fix(deps): vuln torch (major → 2.12.0) [examples/pytorch/audio-classification]

[gh-worker-campaigns-3e9aa4]

Summary: Critical-severity security update — 1 package upgraded (MAJOR changes included)

Manifests changed:

• examples/pytorch/audio-classification (pip)

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✅ Action Required: Please review the changes below. If they look good, approve and merge this PR.

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Updates

Package	From	To	Type	Dep Type	Vulnerabilities Fixed
torch	1.6	2.12.0	major	Direct	8 CRITICAL, 19 HIGH, 18 MEDIUM, 14 LOW

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Warning

Major Version Upgrade

This update includes major version changes that may contain breaking changes. Please:

• Review the changelog/release notes for breaking changes
• Test thoroughly in a staging environment
• Update any code that depends on changed APIs
• Ensure all tests pass before merging

Security Details

🚨 Critical & High Severity (27 fixed)

Package	CVE	Severity	Summary	Unsafe Version	Fixed In
torch	CVE-2025-32434	critical	PyTorch: torch.load with weights_only=True leads to remote code execution	1.6	-
torch	GHSA-53q9-r3pm-6pq6	CRITICAL	PyTorch: torch.load with weights_only=True leads to remote code execution	1.6	2.6.0
torch	GHSA-47fc-vmwq-366v	CRITICAL	PyTorch vulnerable to arbitrary code execution	1.6	1.13.1
torch	CVE-2022-45907	CRITICAL	-	1.6	-
torch	PYSEC-2022-43015	CRITICAL	-	1.6	767f6aa49fe20a2766b9843d01e3b7f7793df6a3
torch	CVE-2024-48063	critical	-	1.6	-
torch	PYSEC-2024-259	critical	-	1.6	2.5.0
torch	PYSEC-2025-41	critical	-	1.6	2.6.0
torch	CVE-2025-55552	high	-	1.6	-
torch	PYSEC-2024-252	HIGH	-	1.6	b5c3a17c2c207ebefcb85043f0cf94be9b2fef81
torch	CVE-2025-55551	high	-	1.6	-
torch	PYSEC-2025-203	high	-	1.6	2.9.0
torch	PYSEC-2026-139	high	-	1.6	-
torch	PYSEC-2025-209	high	-	1.6	2.7.1
torch	CVE-2025-55557	high	-	1.6	-
torch	PYSEC-2025-204	high	-	1.6	2.9.0
torch	PYSEC-2025-207	high	-	1.6	2.7.1
torch	GHSA-pg7h-5qx3-wjr3	HIGH	Pytorch use-after-free vulnerability	1.6	2.2.0
torch	CVE-2024-31583	HIGH	-	1.6	-
torch	PYSEC-2024-251	HIGH	-	1.6	9c7071b0e324f9fb68ab881283d6b8d388a4bcd2
torch	CVE-2025-55558	high	-	1.6	-
torch	PYSEC-2025-208	high	-	1.6	2.7.1
torch	CVE-2025-55560	high	-	1.6	-
torch	PYSEC-2025-205	high	-	1.6	2.7.1
torch	CVE-2025-55553	high	-	1.6	-
torch	GHSA-5pcm-hx3q-hm94	HIGH	PyTorch heap buffer overflow vulnerability	1.6	2.2.0
torch	CVE-2024-31580	HIGH	-	1.6	-

ℹ️ Other Vulnerabilities (32)

Package	CVE	Severity	Summary	Unsafe Version	Fixed In
torch	PYSEC-2025-198	medium	-	1.6	2.7.0
torch	PYSEC-2025-206	medium	-	1.6	2.9.0
torch	CVE-2025-55554	medium	-	1.6	-
torch	CVE-2025-3121	medium	-	1.6	-
torch	PYSEC-2025-196	medium	-	1.6	-
torch	CVE-2024-31584	medium	-	1.6	-
torch	PYSEC-2024-250	medium	-	1.6	7c35874ad664e74c8e4252d67521f3986eadb0e6
torch	CVE-2025-3136	medium	-	1.6	-
torch	PYSEC-2025-197	medium	-	1.6	-
torch	CVE-2025-2998	medium	-	1.6	-
torch	PYSEC-2025-192	medium	-	1.6	-
torch	CVE-2025-46148	medium	-	1.6	-
torch	GHSA-f4hp-rmr7-r7v8	MODERATE	PyTorch is Vulnerable to Memory Consumption through pad_packed_sequence Function	1.6	-
torch	PYSEC-2025-193	MODERATE	-	1.6	-
torch	CVE-2025-2999	MODERATE	-	1.6	-
torch	GHSA-vgrw-7cvw-pwgx	MODERATE	PyTorch is vulnerable to memory corruption through its unpack_sequence function	1.6	2.9.1
torch	CVE-2025-3730	MODERATE	-	1.6	-
torch	GHSA-887c-mr87-cxwp	MODERATE	PyTorch Improper Resource Shutdown or Release vulnerability	1.6	2.8.0
torch	CVE-2025-3000	LOW	-	1.6	-
torch	PYSEC-2025-195	LOW	-	1.6	-
torch	GHSA-rrmf-rvhw-rf47	LOW	PyTorch is vulnerable to memory corruption through its torch.jit.script function	1.6	-
torch	CVE-2025-63396	low	-	1.6	-
torch	PYSEC-2025-190	LOW	-	1.6	-
torch	GHSA-qfhq-4f3w-5fph	LOW	PyTorch is vulnerable to memory corruption through its torch.lstm_cell function	1.6	2.10.0
torch	CVE-2025-3001	LOW	-	1.6	-
torch	PYSEC-2025-210	low	-	1.6	-
torch	GHSA-3749-ghw9-m3mg	LOW	PyTorch susceptible to local Denial of Service	1.6	2.7.1-rc1
torch	PYSEC-2025-194	LOW	-	1.6	-
torch	PYSEC-2025-189	LOW	-	1.6	-
torch	GHSA-c678-jfcj-6jmf	LOW	PyTorch Tuple Handler is Vulnerable to Memory Corruption through Manipulation of None Argument	1.6	-
torch	GHSA-x3gm-94wq-g975	LOW	PyTorch: Manipulation of the argument scale/zero_point leads to improper initialization via Quantized Sigmoid Module	1.6	-
torch	PYSEC-2025-191	LOW	-	1.6	-

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Review Checklist

Extra review is recommended for this update:

• Review changes for compatibility with your code
• Check release notes for breaking changes
• Run integration tests to verify service behavior
• Test in staging environment before production
• Monitor key metrics after deployment
• Approve and merge this PR

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Update Mode: all_vulns

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