Scan report

guanguans / music-dl

Vulnerability Medium

Could an attacker exploit mistakes in this code?

40 risk score

Real issues worth reviewing before you rely on this code.

High
1
Medium
21
Low
0

Sources: Bandit, Semgrep, pip-audit

Malicious pattern Safe

Does this code look like it is trying to cause harm?

0 risk score

No issues of this kind were found.

High
0
Medium
0
Low
0

Sources: YARA, ClamAV, GuardDog, dependency checker

Findings overview
22 total findings
Likely real
21
Uncertain
0
Likely noise
1

The risk classifier rates every finding for how likely it is to be a real issue. Likely noise still counts, just much less.

What we found, in plain English

This repository has a medium vulnerability score of 40, which means there are some insecure coding patterns that an attacker could potentially exploit if they gain access to the code. However, the scan found no signs of malicious intent or hidden malware in the files themselves, so the code is not actively dangerous right now. The main issues identified are related to how the project handles secrets and package updates rather than intentional attacks. One specific concern involves using variable interpolation with GitHub context data, which could theoretically allow an attacker to inject their own code into the runner. Another issue is that the Dependabot configuration does not set a cooldown period for new packages, meaning unstable or malicious updates could be applied without waiting. These findings represent ordinary insecure coding practices rather than signs of deliberate sabotage. While the repository is safe from immediate malicious attacks, developers should address these two specific issues to improve security posture and prevent future risks.

Written by a local language model from the findings below. The risk scores come from the classifier, not from this summary.

Detections by engine

  • Semgrep 22

    Pattern-based code analysis · Vulnerability

Score over time

Overall score each time this repository was scanned.

Findings

Highest severity first. Select a finding to see the code and what it means.