{"slug":"semgrep","name":"Semgrep","domain":"semgrep.dev","verdict":"As of 2026-07-15, ChatGPT, Claude, Gemini, Grok collectively rank Semgrep first for sast tool for application security (one of 6 leaderboards it appears on). Source: https://modelsagree.com/product/semgrep (modelsagree.com, CC BY 4.0).","best_rank":1,"categories":6,"brief":{"category":"best-sast-tool-for-application-security","title":"Best SAST tool for application security","rank":1,"of":6,"top":null,"day":"2026-07-16","why":[{"t":"Fast CI and IDE scans","m":["ChatGPT","Claude","Gemini","Grok"],"q":"fast CI and IDE scans"},{"t":"Highly customizable rules","m":["ChatGPT","Claude","Gemini","Grok"],"q":"highly customizable rules in familiar syntax"},{"t":"Strong accuracy with low noise","m":["ChatGPT","Claude","Grok"],"q":"strong accuracy with low noise when tuned"},{"t":"Broad language support","m":["ChatGPT","Grok"],"q":"broad language support (~30+)"}],"gap":[],"fix":[{"t":"Deep analysis requires paid tiers","m":["ChatGPT","Claude"],"q":"Its deepest interprocedural analysis and strongest managed rules require paid tiers"},{"t":"Not deepest for complex data flows","m":["ChatGPT","Gemini","Grok"],"q":"not the deepest semantic analysis for complex data flows"},{"t":"Requires rule expertise","m":["Grok"],"q":"Requires rule expertise/investment for optimal depth/custom coverage beyond community rules"}]},"entries":[{"slug":"best-sast-tool-for-application-security","title":"Best SAST tool for application security","rank":1,"of":6,"score":20,"appearances":4,"modelRanks":{"ChatGPT":1,"Claude":1,"Gemini":1,"Grok":1},"reason":"Best overall balance of fast CI and IDE scans, approachable custom rules, broad modern-language coverage, and high-signal commercial cross-file analysis; assumes a typical cloud-native team values developer adoption and tunability","reasons":[{"model":"ChatGPT","reason":"Best overall balance of fast CI and IDE scans, approachable custom rules, broad modern-language coverage, and high-signal commercial cross-file analysis; assumes a typical cloud-native team values developer adoption and tunability"},{"model":"Claude","reason":"Best balance of speed, accuracy, and control for a working AppSec team — rules are transparent YAML anyone can read and write, scans run in minutes in CI, false-positive rates are low, and the Pro engine adds real cross-file/cross-function taint analysis; it has become the default recommendation for teams that want SAST developers won't ignore. Near-tie with CodeQL at the top: Semgrep wins on ease and speed, CodeQL on analysis depth."},{"model":"Gemini","reason":"Offers lightweight, pattern-matching speed with a highly customizable YAML-based rule syntax that developers can easily write and debug, combined with a vast registry of community-maintained rules."},{"model":"Grok","reason":"Exceptional speed (seconds for PR scans), highly customizable rules in familiar syntax, strong accuracy with low noise when tuned, excellent developer adoption and CI integration, free open-source core with broad language support (~30+), proven in real-world DevSecOps for velocity without heavy overhead. Assumption: typical practitioner values actionable, fast feedback over out-of-box enterprise dashboards."}],"fixes":[{"model":"ChatGPT","fix":"Its deepest interprocedural analysis and strongest managed rules require paid tiers, while the open-source engine can miss complex cross-file vulnerabilities"},{"model":"Claude","fix":"The deep interprocedural analysis and best rulesets sit behind the commercial Pro engine — the OSS engine is largely intra-file, and the 2024 license tightening (which spawned the Opengrep fork) makes it a weaker pick for strictly-OSS shops."},{"model":"Gemini","fix":"Taint analysis and deep interprocedural analysis are less mature compared to traditional heavyweight AST-based engines, making it less effective for complex multi-file data flows."},{"model":"Grok","fix":"Requires rule expertise/investment for optimal depth/custom coverage beyond community rules; not the deepest semantic analysis for complex data flows."}],"updated":"2026-07-15","rank_history":{"days":["2026-06-29","2026-06-30","2026-07-08","2026-07-09","2026-07-10","2026-07-14","2026-07-15"],"ranks":[2,1,1,1,1,1,1]},"reasoning_shift":[{"model":"Gemini","from":"2026-07-14","to":"2026-07-15","added":[{"t":"vast registry of community-maintained rules","q":"a vast registry of community-maintained rules"}],"dropped":[{"t":"run custom checks within CI/CD","q":"run them inline within CI/CD"}]},{"model":"Claude","from":"2026-07-09","to":"2026-07-14","added":[{"t":"Low false positives","q":"false-positive rates are low"},{"t":"CodeQL depth comparison","q":"Semgrep wins on ease and speed, CodeQL on analysis depth"},{"t":"License tightening hurts OSS","q":"the 2024 license tightening (which spawned the Opengrep fork) makes it a weaker pick for strictly-OSS shops"}],"dropped":[{"t":"Supply-chain and secrets coverage","q":"supply-chain/secrets coverage in one platform"},{"t":"Large polyglot accuracy gap","q":"Deepen interprocedural taint analysis accuracy on large polyglot codebases to fully match legacy enterprise