Now that you know how SAST works under the hood, let’s talk about where it really makes a difference in the team’s day-to-day work: identifying problems as early as possible in the development cycle.

Integrating SAST into the earliest stages of development, the well-known shifting left, is one of the most efficient ways to prevent vulnerabilities from escaping into production. The earlier the problem appears to the dev, the faster and cheaper it is to fix.

When the tool runs directly in the IDE or in the commit process, feedback arrives almost in real time. The code is still fresh in the developer’s head, the context is recent, and the fix becomes just another natural step in development, like fixing a lint error. This avoids that classic scenario of discovering a problem only in the QA phase, or worse, after a production incident.

Besides avoiding rework, applying SAST early has another positive effect: it educates the team day by day. Every time a dev receives a suggestion or a vulnerability alert, they learn in practice what to avoid in the next code they write.

Over time, this creates a stronger security culture inside the team. The number of new vulnerabilities tends to drop sprint after sprint, because the team starts internalizing good practices.

Another important point is avoiding the accumulation of security technical debt. If the team only discovers vulnerabilities after the code is already consolidated and deployed, the cost of fixing them goes way up. Many times, the fix becomes a large and risky refactor.

By integrating SAST from the beginning, the team gets:

• Faster fixes
• Less rework
• Less technical debt
• Faster delivery without compromising security
• Developers who are more aware of code security

List of the Top SAST Tools in 2026

There are many tools on the market, each with its own strengths and weaknesses. Here is an overview of the best-known ones:

1. Kodus

Kodus is not the most “traditional” option on this list if your definition of SAST is only a classic static engine. It makes more sense when the question is different: how do you reduce code risk inside the real development flow, before the problem reaches production?

Kodus’s proposal is to operate in that PR layer, where many security, architecture, and quality decisions can still be fixed at a low cost. Instead of depending only on fixed checks or generic comments about the diff, the platform combines repository context, AST-based structural analysis, reading dependencies between modules, semantic analysis with LLMs, and custom team rules.

This changes the practical usefulness of the tool. The problem with SAST is almost never just finding issues. It is finding useful issues, with enough context for the team to understand, trust, and fix them. Kodus tries to solve this by looking at the change within the context of the codebase, the internal standards, and the rules the team wants to reinforce.

In practice, it works as a prevention layer in review. Kody reviews changes in the PR, can run in automated flows and also via CLI, groups findings by severity, suggests fixes, and reduces noise based on the team’s context. For companies that want to bring security closer to the daily engineering flow, this makes analysis more actionable than a separate scanner dumping alerts into the backlog.

Pros

Kodus’s main differentiator is context. Kody, the platform’s code review agent, can work with an understanding of the repository, the team’s standards, and the rules the team wants to apply. This reduces that kind of automated comment that looks correct but does not help anyone decide what to do.

Another important point is rule flexibility. The team can create Kody Rules in natural language, scoped by repository, directory, language, file type, glob, severity, and category. This makes it possible to turn internal standards into real review criteria, including input validation, unsafe API usage, error handling, authentication, boundaries between layers, exposure of public contracts, and rules tied to product logic.

Kodus can also sync rule files that already exist in the repository, including files used by tools like Cursor, Copilot, Claude Code, and Aider. This helps reuse standards the team already maintains and turn that knowledge into enforcement inside review, without starting everything from scratch.

Another relevant point is learning from the team’s history. The platform can suggest new rules based on months of review history, using real patterns from the codebase as the basis for new guardrails. This helps the analysis become less generic over time.

The model and cost side also matters. Kodus is open source, model-agnostic, supports BYOK, and does not add markup on LLM usage. The team chooses the provider, connects its own key, and pays usage directly to the vendor. For companies that want control over cost, privacy, and lock-in, this makes a difference.

Finally, the plugin and MCP layer helps bring external context into review. This can include documentation, business rules, tickets, product decisions, or other sources that help Kody evaluate the change beyond the changed code.

Cons

Kodus is not the best choice if the company is looking only for a classic SAST tool, with broad AppSec coverage inside a traditional single-vendor package.

