Best AI AppSec Assistants

How Many AI AppSec Assistants Products Does G2 Track?

Total Products under this Category: 25

Category Stats (Jul 2026)

Average Rating: 4.44/5 The average rating of products in this category, based on all submitted ratings
Top Trending Product: Black Duck (+1.16%) - Among all products in this category, Black Duck recorded the largest rating increase compared to last month

Last updated: July 15, 2026

How Does G2 Rank AI AppSec Assistants Products?

Why You Can Trust G2's Software Rankings:

30 Analysts and Data Experts
1,600+ Authentic Reviews
25+ Products
Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

GitHub Copilot

By GitHub

4.5/5(373)

What do users say?

Users consistently praise the real-time code suggestions and seamless integration with popular IDEs, which significantly enhance productivity and reduce repetitive tasks. Many appreciate how it adapts

Pros and Cons

Ease of Use (149) Poor Coding (39)

FAQs About AI AppSec Assistants

Generated using AI

Last updated: June 3, 2026

Which AI AppSec platforms avoid high false positive rates that waste security and developer time

Based on G2 reviews, these products are most often praised for reducing noisy findings and helping teams focus on real issues.

Aikido Security — low-noise findings with fast remediation.
DryRun Security — contextual PR feedback with high signal.
SonarQube — early code checks with quality gates.
Snyk — reachability-based triage for dependencies.

AI AppSec Assistants with accurate detection of OWASP Top 10 vulnerabilities and supply chain risks

According to verified users, strong AI AppSec Assistants are valued for surfacing meaningful vulnerabilities across code, dependencies, containers, secrets, and cloud environments without overwhelming teams with noise. Reviews repeatedly highlight the importance of clear remediation guidance, contextual findings, and prioritization that helps developers act quickly. Recent G2 feedback also points to demand for coverage of common web application risks such as injection flaws, authorization issues, leaked secrets, and insecure dependencies. Buyers evaluating this category should look for products that combine code scanning with software composition analysis, explain why an issue matters, and fit naturally into pull requests, CI pipelines, or repository-based workflows so fixes happen before release.

Which AI AppSec solutions integrate into IDEs and provide real-time guidance during code development

Based on G2 reviews, these products stand out for developer-facing workflows, in-editor feedback, or fast guidance during coding and review.

SonarQube — IDE plugin feedback with quality gates.
Snyk — VS Code scans and remediation help.
Amazon Q Developer — IDE assistance with security suggestions.
Aikido Security — workflow guidance with actionable fixes.

What are AI AppSec Assistants

AI AppSec Assistants are tools that help teams find, prioritize, and remediate application security issues within software development workflows. Recent G2 reviews describe them as products that scan code, dependencies, containers, secrets, and related environments while giving developers actionable guidance instead of long lists of raw alerts. They are commonly used in pull requests, repositories, CI pipelines, and dashboards so teams can catch vulnerabilities earlier and reduce manual review effort. Across the category, buyers consistently value fast setup, clear explanations, lower false-positive rates, and remediation support that helps engineering and security teams work from the same findings without slowing delivery.

How does AI AppSec Assistants integrate with GitHub

G2 reviewers mention GitHub integration as one of the most practical workflows in this category. Recent reviews describe teams connecting repositories quickly, scanning pull requests or merged code, and receiving findings directly where developers already work. Common benefits include PR comments, automatic repository onboarding, alerts on new issues, and remediation guidance that reduces context switching. Buyers also appear to value tools that support continuous monitoring after code changes, help prioritize what should be fixed first, and make security review easier for both developers and AppSec teams. In the latest G2 feedback, GitHub-connected workflows are especially associated with faster reviews, earlier detection, and better trust in findings.

Replit

By Replit

4.4/5(384)

What do users say?

Users consistently praise Replit for its ease of use and intuitive interface, which allows both beginners and experienced developers to quickly build and deploy applications without extensive coding k

Pros and Cons

Ease of Use (210) Expensive (68)

DryRun Security

By DryRun Security

4.9/5(20)

What do users say?

