--- title: "stt trust report" type: "trust-report" slug: "jianchang512-stt" canonical_url: "https://www.graphcanon.com/tools/jianchang512-stt/trust" computed_at: "2026-07-11T12:15:37.549Z" maintenance_label: "Slowing" security_status: "findings" --- # stt trust report _Sourced [trust signals](/glossary/trust-and-signals/trust-signal) from public GitHub metadata and optional dependency [security scans](/glossary/trust-and-signals/security-scan). Not a security guarantee._ ## Maintenance - Label: Slowing (36% recency signal) - Days since last push: 170 - Last release: 2025-08-05T05:09:16Z - Methodology: github_public_v1 ## Provenance - GitHub repo id: 736697367 - Not a fork - Owner type: User - Computed at: 2026-07-11T12:15:37.549Z - Methodology: github_public_v1 ## Security scan - Status: Findings present (1 critical, 2 high, 3 medium, 21 low) · last scan 2026-07-11T12:15:43.983Z ### Findings - **low**: PyTorch susceptible to local Denial of Service (torch@2.1.2 · CVE-2025-2953 · requirements.txt) - **critical**: PyTorch: `torch.load` with `weights_only=True` leads to remote code execution (torch@2.1.2 · CVE-2025-32434 · requirements.txt) - **high**: PyTorch heap buffer overflow vulnerability (torch@2.1.2 · CVE-2024-31580 · requirements.txt) - **medium**: PyTorch Improper Resource Shutdown or Release vulnerability (torch@2.1.2 · CVE-2025-3730 · requirements.txt) - **low**: PyTorch Tuple Handler is Vulnerable to Memory Corruption through Manipulation of None Argument (torch@2.1.2 · CVE-2025-2148 · requirements.txt) - **medium**: PyTorch is Vulnerable to Memory Consumption through pad_packed_sequence Function (torch@2.1.2 · CVE-2025-2998 · requirements.txt) - **high**: Pytorch use-after-free vulnerability (torch@2.1.2 · CVE-2024-31583 · requirements.txt) - **low**: PyTorch is vulnerable to memory corruption through its torch.lstm_cell function (torch@2.1.2 · CVE-2025-3001 · requirements.txt) - **low**: PyTorch is vulnerable to memory corruption through its torch.jit.script function (torch@2.1.2 · CVE-2025-3000 · requirements.txt) - **medium**: PyTorch is vulnerable to memory corruption through its unpack_sequence function (torch@2.1.2 · CVE-2025-2999 · requirements.txt) - **low**: PyTorch: Manipulation of the argument scale/zero_point leads to improper initialization via Quantized Sigmoid Module (torch@2.1.2 · CVE-2025-2149 · requirements.txt) - **low**: PYSEC-2024-250 (torch@2.1.2 · CVE-2024-31584 · requirements.txt) - **low**: PYSEC-2024-251 (torch@2.1.2 · CVE-2024-31583 · requirements.txt) - **low**: PYSEC-2024-252 (torch@2.1.2 · CVE-2024-31580 · requirements.txt) - **low**: PYSEC-2024-259 (torch@2.1.2 · CVE-2024-48063 · requirements.txt) - **low**: PYSEC-2025-191 (torch@2.1.2 · CVE-2025-2953 · requirements.txt) - **low**: PYSEC-2025-198 (torch@2.1.2 · CVE-2025-46148 · requirements.txt) - **low**: PYSEC-2025-203 (torch@2.1.2 · CVE-2025-55551 · requirements.txt) - **low**: PYSEC-2025-204 (torch@2.1.2 · CVE-2025-55552 · requirements.txt) - **low**: PYSEC-2025-205 (torch@2.1.2 · CVE-2025-55553 · requirements.txt) - **low**: PYSEC-2025-206 (torch@2.1.2 · CVE-2025-55554 · requirements.txt) - **low**: PYSEC-2025-207 (torch@2.1.2 · CVE-2025-55557 · requirements.txt) - **low**: PYSEC-2025-208 (torch@2.1.2 · CVE-2025-55558 · requirements.txt) - **low**: PYSEC-2025-209 (torch@2.1.2 · CVE-2025-55560 · requirements.txt) - **low**: PYSEC-2025-41 (torch@2.1.2 · CVE-2025-32434 · requirements.txt) - **low**: PYSEC-2026-139 (torch@2.1.2 · CVE-2026-4538 · requirements.txt) - **low**: PyTorch Improper Resource Shutdown or Release vulnerability (torch@2.1.2 · CVE-2025-3730 · requirements.txt) ## Method and caveats These are heuristics from public GitHub data and optional dependency scans, sourced and dated. "No criticals found on 2026-07-11" is not a guarantee of safety. See the full methodology: [/trust-methodology](/trust-methodology.md). ## Common questions ### Is stt maintained? GraphCanon rates stt "Slowing" (36% maintenance signal from public GitHub metadata, computed today). Last push was 170 days ago. This is a recency heuristic, not a guarantee the project will stay maintained. ### Is stt safe to use? Last scanned today (deps profile). Status: 1 critical, 2 high, 3 medium, 21 low - 1 critical, 2 high, 3 medium, 21 low finding(s) in the latest scan. GraphCanon does not claim the project is safe or vulnerability-free; review findings on the trust report. GraphCanon does not certify stt as safe - review maintenance, provenance, and scan findings on this page before adopting. ### Is stt a fork? No. stt is not flagged as a fork in GitHub metadata at the time of the last refresh. ### Does stt have known security vulnerabilities? Last scanned today (deps profile). Status: 1 critical, 2 high, 3 medium, 21 low - 1 critical, 2 high, 3 medium, 21 low finding(s) in the latest scan. GraphCanon does not claim the project is safe or vulnerability-free; review findings on the trust report. ### How often is the stt trust report updated? Trust signals refresh on GitHub ingest/refresh cycles and optional dependency/MCP scans. This report was computed today (methodology github_public_v1). ### What does GraphCanon never claim about stt? We never publish a composite safety grade, pen-test endorsement, or "verified secure" label for stt. Signals are sourced heuristics with explicit limits - see [trust methodology](/trust-methodology). ### How does GraphCanon assess trust for stt? Signals are sourced from public GitHub metadata and optional dependency/MCP manifest scans, each tagged with methodology version and computed date. GraphCanon does not publish a composite safety grade. Read [trust methodology](/trust-methodology) for full scope and limits. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/tools/jianchang512-stt/trust`](/api/graphcanon/tools/jianchang512-stt/trust) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_