Head-to-Head Comparison
DryRun Security vs DepthFirst
For a team evaluating depthfirst, start with the code review workflow you need. DryRun performs automated adversarial review in configured pull request workflows, while PR reviews and DeepScan build and use application context. Compare the relevant modules, policy controls and remediation connections.
depthfirst markets separate modules for code security review, supply-chain analysis and runtime testing. Source 1 · Source 2 · Source 3 · Source 4
15
DryRun Leads
6
Tie
0
DepthFirst Leads
21
Capabilities Compared
| Capability | DryRun Security | DepthFirst | Verdict |
|---|---|---|---|
| Detection Categories1 | |||
| What this tool covers | ℹ | ℹ | — |
| AI & Intelligence9 | |||
| AI-Native Architecture | ✓ | ✓ Vendor-trained model inside an AI scanning pipeline. Marketed as model-agnostic. |
Tie |
| Agentic / Multi-Agent System | ✓ PR review and repository investigations use specialized security agents and evaluations. Source |
~ Claims multi-agent; implementation details not public |
DryRun leads |
| Natural Language Policies | ✓ | ✗ Not offered. Platform uses AI reasoning, not policy-driven rules. |
DryRun leads |
| Model-Independent Verification | ✓ DryRun security evaluation is separate from developer or supported coding-agent repair. Changed code receives fresh review. Source |
✓ | Tie |
| Code Security Knowledge Graph | ✓ PR reviews and DeepScan both build and use the DryRun Security Context Graph. |
✓ depthfirst describes its Component Graph as mapping application data flows, services and dependencies. Source |
Tie |
| 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 | ✓ | ✓ depthfirst announced dfs-large1 as a security-post-trained model in preview in July 2026. Source |
Tie |
| Multi-model Architecture | ✓ Routes each task to the best-fit model rather than relying on a single LLM. |
✗ — |
DryRun leads |
| AI Coding Agent Security6 | |||
| Securing AI-Generated Code | ✓ Reviews human- and AI-written code in connected, configured workflows. Source |
~ Scans AI-generated code; no dedicated AI-code-review 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 |
✗ Scan results only; no AI-coding observability. |
DryRun leads |
| 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 |
✗ No dedicated AI-agent skill scanning. |
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 |
✗ Not offered. |
DryRun leads |
| Continuous Enforcement Layer | ✓ Configured PR findings fail checks; required source-control protections enforce the customer’s merge policy. Source |
✓ PR-time scanning with auto-fix. |
Tie |
| Per-Review Economics (predictable vs. usage-metered) | ✓ Flat subscription pricing based on team size. Usage pricing applies to DeepScan product. |
✓ Subscription pricing. |
Tie |
| Code Security Intelligence3 | |||
| Business Logic Flaw Detection | ✓ Investigates authorization and business-logic vulnerabilities such as IDOR and tenant-isolation failures. Source |
~ Marketed as attacker-style reasoning for IDOR and auth bypass |
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 |
~ Security analytics; burn-down tracking; time-to-remediate |
DryRun leads |
| Workflow & Supply Chain2 | |||
| SCM Support | ✓ GitHub and GitLab (native apps with OAuth) |
~ GitHub (primary); limited other SCM support |
DryRun leads |
| SBOM / AI-BOM Generation | ✓ | ✗ Not offered. |
DryRun leads |
| Reporting & Compliance1 | |||
| Compliance Framework Mapping (SOC 2, PCI, NIST, OWASP, MISRA, STIG) | ~ | ✗ No dedicated compliance reporting. |
DryRun leads |
| Market Feedback (G2)4 | |||
| G2 Rating / Review Count | ℹ 4.9/5 (19 reviews) — g2.com/products/dryrun-security/reviews |
ℹ No G2 reviews |
— |
| 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 No G2 reviews available |
— |
| 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 No G2 reviews available |
— |
| Common G2 Complaint Themes | ℹ UI/portal speed; desire for more analyzer customization (g2.com/products/dryrun-security/reviews) |
ℹ Too new for G2 feedback |
— |
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