Every CVESearch/Get API key

GHSA-wf6j-7hvr-gr93

Hydra legacy target blacklist permits unsafe PyYAML loading

7.8 HighFix available

Summary

Hydra's legacy target blacklist omits PyYAML's unsafe loading surfaces. If an application passes attacker-controlled targets and arguments to instantiate(), a target such as yaml.unsafe_load can execute Python code through a config-controlled YAML stream containing Python object-construction tags.

Impact and prerequisites

The attacker must control the relevant target and arguments that the application instantiates. The configured callable executes with the application's process privileges. This is a gap in the best-effort legacy blacklist. It is not a bypass of Hydra 1.4's execution whitelist supplied by trusted Python code.

One realistic exposure is a model downloaded from a third-party repository, such as Hugging Face, that bundles attacker-controlled configuration. When a victim loads the model using application code that passes this configuration to legacy Hydra instantiation without effective target restrictions, the model's metadata can execute code in the victim process. This model-loading attack pattern is documented in the original Hydra advisory GHSA-2cp2-2r3c-7p7r and the associated Unit 42 research. It does not imply that all Hugging Face models or currently patched downstream loaders are affected.

Hydra 1.3's blacklist is defense in depth, not a complete security boundary. Hydra 1.4 is affected on its deprecated no-whitelist legacy path. Installed application wrappers can perform indirect operations beyond a name-based blacklist's coverage; this fix does not make arbitrary configuration safe.

The unsafe_load finding is directly reproduced. PyYAML 6.0.3 full_load rejects the demonstrated python/object/apply payload, so the finding does not claim that all PyYAML loading APIs execute that payload.

Remediation

The fix blocks the yaml. target namespace except for the exact yaml.safe_load, yaml.safe_load_all, yaml.safe_dump, and yaml.safe_dump_all functions. Loader classes, constructor registration, general dump/load APIs, and other targets in the namespace remain blocked. Existing canonical-identity checks also cover aliases. The fix preserves Hydra 1.4's explicit unsafe opt-out for trusted use.

Workarounds

Do not pass untrusted configuration to instantiate() or call(). For Hydra 1.4, supply a narrow execution whitelist from trusted Python code. Do not let untrusted configuration select its own execution policy or opt out of checks.

Affected releases

The reported incomplete-remediation stable range is hydra-core 1.3.6 through 1.3.7. The 1.4 prerelease legacy path is also affected, including 1.4.0.dev9, 1.4.0.dev10, 1.4.0rc1, and 1.4.0rc2. The related blacklist advisory GHSA-rqx7-p7vv-w7hr was first patched in 1.3.6 and 1.4.0.dev9; these ranges describe the remaining omission after that remediation.

Credit

Reported by zx (@manus-pi).

Attack profile

How easy it is to exploit

Attack vector
Local
Complexity
Low
Privileges needed
None
User interaction
Required

What an attacker can affect

Confidentiality
High
Integrity
High
Availability
High

What each source reports

GitHub Advisories Score used7.8

Hydra legacy target blacklist permits unsafe PyYAML loading

Summary

Hydra's legacy target blacklist omits PyYAML's unsafe loading surfaces. If an application passes attacker-controlled targets and arguments to instantiate(), a target such as yaml.unsafe_load can execute Python code through a config-controlled YAML stream containing Python object-construction tags.

Impact and prerequisites

The attacker must control the relevant target and arguments that the application instantiates. The configured callable executes with the application's process privileges. This is a gap in the best-effort legacy blacklist. It is not a bypass of Hydra 1.4's execution whitelist supplied by trusted Python code.

One realistic exposure is a model downloaded from a third-party repository, such as Hugging Face, that bundles attacker-controlled configuration. When a victim loads the model using application code that passes this configuration to legacy Hydra instantiation without effective target restrictions, the model's metadata can execute code in the victim process. This model-loading attack pattern is documented in the original Hydra advisory GHSA-2cp2-2r3c-7p7r and the associated Unit 42 research. It does not imply that all Hugging Face models or currently patched downstream loaders are affected.

Hydra 1.3's blacklist is defense in depth, not a complete security boundary. Hydra 1.4 is affected on its deprecated no-whitelist legacy path. Installed application wrappers can perform indirect operations beyond a name-based blacklist's coverage; this fix does not make arbitrary configuration safe.

The unsafe_load finding is directly reproduced. PyYAML 6.0.3 full_load rejects the demonstrated python/object/apply payload, so the finding does not claim that all PyYAML loading APIs execute that payload.

Remediation

The fix blocks the yaml. target namespace except for the exact yaml.safe_load, yaml.safe_load_all, yaml.safe_dump, and yaml.safe_dump_all functions. Loader classes, constructor registration, general dump/load APIs, and other targets in the namespace remain blocked. Existing canonical-identity checks also cover aliases. The fix preserves Hydra 1.4's explicit unsafe opt-out for trusted use.