It also makes more sense for teams that want to bring rules, context, and internal standards into review. If the expectation is only to turn on a generic scanner and handle all alerts outside the PR flow, other tools may fit better.

Pricing

The Community plan is free. The Teams plan costs $10 per developer per month, with BYOK. Enterprise is custom pricing.

2. SonarQube

SonarQube Cloud and SonarQube Community Build keep showing up in almost every conversation about code quality and security. This happens because Sonar has been part of many teams’ day-to-day work for a long time and solves a very concrete problem: giving continuous feedback on quality, bugs, vulnerabilities, and coverage without requiring a separate AppSec process.

It is not the most specialized SAST on the list, and it does not try to be a platform focused only on application security. Its value is more in the combination of code analysis, quality gates, coverage, merge rules, and integration with the development flow.

For companies that want to combine quality and security in the same governance layer, Sonar still makes a lot of sense. It helps create minimum criteria for code to enter the codebase, especially in teams that need to standardize practices across several repositories.

In recent cycles, the platform has also started talking more to the AI context, with features like AI Code Assurance and AI CodeFix. This puts Sonar in a slightly more current position, especially for teams concerned about the quality of code generated or changed with AI support.

Pros

Sonar’s main value is in the combination of continuous analysis and simple governance to maintain. Quality gates, PR feedback, IDE integration, and support for several languages help put quality and security inside the team’s normal flow.

Another important point is that it serves teams at very different stages. Community Build works as an entry point for those who want to run self-managed at no cost. SonarQube Cloud simplifies adoption for those who prefer not to operate the infrastructure. And the larger editions cover scenarios with stronger governance requirements.

For companies that do not want to treat quality and security as two completely separate purchases, Sonar remains a practical option. It does not cover everything a more complete AppSec stack covers, but it helps a lot in creating a minimum quality standard per project.

Cons

The main caution is AppSec depth. Sonar covers vulnerabilities and security hotspots, but it is not necessarily the most suitable choice when the priority is application security at a more specialized level, such as tools focused on SAST, advanced policies, or more customized analysis.

It is also worth understanding the LOC-based model well, especially in SonarQube Cloud. In organizations with many private projects, large monorepos, or older codebases, this point can show up early in the bill.

Another caution is not expecting Sonar to work as a contextual PR reviewer. It is very good at applying rules, quality gates, and analysis standards, but it does not have the same proposal of understanding repository history, specific product rules, or the team’s architectural decisions.

Pricing

On SonarQube Cloud, the Free plan covers up to 50k private LOC and 5 members. The Team plan starts at $32 per month. The Enterprise plan is custom pricing. SonarQube Community Build self-managed is free.

3. Snyk Code

Snyk Code, which many people still know as Snyk DeepCode, is part of Snyk’s platform. The proposal is to bring security closer to the developer, covering the flow from IDE to CI without leaving everything to a separate stage at the end of the cycle.

It makes sense for teams looking for a SAST tool that is more connected to day-to-day development, but with a purchase driven by AppSec. The focus is not on doing a general engineering review, but on finding vulnerabilities, prioritizing what needs to be fixed, and helping the team resolve it earlier.

Snyk also fits well in companies that want to concentrate SAST, SCA, IaC, and container security in the same platform. For teams that already use Snyk for dependencies or security governance, Snyk Code comes in almost as a natural extension of the flow.

The point that deserves attention is the commercial model. Snyk sells the platform by modules, so the real cost depends on the package adopted, the products included, and usage volume. For small teams, this can become more expensive than it looks when only looking at the entry price. It is also worth looking carefully at where features like AI Fix, advanced governance, and custom rules come in.

Pros

Snyk’s main point is the developer-first experience. Feedback appears early, in the IDE, CLI, SCM, or CI, so the developer can fix some of the problems before they become a ticket or security backlog.

Another important point is the integration with the rest of the platform. For teams that already deal with vulnerable dependencies, IaC, containers, and AppSec policies, using Snyk Code inside the same stack can simplify operations.

