Agent Configurations
13 agent-model configurations evaluated on real CVEs. Compare Claude Code, Codex, Gemini CLI, Cursor, and OpenCode.
Agent coverage
13 agent-model configurations spanning 5 major coding agent frameworks. Each agent runs on the same set of vulnerabilities for fair comparison.
Per-agent metrics
Each agent profile includes pass rate, cost per fix, build failure rate, and infrastructure failure rate. Results feed back into agent harnesses for continuous learning.
Agent Comparison
9 agents tested on 136 real bugs. Each agent runs in an isolated container with automated safety checks.
Unlock full results
Enter your email to access the full methodology, per-sample analysis, and patch examples.
FAQ
Which agents are evaluated?
Claude Code, Codex, Gemini CLI, Cursor, and OpenCode across 13 model configurations including Claude Opus 4.5/4.6, GPT-5.2, Gemini 3 Pro, and Cursor Composer.
Can I add my own agent?
Yes. The benchmark framework accepts any agent that writes code. Contact us for custom agent evaluation.
Patch verification
XOR writes a verifier for each vulnerability, then tests agent-generated patches against it. If the fix passes, it ships. If not, the failure feeds back into the agent harness.
Automated vulnerability patching
AI agents generate fixes for known CVEs. XOR verifies each fix and feeds outcomes back into the agent harness so future patches improve.
Benchmark Results
62.7% pass rate. $2.64 per fix. Real data from 1,736 evaluations.
Benchmark Results
62.7% pass rate. $2.64 per fix. Real data from 1,736 evaluations.
Agent Cost Economics
Fix vulnerabilities for $2.64–$87 with agents. 100x cheaper than incident response. Real cost data.
Benchmark Methodology
How CVE-Agent-Bench evaluates 13 coding agents on 136 real vulnerabilities. Deterministic, reproducible, open methodology.
Agent Environment Security
AI agents run with real permissions. XOR verifies tool configurations, sandbox boundaries, and credential exposure.
Security Economics for Agentic Patching
Security economics for agentic patching. ROI models backed by verified pass/fail data and business-impact triage.
Automated Vulnerability Patching and PR Review
Automated code review, fix generation, GitHub Actions hardening, safety checks, and learning feedback. One-click install on any GitHub repository.
Continuous Learning from Verified Agent Runs
A signed record of every agent run. See what the agent did, verify it independently, and feed the data back so agents improve.
Signed Compliance Evidence for AI Agents
A tamper-proof record of every AI agent action. Produces evidence for SOC 2, EU AI Act, PCI DSS, and more. Built on open standards so auditors verify independently.
Compliance Evidence and Standards Alignment
How XOR signed audit trails produce evidence for SOC 2, EU AI Act, PCI DSS, NIST, and other compliance frameworks.
See which agents produce fixes that work
136 CVEs. 13 agents. 1,736 evaluations. Agents learn from every run.