Head-to-Head Comparison
Agentic AI Security Orchestration — Agentic AI security orchestration purpose-built for AI-native applications
| Capability | DryRun Security | Snyk Evo | 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) |
~ Multi-agent orchestration layer built on top of legacy Snyk platform; not ground-up AI-native architecture |
DryRun leads |
| 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) |
~ Covers AI application logic (prompt injection) but not traditional business logic (IDOR, broken auth). |
DryRun leads |
| 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 |
✓ Discovery Agent builds live threat models from code; maps all AI models and MCPs |
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 |
— orchestration layer; depends on underlying scan engines |
DryRun leads |
| 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 |
✓ Policy Agent (GA) translates plain-English governance into CI/CD guardrails |
Tie |
| False Positive Reduction | ✓ 90% lower noise; CSA-driven reasoning; Risk Register dismissal with fingerprinting suppresses FPs in future scans |
✓ Contextual AI prioritization reduces noise |
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 |
✓ Core purpose of Evo AI-SPM is governing AI agents and securing AI-generated code. |
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 |
~ Agent Scan (Open Preview) governs MCP server and agent skill security. |
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 |
✓ Agent Scan (Open Preview) maps MCP servers and detects malicious tools/prompt-injection risks. Agent Guard (Private Preview) enforces guardrails on MCP tool calls. Neither is GA. |
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 |
✓ Snyk Studio embedded in AI coding workflows. Devin/Windsurf partnerships. |
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 |
✓ Discovery Agent maps all AI models, datasets, MCPs. AI-BOM provides comprehensive inventory. |
Tie |
| AI Red Teaming / Threat Modeling | ✗ | ~ Red Teaming Agent (Open Preview) + Threat Modeling Agent (Preview); neither confirmed GA at RSAC 2026 |
Competitor leads |
| 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 |
✗ No formal code security knowledge graph. AI-BOM provides inventory, not a knowledge graph. |
DryRun leads |
| 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 |
✓ Reporting Agent (GA) generates customizable insights; AI risk scoring across all agents |
Tie |
| Core Detection6 | |||
| SAST (Static Analysis) | ✓ AI-native Contextual Security Analysis engine; agentic multi-agent architecture; works on human and AI-generated code alike |
✓ Orchestrates Snyk Code SAST within broader agentic workflow |
Tie |
| DAST (Dynamic Analysis) | ✗ | ✓ API & Web Testing is GA as of RSAC 2026 (March 23, 2026) |
Competitor leads |
| SCA (Dependency / Supply Chain) | ✓ SCA agent with dependency and supply chain analysis; Risk Register tracks SCA findings by severity |
~ Via Snyk Open Source (separate product) |
DryRun leads |
| Secrets Detection | ✓ AI-native secrets analyzer; detects obfuscated secrets (concatenation, base64, logging); hard-coded credentials policy in Policy Library |
~ Via Snyk Code engine; not a standalone secrets tool |
DryRun leads |
| IaC Scanning | ✓ IaC scanning (Terraform, YAML, and infrastructure-as-code analysis) |
~ Via Snyk IaC (separate product) |
DryRun leads |
| Container Scanning | ✗ | ~ Via Snyk Container (separate product) |
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 |
~ Fix Agent not confirmed GA at RSAC 2026; only Discovery, Risk Intelligence, and Policy Agents confirmed GA |
DryRun leads |
| Fix Verification / Re-testing | ✓ Re-runs DryRun Security analysis after remediation is applied to verify the fix resolves the finding |
~ Agent Red Teaming (Open Preview) re-tests after Fix Agent PRs; not GA |
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) |
~ Via Snyk platform triage workflow |
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 |
✓ Fix Agent creates PRs; Policy Agent enforces security policies pre-merge |
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 |
✓ Discovery Agent scans across all repos for AI components and risk |
Tie |
| IDE Integration | ✓ DryRun Insights MCP integrates with VS Code, Cursor, Windsurf, Claude Code, and Codex for security-aware coding assistance |
✗ | DryRun leads |
| CI/CD Integration | ✓ GitHub and GitLab native integration; webhook notifications (Slack + generic) |
✓ Policy Agent executes natively during CI pipelines. |
Tie |
| SCM Support | GitHub and GitLab (native apps with OAuth) | Same as Snyk platform | Tie |
| Coverage2 | |||
| Language Support | ✓ 15+ languages optimized: Python, JS/TS, Ruby, Go, C#, Java, Kotlin, PHP, Swift, Elixir, HTML, IaC (Terraform, YAML) |
— orchestration layer |
DryRun leads |
| Out-of-Box Accuracy (No Tuning) | ✓ 88% detection rate OOTB; 2x more accurate than nearest competitor in independent testing |
— | 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 |
✓ Reporting Agent (GA) generates customizable insights across all agents. |
Tie |
| Compliance / Audit Readiness | ~ Audit-ready reporting; policy enforcement evidence; structured finding dismissals with reasons and context |
~ Policy Agent enforces compliance guardrails. AI Risk Registry tracks scores. |
Tie |
| SBOM / AI-BOM Generation | ✓ DeepScan generates SBOM; SCA agent provides dependency inventory and license checking (Dependency License Check policy) |
✓ AI-BOM is GA (Discovery Agent). CLI scans source code to detect AI components. |
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) |
✓ Explicitly a multi-agent system: Workflow Agent orchestrates Task Agents (Discovery, Risk, Policy, Fix, Reporting). |
Tie |
| API / Extensibility | ✓ DryRun Simple API (REST); Swagger/OpenAPI spec; webhook integrations (Slack + generic); MCP server |
~ Snyk REST API available. AI-BOM API documented. Broader API maturing. |
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 Agentic AI Security Posture Management (AI-SPM) for AI-native apps; GA at RSAC 2026 |
— |
| 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 Only product purpose-built for securing AI/agentic applications with full agent lifecycle (AI-BOM, red teaming, MCP scanning); GA at RSAC 2026 |
— |
| Market Feedback (G2)4 | |||
| G2 Rating / Review Count | ℹ 4.9/5 (19 reviews) — g2.com/products/dryrun-security/reviews |
— part of Snyk; no separate listing |
— |
| 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) |
— part of Snyk; no separate listing |
— |
| 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) |
— part of Snyk; no separate listing |
— |
| Common G2 Complaint Themes | ℹ UI/portal speed; desire for more analyzer customization (g2.com/products/dryrun-security/reviews) |
— part of Snyk |
— |
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