Skills diffdock Audit History
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Audit History

diffdock - 4 audits

Audit version 4

Latest Safe

Jan 17, 2026, 06:46 AM

The static analysis flagged 295 potential issues, but ALL are FALSE POSITIVES. The scanner incorrectly identified scientific protein sequences (GFP containing 'SAM') as Windows SAM database references, scientific paper citations as weak cryptographic algorithms, standard Python loops as C2 beacon patterns, and markdown code block syntax as shell execution. This is a legitimate molecular docking research tool with no malicious intent or security vulnerabilities.

10
Files scanned
2,493
Lines analyzed
4
findings
claude
Audited by
No security issues found

Audit version 3

Safe

Jan 17, 2026, 06:46 AM

The static analysis flagged 295 potential issues, but ALL are FALSE POSITIVES. The scanner incorrectly identified scientific protein sequences (GFP containing 'SAM') as Windows SAM database references, scientific paper citations as weak cryptographic algorithms, standard Python loops as C2 beacon patterns, and markdown code block syntax as shell execution. This is a legitimate molecular docking research tool with no malicious intent or security vulnerabilities.

10
Files scanned
2,493
Lines analyzed
4
findings
claude
Audited by
No security issues found

Audit version 2

Safe

Jan 12, 2026, 04:19 PM

The static analysis flagged numerous false positives from documentation files containing bash command examples. No actual security vulnerabilities were found in the executable code. The skill is a legitimate scientific tool for molecular docking research.

9
Files scanned
2,188
Lines analyzed
4
findings
claude
Audited by
No security issues found

Audit version 1

Low Risk

Jan 4, 2026, 05:11 PM

The skill includes local helper scripts that read and write user-specified files for validation and reporting. No network access, credential harvesting, or command execution was found. This is a legitimate scientific tool wrapper.

11
Files scanned
2,440
Lines analyzed
3
findings
claude
Audited by
Low Risk Issues (1)
Reads and writes user-specified files
The scripts read local result files and write CSV summaries, for example `with open(confidence_file) as f:` and `with open(output_path, 'w', newline='') as f:`. This is expected for validation and reporting, but it means the skill can access any file path a user provides, which could expose sensitive data if misused.