engines"}]}],"api":"https://modelsagree.com/api/v1/best/best-sast-tool-for-application-security.json"},{"slug":"best-sast-tool-for-ci-pipelines","title":"Best SAST tool for CI pipelines","rank":1,"of":5,"score":20,"appearances":4,"modelRanks":{"ChatGPT":1,"Claude":1,"Gemini":1,"Grok":1},"reason":"Fast CI scans, excellent developer feedback, 35+ languages, easy custom rules, and strong cross-file analysis make it the best overall balance of detection, workflow fit, and value; near-tied with CodeQL, but easier for typical teams to tune and extend","reasons":[{"model":"ChatGPT","reason":"Fast CI scans, excellent developer feedback, 35+ languages, easy custom rules, and strong cross-file analysis make it the best overall balance of detection, workflow fit, and value; near-tied with CodeQL, but easier for typical teams to tune and extend"},{"model":"Claude","reason":"Fast, dependency-free scans (minutes, often seconds) that fit PR-time CI without babysitting; readable YAML rules let teams encode their own policies instead of waiting on a vendor; strong OSS core with a generous free tier, and the commercial tier adds cross-file dataflow and decent triage. Best default for the typical engineering team wiring SAST into GitHub Actions/GitLab CI."},{"model":"Gemini","reason":"Extremely fast scan execution engineered for rapid PR blocking in CI/CD pipelines, paired with an accessible rule syntax that allows developers to write custom security checks easily; near-tie with SonarQube based on CI agility."},{"model":"Grok","reason":"Blazing-fast local scans (seconds on PRs), excellent CI/CD integration (GitHub Actions, GitLab, Jenkins, etc.) with minimal overhead, highly customizable rules (YAML, community-driven), strong accuracy with low false positives for typical use, free core/open-source option scales well, broad language support (~40+), ideal for developer-centric pipelines without heavy vendor lock-in"}],"fixes":[{"model":"ChatGPT","fix":"Its strongest cross-file engine and security rules are proprietary, and serious multi-repository use becomes contributor-priced"},{"model":"Claude","fix":"Cross-file/interprocedural taint analysis is gated behind the paid product; OSS-only users get mostly intra-file findings and shallower coverage on complex injection chains than CodeQL."},{"model":"Gemini","fix":"Lacks deep cross-file global dataflow and complex inter-procedural taint analysis compared to heavy semantic engines."},{"model":"Grok","fix":"Requires rule expertise for advanced depth; may lack some enterprise taint analysis or binary scanning out-of-box (not for teams needing fully managed deep enterprise compliance without customization)."}],"updated":"2026-07-19","api":"https://modelsagree.com/api/v1/best/best-sast-tool-for-ci-pipelines.json"},{"slug":"best-sast-tools-for-polyglot-monorepos","title":"Best SAST tools for polyglot monorepos","rank":1,"of":7,"score":15,"appearances":3,"modelRanks":{"ChatGPT":1,"Claude":1,"Gemini":1},"reason":"Best overall balance for polyglot monorepos: fast differential scans, 30+ languages, strong framework-aware and cross-file analysis, excellent custom-rule ergonomics, and developer-friendly CI/PR feedback.","reasons":[{"model":"ChatGPT","reason":"Best overall balance for polyglot monorepos: fast differential scans, 30+ languages, strong framework-aware and cross-file analysis, excellent custom-rule ergonomics, and developer-friendly CI/PR feedback."},{"model":"Claude","reason":"Best fit for polyglot monorepos on real merit — 30+ languages under one rule syntax, fast per-file scanning that parallelizes cleanly in monorepo CI, cross-file/cross-function taint analysis in the Pro engine, and rules-as-code that lives in the repo so security and dev teams iterate like on any other code; the open-source engine alone is genuinely useful, and the commercial tier adds dataflow depth without changing workflow. Assumption: the typical practitioner values low false-positive rates and diff-aware CI speed over maximal rule breadth."},{"model":"Gemini","reason":"Fast, build-free AST-based scanning that allows near-instant PR-level feedback. In a near-tie with Snyk Code for developer velocity, Semgrep wins on its open-source core and the ease of writing custom rules for proprietary internal APIs. It natively supports logical subdirectory splitting and diff-aware scanning to prevent CI bottlenecks."}],"fixes":[{"model":"ChatGPT","fix":"Its strongest low-noise, interfile capabilities and managed monorepo features require the commercial platform; Community Edition alone is less comprehensive."},{"model":"Claude","fix":"The deepest interprocedural/cross-file analysis is gated behind the paid Pro engine, and its 2024 license change limits how the community edition's rules can be used in competing products — pure-OSS shops get a meaningfully shallower tool."},{"model":"Gemini","fix":"Lacks deep inter-procedural taint analysis across directory boundaries or multiple services, making it less effective at tracing complex data flows."