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Head-to-Head Comparison

DryRun Security vs Codex Security

For teams considering Codex Security, the decision includes how findings reach developers and how repaired code is checked. DryRun combines automated adversarial review with application context, customer-defined requirements and fresh review of changes made by developers or supported coding agents.

AI Security Agent — AI application security agent with threat modeling and sandbox exploit validation, research preview (Mar 2026)

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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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18
DryRun Leads
3
Tie
0
Codex Leads
21
Capabilities Compared
Capability DryRun Security Codex 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
Source-code security investigation with attempted execution validation and patch review. Source
 —
AI & Intelligence9
AI-Native Architecture ✓
Automated adversarial review combines security agents, application context and deterministic analysis. Source 1 · Source 2
 ✓
AI-based security investigation is available through Codex Security Cloud; local tooling is a separate surface. Source
 Tie
Agentic / Multi-Agent System ✓
PR review and repository investigations use specialized security agents and evaluations. Source
 ~
Single-agent autonomous pipeline (Aardvark-derived). Threat model → commit scan → sandbox validation → patch via Codex.
 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
 ~
Editable threat model acts as project-level customization — closer to configuration than a policy engine.
 DryRun leads
Model-Independent Verification ✓
DryRun security evaluation is separate from developer or supported coding-agent repair. Changed code receives fresh review. Source
 ~
Sandboxed PoC execution adds a non-model validation step
 DryRun leads
Code Security Knowledge Graph ✓
PR reviews and DeepScan both build and use the DryRun Security Context Graph.
 ~
Editable threat model captures entry points and trust boundaries
 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.
 ✗
—
 DryRun leads
AI Coding Agent Security6
Securing AI-Generated Code ✓
Reviews human- and AI-written code in connected, configured workflows. Source
 ✓
Investigates source-code vulnerabilities and proposes patches for review, with attempted sandbox validation. Source
 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
 ~
Finding tracking across commits; not 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 detection for malicious AI agent skills or plugins.
 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
 ~
MCP support in Codex agent; not a documented security-product integration
 DryRun leads
Continuous Enforcement Layer ✓
Configured PR findings fail checks; required source-control protections enforce the customer’s merge policy. Source
 ✗
Commit-level scanning is continuous in principle (Aardvark-style), but Codex Security is still research preview with per-task cost. Selective rather than universal.
 DryRun leads
Per-Review Economics (predictable vs. usage-metered) ✓
Flat subscription pricing based on team size. Usage pricing applies to DeepScan product.
 ✗
Cloud scans use token billing; Security Review uses Codex allowance or credits. Source 1 · Source 2
 DryRun leads
Code Security Intelligence3
Business Logic Flaw Detection ✓
Investigates authorization and business-logic vulnerabilities such as IDOR and tenant-isolation failures. Source
 ✓
Threat-model-guided investigation can examine logic and authorization vulnerabilities. Source 1 · Source 2
 Tie
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
 ~
Repository baselines, commit monitoring and finding-state summaries are documented. Source 1 · Source 2
 DryRun leads
Workflow & Supply Chain2
SCM Support ✓
GitHub and GitLab (native apps with OAuth)
 ~
GitHub only.
 DryRun leads
SBOM / AI-BOM Generation ✓
Provides dependency SBOMs and an AI-BOM inventory. Source 1 · Source 2
 ✗
No SBOM or AI-BOM generation capability.
 DryRun leads
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
 ✗
Not a compliance product.
 DryRun leads
Market Feedback (G2)4
G2 Rating / Review Count ℹ
4.9/5 (19 reviews) — g2.com/products/dryrun-security/reviews
 ℹ
Codex Security-specific G2 rating and review count not verified. Source 1 · Source 2
 —
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 exist for OpenAI Codex Security product
 —
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
"Learning curve for advanced features." (g2.com/products/openai/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
Learning curve; expensive higher tiers; context hallucinations (g2.com/products/openai/reviews)
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G2 High Performer — SAST Spring 2026