The fix side also helps. Features like DeepCode AI Fix and Snyk Agent Fix reduce the distance between finding a problem and opening a path to fix it, which is especially useful in teams with a large accumulated security backlog.

Cons

The caution is not expecting Snyk Code to work as a deeply contextual PR reviewer, at the level of architecture, repository history, and specific product rules. It is more centered on security than on understanding how the team reviews code day to day.

It is also worth looking carefully at the price. Since the platform is modular, the bill can go up as more products, integrations, higher limits, and advanced features come in.

Custom rules exist, but they do not seem to be the simplest entry path for every team. In general, this kind of feature tends to make more sense in larger plans or in teams with a more mature AppSec operation.

Pricing

On the Team plan, Snyk starts at $25 per contributing developer per month, with a minimum of 5 developers. There is a Free plan with limits, and the Ignite and Enterprise plans are custom pricing.

4. Checkmarx One AI

Checkmarx One remains a well-known reference in the enterprise AppSec market. The platform covers SAST, SCA, API security, DAST, containers, IaC, secrets, and newer AI-assisted remediation features.

It is a tool that usually makes sense when the company already has a formal AppSec program, with the need to centralize scanners, policies, triage, and fixes in the same platform. It is not a solution designed for small or very simple adoption. It fits better in organizations that already treat application security as part of engineering governance.

The Checkmarx One Assist layer reinforces this positioning. Developer Assist brings detection and guidance into the IDE, covering SAST, SCA, IaC, secrets, and packages. The idea is to reduce the distance between finding a vulnerability and guiding the fix, especially in companies with a high code volume and a large accumulated security backlog.

In a practical comparison, Checkmarx is not the best option on the list for some teams. It makes more sense for companies that need broad coverage, centralized control, and a more structured AppSec process.

Pros

Checkmarx’s main value is enterprise coverage. It brings several types of analysis together in the same platform, which helps companies that need to deal with proprietary code, dependencies, APIs, containers, IaC, and secrets without spreading everything across separate tools.

Another important point is process centralization. For AppSec teams that need to track findings, prioritize risk, guide fixes, and maintain policies across several repositories, Checkmarx offers a more complete base than tools focused on only one part of the problem.

The AI-assisted layer also helps in the remediation flow. Developer Assist brings guidance closer to the environment where the developer works, which can reduce some of the back-and-forth between AppSec and engineering.

Cons

The main caution is adoption complexity. Consultative sales, bundles, add-ons, and enterprise operation can make sense for a large organization, but become too much for smaller teams or for anyone who wants to test a tool quickly.

It is also a platform where the value shows up better when internal maturity already exists. Without a clearer AppSec process, part of the coverage can become just another queue of findings to triage.

Another point is that Checkmarx tends to be less attractive for squads that want a simple entry point, quick setup, and a direct focus on the PR flow. In those cases, lighter tools may fit better.

Pricing

Checkmarx does not publish an open pricing table. The model is custom pricing, with bundles and packages defined according to the company’s scenario.

5. GitHub Advanced Security (CodeQL)

CodeQL is one of the best-known tools on this list when the conversation is semantic analysis. Instead of just searching for known patterns, it treats code as queryable data. This makes it possible to analyze flow, find vulnerability variants, and create custom queries with a level of depth that few tools offer.

In practice, it makes a lot of sense for companies that are already in the GitHub ecosystem and want to bring code scanning into the normal development flow. PR alerts, query packs, security overview, and integration with GitHub Code Security make the experience simpler for GitHub-first teams.

The point of attention is that CodeQL delivers more when there is technical capacity to go beyond basic use. The tool can run with ready-made scans, but the differentiator appears when the team can work with queries, adjust workflows, and create its own checks over time.

That is why it is not necessarily the simplest option for every team. It is a good tool for those who want depth and already have the maturity to operate this type of analysis, but it may require more effort from teams looking for a quick and low-customization entry point.

Pros

CodeQL’s main differentiator is analysis depth. For vulnerabilities that depend on dataflow, relationships between functions, and a more semantic understanding of the code, it remains one of the most complete options.

