Xmore AI
Xmore AI provides an AI agent security platform that tests enterprise agents for over-broad permissions, unsafe tool use, prompt-injection exposure, and data leakage, then implements fixes and verifies them against the same attacks. The engagement runs four to six weeks, covering baseline assessment, adversarial testing, remediation, and continuous assurance with regression testing in CI and runtime anomaly monitoring.
- Cybersecurity
- Artificial Intelligence
- AI Agents
- Developer Tools
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Traditional application security assumes code decides what happens next, but AI agents operate differently—language decides, and that language can come from anyone whose content reaches the context window. Existing security stacks identify threats but still require human intervention to respond, creating dangerous delays. Agents also hold more access than the person who asked them, often wired to broad service accounts that can reach mailboxes, tickets, and HR records that no single employee could access.
Solution
Xmore AI delivers an AI agent security platform that tests enterprise agents for over-broad permissions, unsafe tool use, prompt-injection exposure, and data leakage, then implements fixes and verifies them against the same attacks. The engagement runs four to six weeks, beginning with scope and inventory mapping, followed by adversarial assessment across permissions, tool use, prompt injection, and data egress. After findings are ranked by real blast radius, the company implements remediation alongside client engineers—including least-privilege identities, tool guardrails, approval gates, and egress control—then re-runs the same attack suite to prove the fixes work. Continuous assurance then keeps the agent inventory current, runs the attack suite on every release, and watches for runtime anomalies like new tools, widened scopes, and first-seen egress destinations.
Target Audience
Primary customers are enterprise security teams and engineering organizations deploying AI agents in production, particularly those using agent frameworks like OpenAI, Anthropic, LangChain, CrewAI, or Microsoft Copilot Studio who need to assess and continuously assure agent security.
Features
- Baseline assessment producing a signed-off picture of every agent, tool, scope, and data source, used as the reference for drift detection
- Adversarial testing across four domains: permissions and identity, tool use, prompt injection, and data egress
- Injection corpus, permission probes, and egress tests run in CI as a pipeline gate on every release
- Runtime monitoring for new tools, widened OAuth scopes, first-seen egress destinations, unusual tool sequences, and spend spikes
- Findings mapped to OWASP Top 10 for LLM Applications, MITRE ATLAS, and NIST AI RMF
- Remediation delivered as pull requests and configuration changes in client repositories, with human-in-the-loop approval gates on irreversible, financial, and outbound actions
- Works with OpenAI Agents SDK, Anthropic Claude and MCP, LangChain/LangGraph, CrewAI, Microsoft Copilot Studio, Amazon Bedrock Agents, Google Vertex AI Agents, and in-house orchestration