Users consistently praise the product for its ease of use and automated scans, which streamline security processes and integrate seamlessly into existing workflows. The ability to receive actionable f

Pros and Cons

Security (13) Slow Performance (2)

Amazon Q Developer

By Amazon Web Services (AWS)

4.6/5(48)

What do users say?

Users consistently praise Amazon Q Developer for its context-aware suggestions and seamless integration with AWS services, which significantly enhances coding efficiency. Many appreciate how it helps

Pros and Cons

Ease of Use (22) Poor Suggestions (6)

Appdome

By Appdome

4.8/5(88)

What do users say?

Users consistently praise the product for its ease of use and exceptional support, highlighting how the no-code integration simplifies mobile app security without requiring extensive coding. Many appr

Pros and Cons

Customer Support (23) Expensive (11)

Codeant AI Code Reviewer

By CodeAnt AI

4.8/5(6)

Product Description

CodeAnt AI reviews your code line by line, finds critical code quality issues and security vulnerabilities, explains their impact, and guides you on how to fix them. It’s SOC 2 and HIPAA compliant,

Pros and Cons

Code Quality (2) Difficult Learning (1)

Checkmarx

By Checkmarx

4.2/5(47)

What do users say?

Users consistently praise the ease of use and comprehensive reporting provided by Checkmarx, noting that it simplifies the process of identifying and fixing security vulnerabilities in code. The tool'

Pros and Cons

Implementation Ease (2) False Positives (1)

CybeDefend

By CybeDefend

5/5(3)

Product Description

CybeDefend is the application security platform built for the AI coding era. Traditional shift-left security detects vulnerabilities after the code is written. But with Claude Code, Cursor, Copilot a

Tabnine

By Tabnine

4.1/5(55)

What do users say?

Users consistently praise the product for its ability to significantly enhance coding productivity by providing quick and relevant code suggestions. Many appreciate its seamless integration with vario

Pros and Cons

Ease of Use (18) Poor Coding (7)

Black Duck

By Synopsys

4.1/5(31)

What do users say?

Users consistently praise the product for its comprehensive analysis and ability to identify open source vulnerabilities effectively. Many appreciate its extensive knowledge base and integration capab

Pros and Cons

Accuracy of Findings (1) Resource Constraints (1)

Semgrep

By Semgrep

4.6/5(56)

What do users say?

Users consistently praise Semgrep for its ease of use and customizability, allowing developers to quickly integrate it into their workflows and create tailored rules for their specific needs. The tool

Pros and Cons

Ease of Use (16) Not User-Friendly (7)

Veracode Application...

By VERACODE

3.8/5(26)

What do users say?

Users consistently praise the platform for its ease of integration with development tools and its comprehensive security reporting. Many appreciate how it streamlines the process of identifying vulner

Pros and Cons

Security (5) Expensive (2)

Core Capabilities of AI AppSec Assistants

To qualify for inclusion in the AI AppSec Assistants category, a product must:

Use AI to provide real-time application security assistance within a development environment
Automatically identify security weaknesses and vulnerabilities
Remediate issues or deliver contextual, actionable remediation guidance
Seamlessly integrate into development teams' existing workflows and practices

Common Use Cases for AI AppSec Assistants

Development and security teams use AI AppSec assistants to shift security left, catching and fixing vulnerabilities earlier in the development cycle without slowing down engineering workflows. Common use cases include:

Detecting insecure code patterns and vulnerabilities in real time as developers write code
Providing contextual remediation guidance that explains security issues and suggests specific fixes in the developer's language and framework
Improving collaboration between development and security teams by making security feedback actionable within existing developer environments

How AI AppSec Assistants Differ from Other Tools

While AI coding assistants help developers with general programming tasks such as code completion and error detection, AI AppSec assistants focus specifically on application security, identifying vulnerabilities, explaining security risks, and guiding remediation within the development environment. This specialization makes them distinct from general coding assistants and from broader application security tools that operate outside the IDE, enabling a "secure by default" approach embedded directly in developer workflows.

Insights from G2 on AI AppSec Assistants

Based on category trends on G2, real-time vulnerability detection and contextual remediation guidance stand out as standout capabilities. Faster vulnerability resolution and improved developer adoption of secure coding practices stand out as primary outcomes of adoption.