Another important point is the integration with GitHub. Code scanning alerts, security overview, dependency review, and Copilot Autofix create a simpler experience for companies that already centralize development on the platform.

The ability to create custom queries also matters. Teams with more AppSec maturity can turn internal patterns, vulnerability classes, and specific codebase cases into their own analyses.

Cons

The main caution is the ecosystem. CodeQL can be used in other contexts, but part of the operational advantage is in the native integration with GitHub. Outside GitHub-first environments, it may require more work to deliver a similar experience.

Another point is the technical curve. CodeQL is very good, but getting more out of the tool requires people who are comfortable with query language, security workflows, and maintaining checks over time.

It is also important not to treat CodeQL as a “plug and play” tool for every scenario. Basic use already helps, but the most interesting part appears when there is a security operation prepared to customize and maintain the analysis.

Pricing

In the GitHub Code Security offering, the public price is $30 per active committer per month. For private repositories, it works as an add-on inside the GitHub Team or Enterprise ecosystem. For public repositories on GitHub.com, some security features are available for free.

6. Semgrep

Semgrep remains one of the best-known options when the conversation is SAST with customization and direct integration with the developer flow.

It became known for combining ready-made rules, custom rules, and lighter adoption than many traditional enterprise platforms. Today, the platform already goes beyond SAST and includes SCA, secrets, reachability, and AI features for triage and remediation.

In practice, it makes a lot of sense for teams that want to adapt analysis to the way they work, without depending only on generic checks. You can use community rules, write your own rules, run it in CI, integrate with PRs, and bring part of the analysis into the normal development flow.

The point of attention is that Semgrep works best when someone on the team takes care of rules, policies, and adjustments. In teams that just want to turn the tool on and never touch it again, part of its potential ends up underused.

Pros

Semgrep’s main differentiator is rule customization. Teams that already know which patterns they want to reinforce can turn that into concrete analysis without depending only on a closed package of checks.

Coverage is also broad. Semgrep offers SAST, SCA, and secrets detection, integrates with IDE and CI/CD, and the documentation mentions support for more than two dozen languages, with cross-file analysis and reachability in some of them.

Another important point is that it serves both smaller teams and more mature AppSec operations well. A team can start with ready-made rules and evolve toward more specific policies as the process matures.

Cons

The main caution is operational. Semgrep delivers more when there is someone maintaining rules, policies, and triage criteria. Without that care, the tool still helps, but it tends to be closer to a common scanner.

Another point is that it is still more centered on AppSec than on general engineering review. To analyze product decisions, repository history, specific architecture, and team memory, other approaches may make more sense.

It is also important to look at plan limits. Features like on-prem SCM support, custom CI/CD integrations, dedicated infrastructure, and no repository or contributor limit appear in Enterprise.

Pricing

Semgrep has a Free plan for up to 10 contributors. On Teams, Code and Supply Chain start at $30 per contributor per month, while Secrets starts at $15 per contributor per month. The Enterprise plan is custom pricing.

7. Aikido

Aikido should not be read only as a SAST tool. It works more like an all-in-one code and cloud security platform, and that changes how the product should be evaluated.

It covers SAST, SCA, IaC, secrets, cloud, runtime, containers, and AI remediation. For companies that want to reduce the number of separate tools, Aikido can make sense because it concentrates several AppSec fronts in a single operational layer.

In the scope of this article, it appears because it covers PR checks, IDE, custom rules, autofix, and risk-oriented analysis. But the purchase does not revolve only around SAST. The center of the proposal is a broader platform for application and cloud security.

The AI SAST side also stands out because it tries to go beyond traditional rules. The proposal is to find classes of problems that more static scanners usually struggle to catch, such as logic flaws, broken access controls, and flows that depend more on application context.

Pros

Aikido’s main point is the breadth of the package. A team can look at code security, dependencies, IaC, cloud, containers, and secrets inside the same platform. This mainly helps smaller companies or teams with a lean AppSec team that do not want to operate several separate tools.

The AI remediation layer also helps the flow. Instead of only pointing out the problem, the platform tries to bring the fix closer to where the developer works, both in the PR and in the IDE.

