Head-to-Head Comparison
AI-native AppSec — AI-native AppSec platform combining SAST, SCA, Secrets, and IaC scanning
| Capability | DryRun Security | ZeroPath | 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; built from scratch on LLMs+AST; Tree-of-Thoughts + ReAct framework |
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) |
✓ 50%+ of critical findings are business logic flaws; auth bypasses, BOLA, race conditions |
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 |
✓ Cross-file/repo data flow; AST-based call graph with enriched annotations; code semantics |
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 |
✓ Broad via unified SAST+SCA+Secrets+IaC engine; 35+ languages |
Tie |
| Git Behavioral Analysis | ✓ Git Behavioral Graphs: code churn, temporal coupling, knowledge decay, temporal anomalies, intent mining |
✗ | DryRun leads |
| Natural Language Policies | ✓ Natural Language Code Policies (NLCP); Policy Library with 16+ pre-built policies; Custom Policy Agent enforces on every PR |
✓ Custom rules via plain English; core differentiator |
Tie |
| False Positive Reduction | ✓ 90% lower noise; CSA-driven reasoning; Risk Register dismissal with fingerprinting suppresses FPs in future scans |
✓ 75%+ FP reduction; 5,000→127 findings typical example |
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 |
✓ Purpose-built solution for AI-generated code; Tree-of-Thoughts reasoning |
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 |
✓ Open-source MCP server (March 2025); compatible with Claude, Cursor, Windsurf |
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 |
✗ | DryRun leads |
| 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 |
✗ | 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 |
✓ AST-based call graph with enriched annotations; org-specific pattern learning |
Tie |
| Model-Independent Verification | ✓ Separates code generation from code verification; works regardless of which AI model or human generates code |
✗ | 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 |
~ Risk management view; continuous monitoring across 300K+ scans/month |
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-native; LLM+AST engine (not Semgrep-based); Tree-of-Thoughts + ReAct; 35+ languages |
Tie |
| DAST (Dynamic Analysis) | ✗ | ✗ | Tie |
| SCA (Dependency / Supply Chain) | ✓ SCA agent with dependency and supply chain analysis; Risk Register tracks SCA findings by severity |
✓ Reachability-based SCA; AI-assessed CVSSv4; 35+ ecosystems |
Tie |
| Secrets Detection | ✓ AI-native secrets analyzer; detects obfuscated secrets (concatenation, base64, logging); hard-coded credentials policy in Policy Library |
✓ 700+ secret patterns; historical git scanning; automated remediation |
Tie |
| IaC Scanning | ✓ IaC scanning (Terraform, YAML, and infrastructure-as-code analysis) |
✓ Terraform, CloudFormation, K8s, Helm, ARM; 500+ policies |
Tie |
| Container Scanning | ✗ | ~ SCA covers Docker/OCI manifests and EOL tracking. No explicit image-layer CVE scanning. |
Competitor leads |
| 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 |
✓ Context-aware auto-fix PRs; imports and auto-fixes findings from 7+ external tools |
Tie |
| Fix Verification / Re-testing | ✓ Re-runs DryRun Security analysis after remediation is applied to verify the fix resolves the finding |
~ Patches compiled and unit tested before push. No runtime re-test of running application. |
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 triage with priority scoring and status management |
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 |
✓ Sub-60 second PR scans; GitHub, GitLab, Bitbucket, Azure DevOps |
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 |
✓ Fleet-wide repo scanning; zero config; 300K+ scans/month |
Tie |
| IDE Integration | ✓ DryRun Insights MCP integrates with VS Code, Cursor, Windsurf, Claude Code, and Codex for security-aware coding assistance |
✗ No VS Code or JetBrains plugin. MCP gives IDE-adjacent functionality but not native extension. |
DryRun leads |
| CI/CD Integration | ✓ GitHub and GitLab native integration; webhook notifications (Slack + generic) |
✓ GitHub, GitLab, Bitbucket, Azure DevOps CI/CD integration |
Tie |
| SCM Support | GitHub and GitLab (native apps with OAuth) | GitHub, GitLab, Bitbucket, Azure DevOps | Tie |
| Coverage2 | |||
| Language Support | ✓ 15+ languages optimized: Python, JS/TS, Ruby, Go, C#, Java, Kotlin, PHP, Swift, Elixir, HTML, IaC (Terraform, YAML) |
✓ 35+ languages; custom LLM+AST engine |
Tie |
| Out-of-Box Accuracy (No Tuning) | ✓ 88% detection rate OOTB; 2x more accurate than nearest competitor in independent testing |
~ Zero config; improves over time with org-specific learning |
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 |
~ Risk management view; findings dashboard |
DryRun leads |
| Compliance / Audit Readiness | ~ Audit-ready reporting; policy enforcement evidence; structured finding dismissals with reasons and context |
✓ SOC 2 certified; ISO 27001 underway; compliance violation detection |
Competitor leads |
| SBOM / AI-BOM Generation | ✓ DeepScan generates SBOM; SCA agent provides dependency inventory and license checking (Dependency License Check policy) |
✓ SBOM generation; SCA dependency inventory |
Tie |
| 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) |
✓ Multi-agent engine; Auto AppSec Mode; custom AI agents per scan type |
Tie |
| API / Extensibility | ✓ DryRun Simple API (REST); Swagger/OpenAPI spec; webhook integrations (Slack + generic); MCP server |
~ API available; webhook integrations |
DryRun leads |
| 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 AppSec platform: unified SAST + SCA + Secrets + IaC (RSA 2026 Innovation Sandbox Top 10; 1,000+ orgs) |
— |
| 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 170 verified issues in curl; RSA 2026 Innovation Sandbox Top 10 finalist; unique third-party SAST orchestration importing findings from 7+ tools |
— |
| Market Feedback (G2)4 | |||
| G2 Rating / Review Count | ℹ 4.9/5 (19 reviews) — g2.com/products/dryrun-security/reviews |
ℹ 4.4/5 (10 reviews) — g2.com/products/zeropath/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 "I was able to find critical vulnerabilities immediately" — noted for fast time-to-value (g2.com/products/zeropath/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 "The UI is a little hard to understand and takes some time getting used to." (g2.com/products/zeropath/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 UI learning curve; limited enterprise integrations (g2.com/products/zeropath/reviews) |
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