Getting Started with XOR GitHub App
Install in 2 minutes. First result in 15. One-click GitHub App install, first auto-review walkthrough, and engineering KPI triad.
Installation
One-click install from github.com/apps/xor-hardener. Select your org, choose repositories, and authorize. XOR creates an evergreen issue in each repo listing every capability and how to trigger it.
Your first interaction
Mention @xor-hardener in any PR comment with what you need. XOR reads the diff, checks for vulnerabilities, and posts a structured review. No configuration files. No YAML.
Install in 2 minutes. First result in 15.
XOR's GitHub App runs security analysis on your pull requests. Mention @xor-hardener in any PR or issue comment, tell it what you need, and it does the work. No configuration files. No YAML. One install, then prompt it.
Verification = reproduce the vulnerability, apply the patch, re-run the exploit harness, and reject if behavior deviates.
Engineering KPI triad
13 min
Median time to verified fix
From CVE to merged patch
45+ min
Reviewer minutes saved
Reclaimed per vulnerability
370
Broken patches caught
Rejected before review
Source: CVE-Agent-Bench, 128 CVEs, 13 agents evaluated. Full results →
Installation
Prerequisites: GitHub org admin access and at least one active repository.
- Go to github.com/apps/xor-hardener
- Click Install
- Select your org
- Choose "Only select repositories" — pick 1-5 repos to start
- Click Install & Authorize
What happens next
- XOR creates a tracking issue in each selected repo ("XOR Evergreen Issue") listing every capability and how to trigger it
- XOR sets up a read-only mirror of each repo for analysis
- You can mention
@xor-hardenerin any PR or issue to request work
Your first interaction
Open any pull request. Add a comment:
@xor-hardener Review this PR for security issues.
XOR reads the diff, checks for vulnerabilities, and posts a structured review with inline comments. For every capability, see Platform Capabilities.
Data isolation
Your code stays in your org. XOR operates on a read-only mirror — no write access to your repositories. All analysis runs against this mirror. When you uninstall, the mirror is deleted.
Training data: Your code never becomes training data without explicit opt-in. XOR analyzes your dependencies; it doesn't learn from your proprietary code.
[NEXT STEPS]
Start using XOR
FAQ
How long does installation take?
Under 2 minutes. Go to github.com/apps/xor-hardener, click Install, select your org and repos. XOR creates a tracking issue in each repo and you can start using it immediately.
Does XOR have write access to my repositories?
No. XOR operates on a read-only mirror. All analysis runs against this mirror. When you uninstall, the mirror is deleted. Your code never becomes training data without explicit opt-in.
What is the first thing I should try?
Open any pull request and comment: @xor-hardener Review this PR for security issues. XOR reads the diff, checks for vulnerabilities, and posts a structured review with inline comments.
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.
Agent Strategies
How different agents approach the same bug. Strategy matters as much as model capability.
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.
Platform Capabilities
One install. Seven capabilities. Prompt-driven. CVE autopatch, PR review, CI hardening, guardrail review, audit packets, and more.
Dependabot Verification
Dependabot bumps versions. XOR verifies they're safe to merge. Reachability analysis, EPSS/KEV enrichment, and structured verdicts.
Compliance Evidence
Machine-readable evidence for every triaged vulnerability. VEX statements, verification reports, and audit trails produced automatically.
Compatibility and Prerequisites
Languages, build systems, CI platforms, and repository types supported by XOR. What you need to get started.
Command Reference
Every @xor-hardener command on one page. /review, /describe, /ask, /patch_i, /issue_spec, /issue_implement, and more.
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.
Agentic Third-Party Risk
33% of enterprise software will be agentic by 2028. 40% of those projects will be canceled due to governance failures. A risk overview for CTOs.
MCP Server Security
17 attack types across 4 surfaces. 7.2% of 1,899 open-source MCP servers contain vulnerabilities. Technical deep-dive with defense controls.
How Agents Get Attacked
20% jailbreak success rate. 42 seconds average. 90% of successful attacks leak data. Threat landscape grounded in published research.
Governing AI Agents in the Enterprise
92% of AI vendors claim broad data usage rights. 17% commit to regulatory compliance. Governance frameworks from NIST, OWASP, EU CRA, and Stanford CodeX.
OWASP Top 10 for Agentic Applications
The OWASP Agentic Top 10 mapped to real-world attack data and XOR capabilities. A reference page for security teams.
See which agents produce fixes that work
128 CVEs. 13 agents. 1,664 evaluations. Agents learn from every run.