}],"updated":"2026-07-17","api":"https://modelsagree.com/api/v1/best/best-sast-tools-for-polyglot-monorepos.json"},{"slug":"best-ai-code-review-tools-for-finding-security-vulnerabilities","title":"Best AI code review tools for finding security vulnerabilities","rank":3,"of":8,"score":11,"appearances":3,"modelRanks":{"ChatGPT":1,"Claude":3,"Gemini":3},"reason":"Best overall balance of fast customizable SAST, cross-file dataflow, AI-assisted detection, triage and remediation, with strong PR integration and an open-source local engine; especially valuable when teams will tune rules to their codebase.","reasons":[{"model":"ChatGPT","reason":"Best overall balance of fast customizable SAST, cross-file dataflow, AI-assisted detection, triage and remediation, with strong PR integration and an open-source local engine; especially valuable when teams will tune rules to their codebase."},{"model":"Claude","reason":"Open-source core, transparent and writable rules, very fast, huge community ruleset, and the AI Assistant now auto-triages/deduplicates findings and drafts fixes to cut false positives — the best value and customizability for security teams that want control."},{"model":"Gemini","reason":"Merges fast, lightweight AST static analysis rules with LLM triage to automatically validate alerts, filter out false positives, and explain exploit paths."}],"fixes":[{"model":"ChatGPT","fix":"Its deepest analysis and AI features are commercial, and detection quality still depends heavily on rule coverage and tuning."},{"model":"Claude","fix":"Pattern-first design misses complex cross-function/cross-file taint flows; deep interprocedural dataflow is gated behind the paid Pro engine."},{"model":"Gemini","fix":"Advanced AI triage capabilities and cross-file dataflow analysis require commercial tier subscriptions."}],"updated":"2026-08-08","api":"https://modelsagree.com/api/v1/best/best-ai-code-review-tools-for-finding-security-vulnerabilities.json"},{"slug":"best-ai-code-security-scanner","title":"Best AI code security scanner","rank":3,"of":8,"score":9,"appearances":3,"modelRanks":{"Claude":2,"Gemini":4,"Grok":3},"reason":"Best engine-plus-AI pairing that works everywhere — fast, low-noise SAST with writable rules and an open-source core, while Semgrep Assistant uses AI to auto-triage false positives, explain findings, and propose fixes in the PR, with published data showing large noise reduction; the strongest choice for teams that want control and cross-SCM support.","reasons":[{"model":"Claude","reason":"Best engine-plus-AI pairing that works everywhere — fast, low-noise SAST with writable rules and an open-source core, while Semgrep Assistant uses AI to auto-triage false positives, explain findings, and propose fixes in the PR, with published data showing large noise reduction; the strongest choice for teams that want control and cross-SCM support."},{"model":"Grok","reason":"Highly customizable open-source core with fast scans and AI-assisted contextual fixes in PRs; strong for custom rules + supply chain; excellent balance of speed, accuracy, and control for security-conscious teams; transparent and extensible for real-world tuning."},{"model":"Gemini","reason":"Combines fast static analysis and Semgrep Assistant to allow security teams to write highly customized rules and automatically generate contextual PR-native fixes."}],"fixes":[{"model":"Claude","fix":"The AI layer (Assistant, autofix) is paid-tier and cloud-connected, and its interprocedural/dataflow depth still trails CodeQL in some languages — pure open-source users get the scanner but not the AI fixing."},{"model":"Gemini","fix":"Requires significant manual policy tuning and custom rule creation to prevent generating noise and low-quality autofix suggestions."},{"model":"Grok","fix":"AI autofix in beta/less mature than leaders for some languages; requires more setup for full auto-PR creation compared to native tools."}],"updated":"2026-07-15","rank_history":{"days":["2026-07-13","2026-07-15"],"ranks":[3,3]},"api":"https://modelsagree.com/api/v1/best/best-ai-code-security-scanner.json"},{"slug":"best-infrastructure-as-code-security-scanners-for-ci-pipelines","title":"Best infrastructure-as-code security scanners for CI pipelines","rank":7,"of":7,"score":1,"appearances":1,"modelRanks":{"Gemini":5},"reason":"High-performance pattern-matching engine that uses simple YAML syntax to allow teams to define custom IaC guardrails quickly and with exceptionally low false-positive rates.","reasons":[{"model":"Gemini","reason":"High-performance pattern-matching engine that uses simple YAML syntax to allow teams to define custom IaC guardrails quickly and with exceptionally low false-positive rates."}],"fixes":[{"model":"Gemini","fix":"Out-of-the-box rule coverage for complex multi-resource relationships is weak compared to dedicated graph-based scanners, requiring significant manual rule-writing."}],"updated":"2026-07-18","rank_history":{"days":["2026-07-17","2026-07-18"],"ranks":[6,null]},"api":"https://modelsagree.com/api/v1/best/best-infrastructure-as-code-security-scanners-for-ci-pipelines.json"}],"page":"https://modelsagree.com/product/semgrep","check":"https://modelsagree.com/check?q=Semgrep","updated":"2026-08-10T18:18:45.051Z","attribution":"modelsagree.com, CC BY 4.0"}