Head-to-Head Comparison
DryRun Security vs Qwiet AI
Qwiet AI is now Harness SAST and SCA. Evaluate the current product alongside DryRun using representative code, a security requirement and a repair. DryRun combines automated adversarial review with retained application context, configured source-control checks and guidance for supported coding agents, followed by review of the changed code.
CPG-based SAST + SCA — CPG-based SAST + SCA platform (acquired by Harness); IEEE award-winning Code Property Graph; 97% TPR claimed
14
DryRun Leads
6
Tie
1
Qwiet AI Leads
21
Capabilities Compared
| Capability | DryRun Security | Qwiet AI | Verdict |
|---|---|---|---|
| Detection Categories1 | |||
| What this tool covers | ℹ | ℹ | — |
| AI & Intelligence9 | |||
| AI-Native Architecture | ✓ | ~ | DryRun leads |
| Agentic / Multi-Agent System | ✓ PR review and repository investigations use specialized security agents and evaluations. Source |
~ AutoFix documentation describes collaborating agents for threat analysis, testing, remediation, dependencies and review. Source |
DryRun leads |
| Natural Language Policies | ✓ | ✗ Rules and policies defined via YAML/Policy Studio, not natural language. |
DryRun leads |
| Model-Independent Verification | ✓ DryRun security evaluation is separate from developer or supported coding-agent repair. Changed code receives fresh review. Source |
~ | DryRun leads |
| Code Security Knowledge Graph | ✓ PR reviews and DeepScan both build and use the DryRun Security Context Graph. |
✓ Documents a Code Property Graph representing program syntax, control flow and data flow for security analysis. 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 | ✓ | ✗ — |
DryRun leads |
| 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 |
~ | 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 |
✗ Standard ASPM views; 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 |
✗ Notable gap vs. competitors; no MCP server. |
DryRun leads |
| Continuous Enforcement Layer | ✓ Configured PR findings fail checks; required source-control protections enforce the customer’s merge policy. Source |
✓ | Tie |
| Per-Review Economics (predictable vs. usage-metered) | ✓ Flat subscription pricing based on team size. Usage pricing applies to DeepScan product. |
✓ | Tie |
| Code Security Intelligence3 | |||
| Business Logic Flaw Detection | ✓ Investigates authorization and business-logic vulnerabilities such as IDOR and tenant-isolation failures. Source |
~ Account-enabled AI SAST documents IDOR checks and exploitability analysis; AI Findings must be enabled for scans. Source |
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 |
✓ | Tie |
| Workflow & Supply Chain2 | |||
| SCM Support | ✓ GitHub and GitLab (native apps with OAuth) |
✓ | Tie |
| SBOM / AI-BOM Generation | ✓ | ✓ Generates application dependency SBOMs with CycloneDX and SPDX export; VEX export is also documented. Source |
Tie |
| Reporting & Compliance1 | |||
| Compliance Framework Mapping (SOC 2, PCI, NIST, OWASP, MISRA, STIG) | ~ | ✓ Exports OWASP and CWE reports, plus PCI DSS reports scoped to application-security requirements. Source |
Competitor leads |
| Market Feedback (G2)4 | |||
| G2 Rating / Review Count | ℹ 4.9/5 (19 reviews) — g2.com/products/dryrun-security/reviews |
ℹ | — |
| 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 Brooks S. praised CI/CD documentation and responsive support (G2, September 19, 2024). Source |
— |
| 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 Brooks S., CEO, criticized CLI-only custom-policy configuration (G2, September 19, 2024). Source |
— |
| Common G2 Complaint Themes | ℹ UI/portal speed; desire for more analyzer customization (g2.com/products/dryrun-security/reviews) |
ℹ Three 2023–2024 reviews mention policy/UI configuration limits and reporting gaps; this small historical sample does not establish current prevalence. Source |
— |
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