Update torch requirement from <2.11 to <2.13

[dependabot]

Updates the requirements on torch to permit the latest version.

Release notes

Sourced from torch's releases.

PyTorch 2.12.0 Release Notes

• Highlights
• Backwards Incompatible Changes
• Deprecations
• New Features
• Improvements
• Bug fixes
• Performance
• Documentation
• Developers
• Security

Highlights

For more details about these highlighted features, you can look at the release blogpost. Below are the full release notes for this release.

Backwards Incompatible Changes

Build Frontend

• Strengthened SVE compile checks in FindARM.cmake, which may reject previously accepted but incorrect SVE configurations (#176646)

  Source builds that enable SVE now validate the compiler configuration more strictly. If a build previously passed with an incomplete or mismatched SVE setup, it may now fail during CMake configuration instead of later in compilation. Update the compiler/toolchain flags so they accurately describe the target SVE support, or disable SVE for that build.

• Updated the minimum CUDA version required to build PyTorch from source to CUDA 12.6 (#178925)

  Building PyTorch from source with CUDA versions older than 12.6 is no longer supported. Users building custom binaries should install CUDA 12.6 or newer and make sure CUDA_HOME points to that installation.

  Version 2.11:

  CUDA_HOME=/usr/local/cuda-12.4 python setup.py develop

  Version 2.12:

  CUDA_HOME=/usr/local/cuda-12.6 python setup.py develop

• Enforced a C++20 minimum in CMake build files (#178662)

... (truncated)

Changelog

Sourced from torch's changelog.

Releasing PyTorch

• Release Compatibility Matrix
  • PyTorch CUDA Support Matrix
• Release Cadence
• General Overview
  • Frequently Asked Questions
• Cutting a release branch preparations
• Cutting release branches
  • pytorch/pytorch
  • PyTorch ecosystem libraries
  • Making release branch specific changes for PyTorch
  • Making release branch specific changes for ecosystem libraries
• Running Launch Execution team Core XFN sync
• Drafting RCs (https://github.com/pytorch/pytorch/blob/main/Release Candidates) for PyTorch and domain libraries
  • Release Candidate Storage
  • Release Candidate health validation
  • Cherry Picking Fixes
    • How to do Cherry Picking
  • Cherry Picking Reverts
• Preparing and Creating Final Release Candidate
• Promoting RCs to Stable
• Additional Steps to prepare for release day
  • Modify release matrix
  • Open Google Colab issue
• Patch Releases
  • Patch Release Criteria
  • Patch Release Process
    • Patch Release Process Description
    • Triage
    • Issue Tracker for Patch releases
    • Building a release schedule / cherry picking
    • Building Binaries / Promotion to Stable
• Hardware / Software Support in Binary Build Matrix
  • Python
  • Accelerator Software
    • Special support cases
  • Operating Systems
• Submitting Tutorials
• Special Topics
  • Updating submodules for a release
  • Triton dependency for the release

Release Compatibility Matrix

Following is the Release Compatibility Matrix for PyTorch releases:

... (truncated)

Commits

• 0d62256 [release] Dockerfile: skip torchaudio install when CUDA_PATH=cu132 (#183346)
• 7661cd9 [MPS] Fix SDPA wrong output for permuted q/k/v with B > 1 (#181886)
• 9da6087 Fix stale PYTORCH_RELEASES_CODE_CC dict (fixes #182250) (#182369)
• e4c37cc Avoid raw stream name collisions in Inductor (#182178)
• 822d047 [MPS] Fix bool mask handling in 1-pass SDPA decode kernel (#182285) (#182311)
• 5c5e523 Add enable_gqa parameter to SDPA MPS meta registration (#181550)
• eece52e [AOTI] Add BC-safe c_shim v2 for _scaled_dot_product_attention_math_for_mps e...
• b39330b [Inductor] Call latest c_shim version for versioned fallback ops (#181548)
• 06f10d0 Revert "[FSDP2] add fqn to communication ops" (#182100) (#182157)
• 449e339 Revert "[Inductor] Improve materialization heuristic for a chain of computaio...
• Additional commits viewable in compare view

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[socket-security]

Review the following changes in direct dependencies. Learn more about Socket for GitHub.

Diff	Package	Supply Chain Security	Vulnerability	Quality	Maintenance	License
	torch@​2.10.0 ⏵ 2.12.0

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[socket-security]

Warning

Review the following alerts detected in dependencies.

According to your organization's Security Policy, it is recommended to resolve "Warn" alerts. Learn more about Socket for GitHub.

Action	Severity	Alert  (click "▶" to expand/collapse)
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 83.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.83 Severity: 0.88 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.
Warn		Potentially malicious package (AI signal): pypi torch is 60.0% likely malicious Notes: This code fragment contains a critical supply-chain/security weakness: it evaluates an input string with eval() to create a kernel object, and then executes that object through TorchInductor/Triton kernel run paths. If kernel_source can be influenced by an attacker, this becomes an immediate arbitrary code execution risk with high downstream impact. No explicit exfiltration/credential theft behavior is shown here; the primary concern is the eval-driven dynamic execution capability and the resulting ability to steer kernel execution. Confidence is limited only by the absence of context for how kernel_source is sourced. Confidence: 0.60 Severity: 0.90 From: pyproject.toml → pypi/torch@2.12.0 ℹ Read more on: This package | This alert | What is AI-detected potential malware? Next steps: Take a moment to review the security alert above. Review the linked package source code to understand the potential risk. Ensure the package is not malicious before proceeding. If you're unsure how to proceed, reach out to your security team or ask the Socket team for help at support@socket.dev. Suggestion: Given the AI system's identification of this package as malware, extreme caution is advised. It is recommended to avoid downloading or installing this package until the threat is confirmed or flagged as a false positive. Mark the package as acceptable risk. To ignore this alert only in this pull request, reply with the comment @SocketSecurity ignore pypi/torch@2.12.0. You can also ignore all packages with @SocketSecurity ignore-all. To ignore an alert for all future pull requests, use Socket's Dashboard to change the triage state of this alert.

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