Verified AgentSkills
Supply chain verification for AI agent skills. 36.82% of agent skills have known vulnerabilities.
The problem
AI agents run third-party tools with real permissions. Nobody checks if those tools are safe. Snyk found that 36.82% of 3,984 audited agent skills contain known vulnerabilities.
What Verified AgentSkills does
Scans third-party skills for vulnerabilities, signs verified skills with a tamper-proof signature, and blocks unverified skills from running in production.
[COMING SOON]
Supply chain verification for AI agent skills
36.82% of agent skills have known vulnerabilities. Verified AgentSkills checks third-party skills before your agents run them - signed, scanned, and independently tested.
Get notified at launch
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FAQ
What is agent skill verification?
AI agents use third-party skills (MCP servers, plugins, tool packages). 36.82% of these have known vulnerabilities. Verified AgentSkills scans, signs, and checks skills before your agents run them.
Where does the 36.82% figure come from?
Snyk ToxicSkills audit, February 2026. 3,984 agent skills audited across public marketplaces. 1,467 had known vulnerabilities.
When does Verified AgentSkills launch?
Coming soon. Enter your email on the contact page to get notified at launch.
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.
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.