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product
Data quality: Editorially Reviewed
Language (LLM / NLP)
CLI / IDE plugin
AI Coding Assistants
Subscription
Software & technology
Self-hosted / on-premises
Predictive / classical ML
Vulnerability management
Freemium
Application & software supply chain security
SaaS (vendor-hosted)
Developer tool
Enterprise / custom quote

Semgrep

AI Coding Assistants

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Overview

Semgrep is a static application security testing platform that supports SAST, software composition analysis, and secrets scanning by combining rule-based pattern matching with AI-based reasoning to reduce false positives. Semgrep Assistant uses AI to analyze vulnerabilities, learn from team decisions, reduce up to 60% of false positives, and recommend remediation steps. The platform scans source code across dozens of programming languages for OWASP-related vulnerabilities, business-logic flaws, and authorization issues, integrating with CI/CD pipelines and developer IDEs.

Pricing model
Freemium
Deployment
SaaS (vendor-hosted), CLI / IDE plugin, Self-hosted / on-premises
Regions served
Global
Categories
Language (LLM / NLP), CLI / IDE plugin, AI Coding Assistants, Subscription, Software & technology, Self-hosted / on-premises, Predictive / classical ML, Vulnerability management, Freemium, Application & software supply chain security, SaaS (vendor-hosted), Developer tool, Enterprise / custom quote
Last updated
2 October 2026
Published
2 October 2026

Use cases

Application & software supply chain security
Vulnerability management

Deployment options

SaaS (vendor-hosted)
CLI / IDE plugin
Self-hosted / on-premises

Data sources & provenance

Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.

Data quality
Data quality: Editorially Reviewed
Primary source
semgrep.dev
Sources cited
2
Last reviewed
27 September 2026
Last updated
2 October 2026

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Anyone can suggest a correction — you don't need an account. An editor checks every suggestion against the sources before the record changes.