Another positive point is commercial transparency. Aikido publishes prices more clearly than many enterprise vendors, which makes the initial evaluation easier and avoids depending on a sales conversation right at the beginning.

Cons

The main caution is depth by language and stack. The documentation itself shows that some features, such as cross-file taint analysis, have more complete support in certain stacks than in others. In a serious POC, this needs to be tested on the company’s real codebase.

It is also worth remembering that Aikido is a broad platform. For those looking only for pure SAST, part of the package may be larger than necessary.

Another point is that teams with more AppSec maturity may still prefer more specialized tools for specific cases, especially when they need very advanced rules, deep tuning, or an operation already built around another scanner.

Pricing

The Developer plan is free for up to 2 users. The Basic plan starts at $300 per month, including 10 users. The Pro plan starts at $600 per month, also including 10 users. The Enterprise plan is custom pricing.

8. Endor Labs

Endor Labs first became known for supply chain and reachability, but today it is also pulling the conversation toward AI SAST and AI security code review.

The proposal is to attack a very common AppSec problem: reducing noise and bringing analysis closer to what can actually be exploited. Instead of treating every finding as equal, the platform tries to prioritize what has a higher chance of representing real risk to the application.

In the SAST layer, Endor uses Opengrep together with AI analysis to classify findings as true positives or false positives. In the AI SAST layer, the promise is to get closer to the reasoning of a security engineer, looking at multi-file flows, relationships between functions, and defects that are harder to catch with simple rules.

There is also an AI Security Review layer for PRs. It brings part of this analysis into the code review flow, but today it still seems more restricted: the documentation positions the feature for GitHub and in beta.

In the comparison, Endor Labs makes more sense in companies where the volume of findings has already become an operational problem. It does not seem to be a lightweight or self-serve purchase for every team. The fit is better in organizations with more mature AppSec, many dependencies, many repositories, and a clear need for prioritization.

Pros

Endor Labs’s main point is the combination of supply chain, reachability, and AI security analysis. For teams struggling with too many alerts, this helps better separate what deserves attention from what probably will not become a real risk.

Another important point is the attempt to reduce false positives in SAST. AI classification helps attack one of the oldest pains in this type of tool: the backlog full of findings that no one trusts enough to fix.

The more contextual analysis also helps in complex scenarios. Flows between files, multiple functions, and indirect dependencies are usually hard for simpler scanners, and that is exactly where Endor tries to differentiate itself.

Cons

The main caution is the adoption profile. Endor Labs looks more like an enterprise product than a simple tool to get started with in a few minutes. For small squads or teams without a clearer AppSec operation, it may be more product than necessary.

The scope of AI Security Review also needs to be confirmed. Based on the current positioning, it still appears more restricted to GitHub and in beta, so it needs to be validated before becoming a purchase criterion.

Pricing

Endor Labs does not publish an open pricing table. The model is custom pricing.

9. Veracode

Veracode is one of the most traditional names on this list. That still counts a lot in large, regulated companies or companies with many different systems, including legacy applications.

It is not the newest tool in the comparison, and it does not try to sell a lightweight adoption experience. Its point is broad coverage, a more structured process, and use in environments where security needs to go through governance, audit, and well-defined criteria.

Veracode’s SAST works with source code analysis, compiled binary, or a combination of both. This detail matters in companies with varied stacks, older systems, and distributed teams, where the flow is not always as simple as “opened a PR, run the scanner, fix it right there.”

In the comparison, Veracode makes more sense for organizations that already have a more mature AppSec operation. For squads that want something simpler, closer to the PR, and with more local autonomy, other tools may fit better day to day.

Pros

Veracode’s main point is coverage. The public documentation highlights support for more than 100 languages and frameworks, which helps a lot in companies with large portfolios and applications in different stacks.

Another important point is binary and bytecode analysis. This is still useful in environments where the company needs to evaluate applications without depending only on source code, or where there are legacy systems that are hard to standardize.

The remediation side with Veracode Fix also helps bring security closer to the development flow. For companies that already use the platform at scale, this can reduce some of the effort between finding a flaw and guiding the fix.

