Head-to-Head Comparison
AI-native Codebase Scanner — AI-native codebase security scanner built into Claude Code, limited research preview (Feb 2026)
| Capability | DryRun Security | Claude Code | Verdict |
|---|---|---|---|
| AI & Intelligence7 | |||
| AI-Native Architecture | ✓ AI-native since 2023; model-independent; multi-agent agentic system (Code Review Agent, DeepScan Agent, Custom Policy Agent, Codebase Insight Agent) |
✓ AI-native; uses Claude Opus 4.6 for multi-stage reasoning |
Tie |
| Business Logic Flaw Detection | ✓ IDOR, broken auth, multi-tenant isolation, logic flaws, mass assignment, privilege escalation, TOCTOU race conditions, OAuth failures, WebSocket auth bypass; 88% detection OOTB; outperformed 5 leading SAST tools (2025 SAST Accuracy Report) |
✓ Broken auth, multi-step injection chains, logic flaws; 500+ zero-days found in OSS (expert-guided) |
Tie |
| Contextual / Semantic Code Analysis | ✓ Contextual Security Analysis (CSA): data flow, architecture, change history, intent, exploitability; detects issues pattern-based SAST cannot — middleware defined but not mounted, trust boundary misalignment, config not wired up; reads AGENTS.md |
✓ Reasons across full codebase like a human security researcher; multi-file context |
Tie |
| Vulnerability Coverage Breadth | ✓ 48+ vulnerability categories: SQLi, XSS, SSRF, IDOR, RCE, auth bypass, CSRF, XXE, path traversal, prompt injection, LLM tool misuse, OAuth failures, TOCTOU, WebSocket auth bypass, and more |
~ Opportunistic, sampling-based. Not exhaustive. SonarSource: 'coverage not guaranteed.' |
DryRun leads |
| Git Behavioral Analysis | ✓ Git Behavioral Graphs: code churn, temporal coupling, knowledge decay, temporal anomalies, intent mining |
✓ Reads Git history to find vulnerability variants across commit history |
Tie |
| Natural Language Policies | ✓ Natural Language Code Policies (NLCP); Policy Library with 16+ pre-built policies; Custom Policy Agent enforces on every PR |
~ CLAUDE.md and .github/security-scan-rules.txt provide NL policy-like functionality. Not a formal engine. |
DryRun leads |
| False Positive Reduction | ✓ 90% lower noise; CSA-driven reasoning; Risk Register dismissal with fingerprinting suppresses FPs in future scans |
✓ Multi-stage adversarial verification filters false positives; confidence + severity ratings |
Tie |
| AI Coding Agent Security6 | |||
| Securing AI-Generated Code | ✓ Reviews all code equally — human or AI-generated; model-independent verification layer; Agentic Coding Security Report (Mar 2026): 143 issues found across Claude/Codex/Gemini builds, 87% of PRs had vulns |
✓ Explicitly positioned for AI-generated code review; Agentic Coding Security analysis |
Tie |
| Malicious AI Agent Skill Detection | ✓ Policy Library includes Malicious AI Agent Skills Detection: flags skills/plugins that could enable data theft, backdoors, or code execution |
✗ | DryRun leads |
| MCP Integration | ✓ DryRun Insights MCP server: security summaries, PR analysis, trend monitoring, file-level history; connects via Direct HTTP, Claude Shortcuts, or mcp-remote |
✓ Native MCP support (Anthropic's own protocol) |
Tie |
| AI Coding Tool Integrations | ✓ Native integrations: Cursor, Codex, Claude Code, Windsurf, VS Code (via Insights MCP + Add Skill); reviews output of any AI tool via PR workflow |
✓ Built into Claude Code (Anthropic's own coding tool) |
Tie |
| AI Coding Visibility / Observability | ✓ Code Insights with AI Assistance (beta): NL queries for risk, trends, exposure; org-wide visibility; per-repo drill-down; file-level security history |
~ Dashboard with scan results and severity ratings |
DryRun leads |
| AI Red Teaming / Threat Modeling | ✗ | ✗ | Tie |
| Code Security Intelligence3 | |||
