// agents · uber/ADR

ADR

ADR est un projet de agents IA open source, créé par uber (uber/ADR sur GitHub). Il compte 1 950 étoiles sur GitHub et 202 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 8 octobre 2026.

Uber's ADR: discover, observe, benchmark, and detect threats across enterprise AI agents, deployed at Uber.

★ 1,9 k étoiles⑂ 202 forksApache-2.0mis à jour oct. 2026
▦ visuel — le README de ce projet ne contient aucune capture intégrable,
voici donc un emplacement réservé. Le guide ci-dessous est complet malgré tout.
// détails du projet

Détails du projet

Dépôt
uber/ADR
Étoiles GitHub
1 950
Forks
202
Licence
Apache-2.0
Dernière mise à jour sur GitHub
8 octobre 2026
Catégorie
Agents IA
Type de fiche
Guide d'installation complet
Site officiel
Official site
// fonctionnement

Comment ça marche

  1. Clarify your goal

    Decide which component you need first: endpoint discovery, telemetry collection, or the detection benchmark.

  2. Get the project

    Clone the repository and move into the component you are evaluating, such as Detection.

  3. Install and configure

    Sync the Python environment with uv and configure the model credentials the detector needs, or choose the keyless smoke-test detector.

  4. Run your first task

    Follow the reproducibility workflow to inflate the benchmark, run detectors, and review results before adapting components to your fleet.

// fonctionnalités

Pourquoi on l'adore

ADR Discovery

Inventories installed AI applications, CLI agents, IDE extensions, local model runtimes, and MCP servers on an endpoint, flagging unknown surfaces for review.

ADR Sensor observability

Collects and normalises agent intent, tool use, and execution traces from many coding tools across macOS, Linux, and Windows into a unified schema.

ADR-Bench benchmark

A security benchmark with hundreds of tasks and many MCP servers covering a range of agent attack techniques, with baselines included.

Two-tier ADR Detector

Combines high-recall triage with deeper agentic reasoning on suspicious sessions to detect risky agent behaviour efficiently.

Synthetic, safe fixtures

Benchmark fixtures are synthetic (fake credentials and emulated environments) intended for defensive security research.

Reproducibility documentation

A step-by-step workflow documents how to reproduce benchmark detection results and the paper's figures.

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// lancez-le

Lancez-le vous-même

  1. Clone and enter the Detection component

    The quickstart in the README focuses on ADR Detection.

    git clone https://github.com/uber/ADR.git
    cd ADR/Detection
  2. Sync the environment and set credentials

    The default adr detector uses an Anthropic key; a keyless smoke-test detector is also documented.

    uv sync
    export ANTHROPIC_API_KEY=<your key>
  3. Run the benchmark workflow

    Follow the reproducibility guide to inflate the packed benchmark and run detectors. # see README docs/REPRODUCIBILITY.md

    # see docs/REPRODUCIBILITY.md for the full evaluation workflow
// cas d'usage

Ce que vous pouvez créer

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// faq

Questions fréquentes

Who maintains it?

It is developed by Uber, where the README says it is deployed in production, and published under the uber GitHub organisation.

Is it free to use?

Yes, the released components are Apache-2.0 licensed. Running the default detector uses your own Anthropic API key; a keyless smoke-test detector option is documented.

Does it need a paid API key?

For the default detector, yes, an Anthropic API key is configured in the quickstart. Organisations can adapt components to their own model setups.

How does it compare to a well-known alternative?

Endpoint security tools watch processes and files; ADR is purpose-built for agent behaviour: it inventories AI tools, observes agent traces, and benchmarks agent-specific attacks such as prompt injection through MCP servers.

How do I get started?

Clone the repo, cd into Detection, run uv sync, set ANTHROPIC_API_KEY, and follow docs/REPRODUCIBILITY.md.

// continuez l'exploration

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// alternatives

Alternatives en Agents IA

Les autres projets de la catégorie Agents IA avec le plus d'étoiles du catalogue LibreAI — la sélection réaliste d'alternatives si ADR ne vous convient pas.

// plus en agents

Plus en Agents IA

Projets de la catégorie Agents IA proches dans le catalogue, les plus proches en étoiles de ADR — continuez à explorer de part et d'autre.

Obtenir ADR

Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.