For regulated organizations, the combination of coverage, market history, and SDLC integration remains a clear reason to consider Veracode.

Cons

The main caution is operational effort. Veracode usually makes more sense in companies that already have an AppSec process, governance, and teams prepared to operate a platform of this size.

For small teams or squads that want fast and lighter adoption, it can feel too big for the problem.

It also would not be my first choice if the priority were team-level flexibility, quick workflow customization, or a more open experience around model, context, and specific product rules.

Pricing

Veracode does not publish a self-serve pricing table for SAST. The model is custom pricing.

10. Mend.io

Mend.io has moved beyond its origin in open source security. Today, it presents itself as an AppSec and AI security platform, covering SAST, SCA, containers, update automation, and governance of AI components.

This changes how the product should be evaluated. Instead of looking at Mend only as a SAST scanner, many companies will see the tool as a way to bring more parts of the security operation into a single layer.

On the code axis, Mend combines SAST with SCA, reachability-based prioritization, AI fixes, and integration with coding assistants. This helps companies that deal at the same time with vulnerabilities in proprietary code, open source dependencies, and code generated with AI support.

There is also a clear governance angle. Mend tries to capture risk earlier, including in tools like Cursor, Windsurf, and Copilot, before the problem reaches the PR or becomes security backlog.

Pros

Mend’s main point is the attempt to bring code security, dependencies, and AI security into the same platform. For companies already struggling with several separate tools, this can simplify part of the operation.

The platform also helps in scenarios where dependencies, updates, and reachability already consume a lot of the team’s time. Instead of just listing vulnerabilities, Mend tries to better prioritize what needs attention and reduce some of the manual work of fixing.

Another important point is its presence in flows with coding assistants. For companies concerned about AI-generated code, this puts Mend in a more current conversation than tools focused only on traditional SAST.

Cons

The main caution is scope. For some teams, Mend can be too much platform for a problem that is still small or very localized.

It is also important to validate the IDE experience and the team’s real workflow. Since part of the documentation shows transitions in plugins and integrations, it is worth testing in the company’s stack before treating this as a decisive criterion.

Another point is cost. The full proposal goes through AppSec, supply chain, and AI security, so the bill can get high for teams that only want to solve SAST in isolation.

Pricing

On the pricing page, Mend lists the AppSec plan at up to $1,000 per dev/year, AI Premium at up to $300 per dev/year, and Renovate Enterprise at up to $250 per dev/year.

11. Socket

Socket appears on this list because code security no longer lives separately from supply chain. In many companies, the most urgent risk is not in proprietary code, but in vulnerable dependencies, malicious packages, and CVE alerts that do not always affect the application.

The platform was born in software supply chain security and is still more specialized in that than in traditional SAST. The focus is on vulnerabilities and dependency behavior, reachability, malware, policy enforcement, GitHub Actions, AI models, and firewall at install time.

It has already added basic SAST, secrets, container scanning, and AI model analysis, but it should not be read as a tool focused mainly on proprietary code. Socket’s point is to help the team better understand risk coming from the open source ecosystem and cut some of the noise that usually blocks triage.

If the team’s main problem is “I cannot take another dashboard full of irrelevant CVEs,” Socket enters the comparison early. If the priority is to find logic flaws, auth bypass, or flow problems inside the application code, it works better as a complement to a SAST tool more focused on first-party code.

Pros

Socket’s main differentiator is reachability. The platform tries to show which vulnerabilities can actually affect the application, instead of treating every CVE in a dependency as the same priority.

Another important point is package behavior analysis. In supply chain, the risk does not come only from known vulnerabilities. Malicious packages, typosquatting, suspicious scripts, and dangerous changes in dependencies also count.

Protection at install time also helps. Socket Firewall can block suspicious packages before they enter the developer’s environment, which reduces a class of problems that traditional scanners usually catch too late.

Public pricing also makes the initial evaluation easier. For smaller teams, it is simpler to understand the bill before talking to sales.