| Code Security Knowledge Graph | ✓ Accumulates organizational knowledge across PRs; cross-repo intelligence; learns risk tolerance from dismissal patterns (nitpicks, FPs, accepted risks); FP fingerprinting improves decision quality over time |
✗ | DryRun leads |
| Model-Independent Verification | ✓ Separates code generation from code verification; works regardless of which AI model or human generates code |
✗ (tied to Claude Opus 4.6) |
DryRun leads |
| Continuous Baseline & Risk Trending | ✓ Risk Register with Critical/High/Medium/Low severity; AI Assistance for Insights with NL queries, trend monitoring, and 30-day window analysis |
~ Dashboard with findings over time (limited preview) |
DryRun leads |
| Core Detection6 | |||
| SAST (Static Analysis) | ✓ AI-native Contextual Security Analysis engine; agentic multi-agent architecture; works on human and AI-generated code alike |
~ AI reasoning over code, not traditional SAST. Non-deterministic and sampling-based. SonarSource calls it complementary to SAST. |
DryRun leads |
| DAST (Dynamic Analysis) | ✗ | ✗ | Tie |
| SCA (Dependency / Supply Chain) | ✓ SCA agent with dependency and supply chain analysis; Risk Register tracks SCA findings by severity |
✗ | DryRun leads |
| Secrets Detection | ✓ AI-native secrets analyzer; detects obfuscated secrets (concatenation, base64, logging); hard-coded credentials policy in Policy Library |
~ Can identify hardcoded secrets during scan but not primary focus; prompt-driven via GitHub Actions |
DryRun leads |
| IaC Scanning | ✓ IaC scanning (Terraform, YAML, and infrastructure-as-code analysis) |
✗ | DryRun leads |
| Container Scanning | ✗ | ✗ | Tie |
| Remediation & Fixes3 | |||
| Auto-Fix / AI Remediation | ✓ Tessl remediation skill for AI coding tools: extracts finding, researches authoritative sources, applies context-grounded fixes in the developer's codebase; co-authored commits; works in Cursor, Claude Code, Codex, VS Code |
✓ Suggested patches in dashboard; human-in-the-loop approval required |
Tie |
| Fix Verification / Re-testing | ✓ Re-runs DryRun Security analysis after remediation is applied to verify the fix resolves the finding |
✗ | DryRun leads |
| Finding Dismissal & Triage Workflow | ✓ Risk Register with structured dismissal: Accepted Risk, False Positive, In Progress, Resolved, Won't Fix / Nitpick; learns risk tolerance of the repo and org from dismissal patterns (nitpicks, FPs, accepted risks); developer dismissal from PR comments (GitHub + GitLab) |
~ Basic dashboard review. No formal triage queue or ticketing integration. |
DryRun leads |
| Developer Workflow5 | |||
| PR / Merge Request Reviews | ✓ Every PR; real-time contextual feedback; pass/fail checks; inline explanations; reads AGENTS.md for project context |
✓ Dedicated security review GitHub Action; inline findings on PRs |
Tie |
| Full Repository / Deep Scan | ✓ DeepScan Agent: full-repo security review in hours; discovers root and nested AGENTS.md for context; findings flow to Risk Register |
✓ Full codebase scanning; found 500+ zero-days in open-source projects |
Tie |
| IDE Integration | ✓ DryRun Insights MCP integrates with VS Code, Cursor, Windsurf, Claude Code, and Codex for security-aware coding assistance |
~ CLI tool in terminal. No native IDE extension with sidebar/inline highlights. |
DryRun leads |
| CI/CD Integration | ✓ GitHub and GitLab native integration; webhook notifications (Slack + generic) |
✓ GitHub Actions CI/CD integration shipped |
Tie |
| SCM Support | GitHub and GitLab (native apps with OAuth) | GitHub only for PR reviews and CI/CD. | Tie |
| Coverage2 | |||
| Language Support | ✓ 15+ languages optimized: Python, JS/TS, Ruby, Go, C#, Java, Kotlin, PHP, Swift, Elixir, HTML, IaC (Terraform, YAML) |
✓ Broad language support via Claude Opus 4.6 (any language the model can reason about) |
Tie |
| Out-of-Box Accuracy (No Tuning) | ✓ 88% detection rate OOTB; 2x more accurate than nearest competitor in independent testing |
