Maintainer of this skill?
Automated security scan — not a certification.
by uber
ADR secures enterprise AI agents through observability, security benchmarking, and threat detection. Deployed at Uber.
# Add to your Claude Code skills
git clone https://github.com/uber/ADRGuides for using ai agents skills like ADR.
Last scanned: 8/4/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-08-04T06:27:23.880Z",
"npmAuditRan": true,
"pipAuditRan": true,
"promptInjectionRan": true
}See how ADR compares with popular alternatives.
ADR is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by uber. ADR secures enterprise AI agents through observability, security benchmarking, and threat detection. Deployed at Uber. It has 2,092 GitHub stars.
Yes. ADR passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/uber/ADR" and add it to your Claude Code skills directory (see the Installation section above).
ADR is primarily written in Python. It is open-source under uber on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh ADR against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Automated security scan — not a certification.
ADR (Agentic AI Detection and Response) is an enterprise security system for AI agents. It helps organizations secure employee-facing agents such as Cursor, Claude Code, Codex, GitHub Copilot CLI, and DeepSeek Harness, as well as customer-facing agents such as AI support agents.
ADR is deployed in production at Uber, and the accompanying paper was accepted to MLSys 2026: Paper PDF · Slides PDF
ADR secures enterprise AI agents through five complementary capabilities: discovering unsanctioned AI tools, observing agent activity, evaluating defenses, detecting threats, and preventing unsafe actions.
This repository contains the open-source ADR Discovery, ADR Sensor, ADR-Bench, and ADR Detector described in the paper. The offline ADR Explorer engine, which hardens ADR Detection through pre-deployment red teaming, is not included here.
| Path | ADR component | Description |
|---|---|---|
| Discovery/ | ADR Discovery | Inventory the AI apps, CLI agents, IDE extensions, model runtimes, and MCP servers on an endpoint, and flag unknown surfaces for review |
| Sensor/ | ADR Observability | Collect and normalize agent telemetry from Claude Code, Cursor, Codex, GitHub Copilot CLI, DeepSeek Harness, opencode, Claude Desktop, and others |
| Detection/ | ADR Benchmark + Detection | Dual-agent detector, 134 MCP servers, 304 benchmark tasks, baselines, figure scripts |
| docs/REPRODUCIBILITY.md | Evaluation | Step-by-step workflow to reproduce benchmark detection and paper figures |
git clone https://github.com/uber/ADR
cd ADR/Detection
uv sync
export ANTHROPIC_API_KEY="..." OPENAI_API_KEY="..."
Default detector is adr (ADR dual-agent). For keyless smoke tests, use --detector llamafirewall (see Detection/README.md).
See docs/REPRODUCIBILITY.md for the full evaluation workflow (inflate packed benchmark → run detectors → plot figures).
Component documentation:
ADR Sensor also captures Gemini CLI session journals on macOS, Linux, and Windows, including tool results and nested subagent sessions.
@inproceedings{li2026adr,
title={ADR: An Agentic Detection System for Enterprise Agentic AI Security},
author={Li, Chenning and Hu, Pan and Xu, Justin and Ozbas, Baris and Liu, Olivia and Van, Caroline and Li, Manxue and Zhou, Wei and Alizadeh, Mohammad and Zhang, Pengyu and Sriramadhesikan, KK and Zhang, Ming},
booktitle={Proceedings of the Ninth Conference on Machine Learning and Systems},
year={2026}
}
Or use CITATION.cff.
Apache License 2.0. See LICENSE. Detection/benchmark/agentdojo/ is vendored third-party code under its own LICENSE (MIT).
Detection/ includes synthetic benchmark fixtures (fake credentials, emulated environments, prompt-injection scenarios) for defensive security research only. Details: docs/OPEN_SOURCE_REVIEW.md.