Cons

The main caution is expectation. Socket is not the tool I would put as the first choice for deep analysis of proprietary code, business logic, or internal application flows. The platform’s focus is still supply chain.

It can complement an AppSec stack very well, but it does not necessarily replace a SAST tool more dedicated to internal code.

It is also worth looking carefully at what comes in each plan. Depending on the level of analysis, repository volume, and governance needs, the simplest plan may not cover everything the team needs.

Pricing

Socket publishes a Free plan, a Team plan at $25 per developer per month, a Business plan at $50 per developer per month, and Enterprise with custom pricing.

12. Codacy

Codacy is an option when the company wants to combine quality, security, and guardrails in a platform that is simple to turn on and operate.

It does not try to occupy the same place as a highly specialized SAST tool. The proposal appears more as a practical layer for continuous analysis, quality gates, PR feedback, AI guardrails, and visibility by repository and team.

For some teams, that is exactly what is missing. Not necessarily a deeper tool, but a simpler way to keep quality and security standards inside the normal development flow.

Codacy also stands out because of its more predictable commercial model. The company presents plans without usage limits, which can make the bill easier for teams that do not want to estimate consumption by analysis, repository, or run.

Pros

Codacy’s main point is simple adoption. The platform tries to avoid too much pipeline complexity and bring fast feedback to the PR and the IDE.

The coverage fits the product proposal well. There are 49 languages and frameworks, with SAST, secrets, dependency checks, malicious package detection, dashboards, and AI guardrails.

Another important point is the focus on enforcement in the developer flow. Instead of leaving quality and security only in a separate dashboard, Codacy tries to bring these signals to where the team already works.

For teams that want to improve quality and security without restructuring the whole process, this helps a lot.

Cons

The main caution is depth. Codacy makes more sense as an operational platform for continuous analysis than as the only SAST engine for more complex cases.

It is also important to consider SCM limitations. The public documentation shows a focus on GitHub Cloud, GitLab Cloud, and Bitbucket Cloud. At the moment, there is no support for Git on-premise or Azure Repos.

Another point is that, in companies with a more mature AppSec operation, Codacy may fit better as a quality and guardrails layer than as a direct replacement for more specialized tools.

Pricing

Codacy offers a free Developer plan. The Team plan starts at $18 per developer per month annually or $21 monthly. The Business plan is custom pricing.

SAST vs DAST vs IAST vs AI Code Review

SAST analyzes code without running the application. It is great for finding problems early, before deployment, especially flaws tied to unsafe flow, wrong API usage, injection, and risky patterns.

DAST tests the running application. It does not see the code, but it sees exposed behavior. This helps with problems that only appear in the active application, such as authentication, headers, HTTP flows, and flaws accessible through the interface.

IAST tries to combine analysis with runtime instrumentation. In theory, it brings the best of both worlds together. In practice, it usually requires more operational effort and is not always the first layer a team adopts.

AI Code Review is not the same as SAST, although there is overlap. AI review tools work very well in PRs, incremental changes, repository context, and LLM-generated code. They help filter the basics and point out risks earlier, but they do not fully replace a good deterministic scanner.

In practice, the healthiest stack today usually combines at least:

• SAST for static code analysis
• SCA for vulnerable or malicious dependencies
• secrets scanning for exposed credentials
• AI code review for PRs, context, and AI-generated code
• DAST when the application is already in a more mature execution stage

Full comparison of SAST tools in 2026

FAQ

What is the best SAST tool for most teams in 2026?

If your definition of SAST is strictly a classic static analysis engine, Semgrep and CodeQL are among the strongest choices. But if the question is more practical, meaning which tool actually helps detect risk in the real development flow, with context, custom rules, and less friction, Kodus stands out as the most complete option for most modern teams.

Why does Kodus appear so strongly on this list if it is not a pure classic SAST tool?

Because the market has changed. Today, many teams do not just need a scanner that generates alerts. They need useful structural analysis in the PR, in the CLI, and in the team’s workflow. Kodus combines AST-based analysis, module dependencies, natural-language rules, repository context, cross-file checks, and configurable severity. In practice, this puts it as a very good SAST option, especially for teams that want more control and less noise.

