Agent Strategies
How different agents approach the same bug. Strategy matters as much as model capability.
Strategy clusters
K-means clustering on session features (turns, tool calls, file reads, edits, backtracking) reveals distinct behavioral patterns. Agents cluster by approach, not just by model.
What this means for agent selection
If an agent falls into a low-pass-rate cluster, its behavioral pattern may be the bottleneck - not its model intelligence. Strategy is sometimes more tunable than the model itself.
How AI agents approach the same bug differently
K-means clustering on 10 session features (turns, tool calls, file reads, edits, backtracking) reveals 3 distinct behavioral patterns across 973 sessions. Some agents explore broadly. Others edit fast. The pattern predicts the outcome.
[KEY INSIGHT]
60% pass rate in the best cluster
The cluster with the highest pass rate shares specific behavioral traits. Pass rate correlates with approach - not just model capability.
Cluster composition
Each cluster's size, pass rate, and dominant agents. Larger clusters represent the most common behavioral strategy.
speed-runner
211 sessions
Top agents
explorer
25 sessions
Top agents
surgical-expert
737 sessions
Top agents
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FAQ
How do agents differ in their approach?
Some agents explore broadly (read many files, backtrack often). Others edit fast (fewer reads, targeted changes). The approach pattern predicts the outcome.
Can I configure agent strategy?
Often yes. System prompts, tool access, and memory settings influence agent behavior. The best-performing cluster shares specific traits: fewer file reads, targeted edits, less backtracking.
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 1,664 evaluations.
Benchmark Results
62.7% pass rate. $2.64 per fix. Real data from 1,664 evaluations.
Agent Cost Economics
Fix vulnerabilities for $2.64–$52 with agents. 100x cheaper than incident response. Real cost data.
Agent Configurations
13 agent-model configurations evaluated on real CVEs. Compare Claude Code, Codex, Gemini CLI, Cursor, and OpenCode.
Benchmark Methodology
How CVE-Agent-Bench evaluates 13 coding agents on 128 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.
Validation Process
25 questions we ran against our own data before publishing. Challenges assumptions, explores implications, extends findings.
Cost Analysis
10 findings on what AI patching costs and whether it is worth buying. 1,664 evaluations analyzed.
Bug Complexity
128 vulnerabilities scored by difficulty. Floor = every agent fixes it. Ceiling = no agent can.
Execution Metrics
Per-agent session data: turns, tool calls, tokens, and timing. See what happens inside an agent run.
Pricing Transparency
Every cost number has a source. Published pricing models, measurement methods, and provider rates.
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
128 CVEs. 13 agents. 1,664 evaluations. Agents learn from every run.