Data as of Oct 18, 2026Based on 478 AI responses
Reviewed by Dimitry Apollonsky
AI summary
Semgrep holds a wide lead across general security queries, especially for tracking down multi-step vulnerabilities and scanning code for insecure LLM library usage. When teams want automated pull request feedback with OWASP fix suggestions, CodeRabbit AI is the usual answer instead.
Rank and Mentioned in · since Jul 5
| # | Brand | Recommended for | Mentioned in |
|---|---|---|---|
| 1 | fast static analysis, custom security rules, and scanning LLM library usage | fast static analysis, custom security rules, and scanning LLM library usage | 72% |
| 2 | real-time scanning of AI-generated snippets and automated IDE remediation | real-time scanning of AI-generated snippets and automated IDE remediation | 44% |
| 3 | deep semantic analysis, custom query building, and enterprise codebase audits | deep semantic analysis, custom query building, and enterprise codebase audits | 36% |
| 4 | developer-centric vulnerability management and broad CI/CD pipeline integration | developer-centric vulnerability management and broad CI/CD pipeline integration | 36% |
| 5 | exploitability prioritization, customizable enterprise rules, and regulated environment compliance | exploitability prioritization, customizable enterprise rules, and regulated environment compliance | 27% |
| 6 | native GitHub workflow scanning combined with Copilot Autofix suggestions | native GitHub workflow scanning combined with Copilot Autofix suggestions | 19% |
| 7 | automated pull request summaries and inline code quality reviews | automated pull request summaries and inline code quality reviews | 18% |
| 8 | pipeline quality gates and IDE feedback through SonarLint integration | pipeline quality gates and IDE feedback through SonarLint integration | 17% |
| 9 | enterprise supply chain security and real-time developer IDE checks | enterprise supply chain security and real-time developer IDE checks | 14% |
| 10 | identifying complex business logic flaws and context-dependent vulnerabilities | identifying complex business logic flaws and context-dependent vulnerabilities | 12% |
| 11 | 12% | ||
| 12 | 12% | ||
| 13 | 12% | ||
| 14 | 10% | ||
| 15 | 9% |
Weeks of Jul 27 – Sep 6, 2026 · Since Jul 5
More topics
Widest split: CodeQL, 49% on ChatGPT Search and 23% on Google AI Mode.
| Brand | ChatGPT Search | Google AI Mode | Comparison |
|---|---|---|---|
| Semgrep | 78% | 66% | |
| Snyk Code | 38% | 49% | |
| CodeQL | 49% | 23% | |
| Snyk | 36% | 35% | |
| Checkmarx | 25% | 29% | |
| GitHub Advanced Security | 14% | 23% | |
| CodeRabbit AI | 17% | 18% | |
| SonarQube | 16% | 18% | |
| Checkmarx One | 14% | 14% | |
| ZeroPath | 7% | 17% |
53% of citations point at the ranked brands’ own sites. augmentcode.com, github.com, youtube.com are the most-cited sites outside the ranked brands’ own domains.
Market map
Mentioned in · since Jul 5
Leading brands by topic
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We need to scan our code for insecure usage of LLM libraries. What's the best static analysis tool that understands AI security risks?
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I need an AI tool to review my code specifically for security flaws. Which one is the most powerful?