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Checkmarx

Agentic AI-powered application security platform for the era of AI-generated code

Enterprise·All audiences·Powered by Anthropic·API available

Key strengths

Hybrid scanning combining rules-based precision with AI (Anthropic)Highest fidelity vulnerability detection (11% higher true-positive rate, 2.5x higher F1 score than average SAST tools)AI-powered security agents (Developer Assist, Triage & Remediation Assist)AI supply chain security (AI-BOM, LLM scanning, MCP scanning)Unified risk intelligence and ASPM across every attack surface800B+ lines of code analyzed monthlyGartner Magic Quadrant Leader and Forrester Wave Leader
Enterprise pricing
Ramat Gan, Israel
Founded 2006
Self-hostable

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Recent changes

  • Models updated: Anthropic
  • Plans updated: Four tiers: Essentials (core AppSec coverage), Professional (advanced + AI-powered), Enterprise (complete coverage & full compliance), and Start with SAST (for existing on-prem customers). All plans require a custom quote.
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Checkmarx — Technical Use Cases

1. High-Fidelity SAST at Scale Engineering and AppSec teams processing large codebases can leverage Checkmarx's hybrid scanning engine — combining rules-based precision with Anthropic AI — to achieve an 11% higher true-positive rate and 2.5x higher F1 score than average SAST tools. At 800B+ lines of code analyzed monthly across its customer base, the platform is proven at enterprise scale.

2. AI-Augmented Vulnerability Triage The Triage & Remediation Assist agent automates the classification and prioritization of findings, reducing analyst toil on false positives and surfacing actionable, high-confidence vulnerabilities for remediation.

3. Developer-Embedded Remediation Developer Assist integrates directly into IDE and PR workflows, providing contextual fix guidance at the point of coding and code review — shifting security left without disrupting developer velocity.

4. AI Supply Chain Security For teams building AI-native applications, Checkmarx provides AI-BOM generation, LLM component scanning, and MCP scanning to identify risks introduced through AI models, third-party LLM integrations, and Model Context Protocol servers.

5. Unified ASPM Across Attack Surfaces Security engineers and AppSec managers can consolidate risk intelligence across all scanning surfaces into a single posture management view, enabling prioritized remediation and compliance reporting.

6. MCP Server Security Native MCP Server integration allows security tooling to participate in AI-agent workflows, enabling security checks to be embedded within agentic development pipelines.

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