Which tool has the best custom rules?

Semgrep remains a strong reference in custom rules for technical AppSec. But Kodus deserves attention because it makes this process much more accessible in the team’s day-to-day work, with natural-language rules, scope by directory or language, categories and severity, plus sync with existing rule files. For many teams, this is more practical than depending only on a more rigid technical engine.

Which tool has the best value for money?

For teams that value flexibility, predictability, and control, Kodus has one of the best value-for-money profiles on the list. The Community plan is free, Teams costs $10 per dev/month, and the BYOK model avoids token markup. Semgrep Free is also a great entry point. Broader platforms like Snyk, Mend, Veracode, and Checkmarx tend to make more sense when the company already wants a larger AppSec strategy.

What is the best option for a monorepo?

Kodus is one of the most natural options for monorepos because it allows rules by directory, different scopes by code area, repository context, and analysis that is more adaptable to the way the team organizes the codebase. Semgrep also works very well in this scenario, especially in teams with more mature AppSec. CodeQL fits better when the GitHub ecosystem is already dominant.

Which tool is better for teams already living in GitHub?

CodeQL is the most natural choice for GitHub-first organizations that want deep semantic analysis and native integration with GitHub Code Security. Still, Kodus remains very competitive in this scenario when the goal is to add more flexible rules, review context, and a more adaptable layer of control in the PR.

Which tool reduces false positives best?

Endor Labs, Semgrep, Aikido, and Mend talk a lot about noise reduction, but through different paths. Endor bets heavily on exploitability and reachability. Semgrep combines fine tuning with AI-assisted triage. Aikido tries to capture more contextual bugs with AI SAST. Mend mixes prioritization of first-party and open source risk. Kodus reduces noise through another path: it uses repository context, team history, and custom rules to avoid generic comments and findings that are not very actionable.

Which tool makes the most sense for startups and small teams?

Kodus, Semgrep Free, Codacy, and Aikido’s free plan are usually more accessible entry points. Kodus’s advantage is that it already delivers a strong base of contextual analysis and customization without requiring a heavy AppSec platform from the start. For small teams, that usually matters a lot.

What is the best open source tool for SAST?

Among the more open options, Semgrep and CodeQL are two well-known names in SAST. Semgrep works well for those who want custom rules and simpler adoption. CodeQL makes more sense for GitHub-first teams that need deeper semantic analysis.

Kodus comes in through another path. It is not a pure classic SAST tool, but it can be the best option for teams that want to bring static analysis into the real review flow. The platform combines AST-based analysis, repository context, natural-language rules, BYOK, and greater control over how findings appear in the PR.

In practice, if the idea is to have a traditional SAST scanner, Semgrep or CodeQL may make more sense. If the goal is to reduce risk in day-to-day development, with team context and fewer loose alerts, Kodus tends to be the most complete option.

Final verdict

If you look at this category in a very traditional way, there are several good options here. Semgrep, CodeQL, Snyk Code, SonarQube, and Veracode remain important names when the conversation is static security analysis.

But the most useful choice for many teams today is not necessarily the tool that finds the most alerts. It is the one that can turn static analysis into something the team can understand, prioritize, and fix inside the real development flow.

This is where Kodus differentiates itself. It does not try to be just another scanner separated from the process. The platform combines AST-based analysis, module dependencies, natural-language rules, repository context, cross-file checks, CLI, MCP plugins, BYOK, model choice, and an open source, model-agnostic approach.

In practice, this gives more control over how the analysis happens and which standards actually matter to the team. Instead of forcing the team to treat security as an external queue of alerts, Kodus brings that process closer to review, where many things can still be fixed before they become backlog or incidents.

For organizations looking for a large, centralized, and more traditional AppSec platform, other tools on the list may make more sense. But for teams that want to bring static analysis into the daily work of engineering, with repository context, team rules, and fewer loose alerts, Kodus is one of the most complete options on this list.

If the priority is to find risk early, adapt analysis to the real context of the codebase, and have more control over how security enters the workflow, I would start with it.