~ Expert-guided: strong. Naive: Checkmarx found 75% FP rate on large codebases. |
DryRun leads |
| Reporting & Compliance3 | |||
| Security Dashboard / Analytics | ✓ Risk Register (Critical/High/Medium/Low); AI Assistance for Insights with NL queries; Codebase Insight Agent; per-repo and file-level drill-down |
~ Dashboard with findings, confidence scores, and suggested patches (limited preview) |
DryRun leads |
| Compliance / Audit Readiness | ~ Audit-ready reporting; policy enforcement evidence; structured finding dismissals with reasons and context |
✗ Research preview; probabilistic results not suitable for compliance audits. |
DryRun leads |
| SBOM / AI-BOM Generation | ✓ DeepScan generates SBOM; SCA agent provides dependency inventory and license checking (Dependency License Check policy) |
✗ | DryRun leads |
| Architecture & Positioning4 | |||
| Agentic / Multi-Agent System | ✓ Code Review Agent, Custom Policy Agent, DeepScan Agent, Codebase Insight Agent + specialized sub-agents; AGENTS.md support (Linux Foundation) |
~ Single AI model (Claude Opus 4.6) with multi-stage pipeline; not multi-agent |
DryRun leads |
| API / Extensibility | ✓ DryRun Simple API (REST); Swagger/OpenAPI spec; webhook integrations (Slack + generic); MCP server |
✓ Claude API with full programmatic access |
Tie |
| Approach / Category | ℹ Code Security Intelligence: continuous, model-independent layer that understands, evaluates, and enforces code security for both human and AI-generated code; used to benchmark Claude, Codex, and Gemini security (Agentic Coding Security Report, Mar 2026) |
ℹ AI-native codebase security scanner built into Claude Code; limited research preview (Feb 2026); built on Claude Opus 4.6 |
— |
| Key Structural Differentiator | ℹ Durable knowledge graph + model-independent verification: accumulates proprietary data about code behavior, vuln patterns, and org risk posture; proven benchmarking tool for AI coding agent security (Agentic Coding Security Report, Mar 2026) |
ℹ Found 500+ zero-days in open-source projects (Ghostscript, OpenSC, CGIF); Claude-powered deep multi-stage reasoning; caused CrowdStrike -8% selloff on launch |
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| Market Feedback (G2)4 | |||
| G2 Rating / Review Count | ℹ 4.9/5 (19 reviews) — g2.com/products/dryrun-security/reviews |
ℹ 4.9/5 (22 reviews for Claude Code) — g2.com/products/anthropic-claude-code/reviews |
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| Notable G2 Praise (Attributed) | ℹ "DryRun goes far beyond what rule-based SAST tools offer. It catches things other tools completely miss — like middleware that's defined but never mounted, or trust boundary misalignments." — Jabez A., Director, Product Security Architecture, Enterprise (g2.com/products/dryrun-security/reviews) |
ℹ "Powerful AI coding assistant" — praised for general coding ability, security scanning too new for dedicated praise (g2.com/products/anthropic-claude-code/reviews) |
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| Notable G2 Criticisms (Attributed) | ℹ "I do somewhat wish there were more customization options for tuning the analyzers, but that seems to be in the works." — Kyle R. (g2.com/products/dryrun-security/reviews) |
ℹ "My tokens keep on running out and legacy models like opus 4.5 and sonnet 4.5 are not accessible anymore." (g2.com/products/anthropic-claude-code/reviews) |
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| Common G2 Complaint Themes | ℹ UI/portal speed; desire for more analyzer customization (g2.com/products/dryrun-security/reviews) |
ℹ Token consumption; CLI less polished than competitors; occasional inaccurate output (g2.com/products/anthropic-claude-code/reviews) |
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