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Head-to-Head Comparison

DryRun Security vs Snyk Evo

Compare Snyk Evo and DryRun against the security work your team needs today. Check the product, access level and release stage behind each capability. DryRun provides automated adversarial review of code changes, application context, configured merge controls and repair guidance for supported coding agents.

Agentic AI Security Orchestration — Agentic AI security orchestration purpose-built for AI-native applications

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Compare with: Snyk Code Snyk Evo GHAS Claude Security Codex ZeroPath DepthFirst Corgea Aikido Semgrep Sonar Corridor OX Security Qwiet AI Socket Wiz Code
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14
DryRun Leads
7
Tie
0
Snyk Evo Leads
21
Capabilities Compared
Capability DryRun Security Snyk Evo Verdict
Detection Categories1
What this tool covers ℹ
PR and repository security review, dependency analysis, secrets analysis and Terraform IaC review. Active-secret verification is attempted where supported. Source 1 · Source 2 · Source 3 · Source 4 · Source 5
 ℹ
Evo includes AI-SPM, Agentic Development Security and Continuous Offensive Security. New Agentic AppSec code-scanning and repository-review agents are experimental preview; remediation is open preview. Source 1 · Source 2 · Source 3 · Source 4
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AI & Intelligence9
AI-Native Architecture ✓
Automated adversarial review combines security agents, application context and deterministic analysis. Source 1 · Source 2
 ~
Snyk describes Evo as combining model reasoning with its security engines; Agentic AppSec functions have distinct preview access. Source 1 · Source 2
 DryRun leads
Agentic / Multi-Agent System ✓
PR review and repository investigations use specialized security agents and evaluations. Source
 ~
Discovery, policy and risk agents coordinate tasks; COS supports agentic pentesting. New code-scanning and repository-review agents are experimental preview for selected customers. Source 1 · Source 2 · Source 3
 DryRun leads
Natural Language Policies ✓
Natural-language requirements are evaluated against code context; configured findings can fail required source-control checks. Source 1 · Source 2
 ~
Natural-language requests create attribute-based AI asset policies, with human approval of policy changes. Source
 DryRun leads
Model-Independent Verification ✓
DryRun security evaluation is separate from developer or supported coding-agent repair. Changed code receives fresh review. Source
 ✗
AI-SPM inventories AI assets; no independent verification of AI-generated code.
 DryRun leads
Code Security Knowledge Graph ✓
PR reviews and DeepScan both build and use the DryRun Security Context Graph.
 ✗
No formal code security knowledge graph. AI-BOM provides inventory, not a knowledge graph.
 DryRun leads
Cross-repo Analysis ✓
DryRun looks locally first and, when needed, automatically investigates relevant context, such as authorization logic, across repositories it has permission to access.
 ✗
—
 DryRun leads
Code Security Memory ✓
Retained application context and feedback inform later investigations; changed code receives fresh review. Scanner-excluded candidates and human dismissals are distinct records. Source
 ✗
—
 DryRun leads
Custom DryRun Cyber Models ✓
DryRun reports training and optimizing models for security analysis, including a security-finding classifier. Source 1 · Source 2
 ✗
—
 DryRun leads
Multi-model Architecture ✓
Routes each task to the best-fit model rather than relying on a single LLM.
 ✓
Snyk describes Continuous Offensive Security as using multiple model types and a separate validation model. Source 1 · Source 2
 Tie
AI Coding Agent Security6
Securing AI-Generated Code ✓
Reviews human- and AI-written code in connected, configured workflows. Source
 ~
ADS and Snyk Studio trigger checks of agent-generated code in supported coding workflows. Source
 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
 ✓
ADS observes supported agent sessions and component use, alongside AI asset inventory; session retention is seven days. Source
 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 Supply Chain Security assesses supported skills for malicious behavior and other risks; discovery-only components are not security-assessed. Source
 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
 ~
The hosted Evo MCP server exposes inventory, relationships, issues and selected policy tools to authorized assistants. Source
 DryRun leads
Continuous Enforcement Layer ✓
Configured PR findings fail checks; required source-control protections enforce the customer’s merge policy. Source
 ✓
Configured ADS policies can govern agent actions before execution in supported coding-agent workflows. Source 1 · Source 2
 Tie
Per-Review Economics (predictable vs. usage-metered) ✓
Flat subscription pricing based on team size. Usage pricing applies to DeepScan product.
 ~
Enterprise credits cover AI-SPM by contributor-day, coding-agent security by machine-day, and COS pentesting by assessment. Source
 DryRun leads
Code Security Intelligence3
Business Logic Flaw Detection ✓
Investigates authorization and business-logic vulnerabilities such as IDOR and tenant-isolation failures. Source
 ✗
Covers AI prompt injection; not traditional business logic
 DryRun leads
Git Behavioral Analysis ✓
DeepScan uses Git Behavioral Graphs for churn, temporal coupling, knowledge decay, anomalies and intent analysis. Source
 ✗
Not available
 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
Workflow & Supply Chain2
SCM Support ✓
GitHub and GitLab (native apps with OAuth)
 ✓
Evo imports repositories through supported Snyk Workspaces integrations or CLI uploads; SCM and feature support vary. Source 1 · Source 2
 Tie
SBOM / AI-BOM Generation ✓
Provides dependency SBOMs and an AI-BOM inventory. Source 1 · Source 2
 ✓
The AI-BOM CLI generates CycloneDX 1.6 JSON inventories of supported AI components and relationships. Source 1 · Source 2
 Tie
Reporting & Compliance1
Compliance Framework Mapping (SOC 2, PCI, NIST, OWASP, MISRA, STIG) ~
Findings and reporting include CWE/OWASP context and evidence useful to compliance review. Source 1 · Source 2
 ~
AI risk maps to OWASP LLM and Agentic guidance, MITRE ATLAS, and NIST AI taxonomies. Source
 Tie
Market Feedback (G2)4
G2 Rating / Review Count ℹ
4.9/5 (19 reviews) — g2.com/products/dryrun-security/reviews
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G2 lists Snyk Evo AI-SPM separately with zero reviews; no aggregate rating is available. Source
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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)
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The separate Snyk Evo AI-SPM G2 listing has no reviews from which to attribute praise. Source
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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)
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The separate Snyk Evo AI-SPM G2 listing has no reviews from which to attribute criticism. Source
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Common G2 Complaint Themes ℹ
UI/portal speed; desire for more analyzer customization (g2.com/products/dryrun-security/reviews)
 —
No review themes are available from the zero-review Snyk Evo AI-SPM G2 listing. Source
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G2 High Performer — SAST Spring 2026