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Hydra is a framework developed by Facebook Research for elegantly configuring complex applications. The vulnerability identified as CVE-2026-68508 resides within the `hydra.utils.instantiate()` function prior to version 1.3.4. This utility is designed to resolve Python objects based on configuration data by invoking `_resolve_target()` in hydra/_internal/instantiate/_instantiate2.py. The core technical deficiency lies in the fact that this resolution mechanism does not sufficiently validate or restrict the target classes and their associated arguments when they are derived from untrusted sources such as external configuration files, command-line interface overrides, or model metadata.
When a config containing a `_target_` field is passed to hydra.utils.instantiate(), Hydra resolves `_target_` and calls it with the provided arguments. This behavior is intended for trusted application configuration. However, if untrusted input controls _target_, the config becomes a callable-selection mechanism. A malicious config can select a callable capable of executing code or commands and provide attacker-controlled arguments. From a technical perspective, this vulnerability allows for arbitrary code execution because the instantiate function effectively acts as a dynamic loader that trusts its input without adequate sanitization.
This issue is the same general class of problem discussed by Unit 42 for downstream AI/ML libraries such as NVIDIA NeMo, where untrusted model metadata was passed into Hydra instantiate. Hydra 1.3.4 includes a blacklist for some dangerous `_target_` values as a defense-in-depth measure, but this blacklist is not a complete security boundary. The blacklist is not present in the released `hydra-core` 1.3.3 package. The unreleased Hydra 1.4 development line uses an allowlist-based instantiation model that fully addresses this vulnerability class.
Hydra is not a network service, so exploitation requires a consuming application, library, or user workflow to load attacker-controlled config, CLI overrides, or model metadata and pass it to hydra.utils.instantiate().
DailyCVE Form:
Platform: Hydra (Facebook Research)
Version: < 1.3.4
Vulnerability: Code Injection (RCE)
Severity: High (CVSS 7.8)
Date: 2026-08-21
Prediction: Patch available (1.3.4)
What Undercode Say:
Analytics:
Hydra’s `instantiate()` API is widely used in AI/ML pipelines for dynamic object construction from configuration files. Attackers can exploit this by embedding malicious `_target_` values in model metadata files (e.g., Hugging Face model configs) or CLI overrides. The vulnerability is triggered when an application passes untrusted configuration to `hydra.utils.instantiate()` without constraining which targets may be instantiated. Successful exploitation allows arbitrary code execution in the context of the consuming process.
Bash Commands & Code:
Check Hydra version pip show hydra-core Upgrade to patched version pip install --upgrade hydra-core==1.3.4 If using conda conda update hydra-core Set allowlist override (defense-in-depth) export HYDRA_INSTANTIATE_ALLOWLIST_OVERRIDE="safe.module:function"
Exploit: (Educational Purposes!)
Malicious config.yaml component: <em>target</em>: os.system args: ["rm -rf /important/data"]
Vulnerable code pattern
import hydra
from omegaconf import OmegaConf
Attacker-controlled config loaded from untrusted source
config = OmegaConf.load("malicious_config.yaml")
hydra.utils.instantiate(config.component) RCE!
Protection:
- Upgrade to Hydra 1.3.4 or later – this version adds target blocking with an explicit `HYDRA_INSTANTIATE_ALLOWLIST_OVERRIDE` escape hatch
- Validate `_target_` values against a trusted allowlist before passing to `instantiate()`
3. Never pass untrusted configuration, CLI overrides, or model metadata directly to `hydra.utils.instantiate()`
4. Restrict instantiate() usage – only use with trusted configs - Implement allowlists for permitted target modules and classes as a defense-in-depth strategy
Impact:
A successful attack can execute arbitrary code in the process that calls hydra.utils.instantiate(). The impact is limited to the privileges and environment of that process and includes:
– Reading files, credentials, environment variables, or data accessible to the process
– Modifying files, outputs, checkpoints, or application state writable by the process
– Terminating or disrupting the process
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Sources:
Reported By: github.com
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