Workarounds

Do not pass untrusted configuration to instantiate() or call(). For Hydra 1.4, supply a narrow execution whitelist from trusted Python code. Do not let untrusted configuration select its own execution policy or opt out of checks.

Affected releases

The reported incomplete-remediation stable range is hydra-core 1.3.6 through 1.3.7. The 1.4 prerelease legacy path is also affected, including 1.4.0.dev9, 1.4.0.dev10, 1.4.0rc1, and 1.4.0rc2. The related blacklist advisory GHSA-rqx7-p7vv-w7hr was first patched in 1.3.6 and 1.4.0.dev9; these ranges describe the remaining omission after that remediation.

Credit

Reported by zx (@manus-pi).

Record
GHSA-wf6j-7hvr-gr93
CVSS 3.1
7.8 HighCVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Weakness
CWE-184
Updated
2026-11-02
OSV7.8

Hydra legacy target blacklist permits unsafe PyYAML loading

Summary

Hydra's legacy target blacklist omits PyYAML's unsafe loading surfaces. If an application passes attacker-controlled targets and arguments to instantiate(), a target such as yaml.unsafe_load can execute Python code through a config-controlled YAML stream containing Python object-construction tags.

Impact and prerequisites

The attacker must control the relevant target and arguments that the application instantiates. The configured callable executes with the application's process privileges. This is a gap in the best-effort legacy blacklist. It is not a bypass of Hydra 1.4's execution whitelist supplied by trusted Python code.

One realistic exposure is a model downloaded from a third-party repository, such as Hugging Face, that bundles attacker-controlled configuration. When a victim loads the model using application code that passes this configuration to legacy Hydra instantiation without effective target restrictions, the model's metadata can execute code in the victim process. This model-loading attack pattern is documented in the original Hydra advisory GHSA-2cp2-2r3c-7p7r and the associated Unit 42 research. It does not imply that all Hugging Face models or currently patched downstream loaders are affected.

Hydra 1.3's blacklist is defense in depth, not a complete security boundary. Hydra 1.4 is affected on its deprecated no-whitelist legacy path. Installed application wrappers can perform indirect operations beyond a name-based blacklist's coverage; this fix does not make arbitrary configuration safe.

The unsafe_load finding is directly reproduced. PyYAML 6.0.3 full_load rejects the demonstrated python/object/apply payload, so the finding does not claim that all PyYAML loading APIs execute that payload.

Remediation

The fix blocks the yaml. target namespace except for the exact yaml.safe_load, yaml.safe_load_all, yaml.safe_dump, and yaml.safe_dump_all functions. Loader classes, constructor registration, general dump/load APIs, and other targets in the namespace remain blocked. Existing canonical-identity checks also cover aliases. The fix preserves Hydra 1.4's explicit unsafe opt-out for trusted use.

Workarounds

Do not pass untrusted configuration to instantiate() or call(). For Hydra 1.4, supply a narrow execution whitelist from trusted Python code. Do not let untrusted configuration select its own execution policy or opt out of checks.

Affected releases

The reported incomplete-remediation stable range is hydra-core 1.3.6 through 1.3.7. The 1.4 prerelease legacy path is also affected, including 1.4.0.dev9, 1.4.0.dev10, 1.4.0rc1, and 1.4.0rc2. The related blacklist advisory GHSA-rqx7-p7vv-w7hr was first patched in 1.3.6 and 1.4.0.dev9; these ranges describe the remaining omission after that remediation.

Credit

Reported by zx (@manus-pi).

Record
GHSA-wf6j-7hvr-gr93
CVSS 3.1
7.8 HighCVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Weakness
CWE-184
Updated
2026-11-02

Affected packages

Affected packages
PackageAffectedFixed
hydra-core
PyPI
1.3.6 up to 1.3.8
1.3.8
hydra-core
PyPI
1.4.0.dev9 up to 1.4.0rc3
1.4.0rc3
hydra-core
PyPI
1.3.6 up to 1.3.8, plus listed versions
1.3.7
1.3.8
hydra-core
PyPI
1.4.0.dev9 up to 1.4.0rc3, plus listed versions
1.4.0.dev101.4.0rc11.4.0rc2
1.4.0rc3

History

History
RecordedChangedSources
first indexedGitHub Advisories, OSV

Dates are when Every CVE recorded each change. Upstream dates may differ.

In short

GHSA-wf6j-7hvr-gr93 is a high vulnerability (CVSS 7.8) in hydra-core, published October 27, 2026. No source lists public exploit code. Fixed in hydra-core 1.3.8.

References

MoveEnter Open