Detect insecure deserialization and pickle misuse in Python projects.
npx skills add https://github.com/ersinkoc/security-check --skill sc-lang-python
Please help me install this Agent Skill. Skill: sc-lang-python Source: https://github.com/ersinkoc/security-check/tree/main Command: npx skills add https://github.com/ersinkoc/security-check --skill sc-lang-python
Python applications often suffer from insecure deserialization and unsafe pickle usage, leading to remote code execution and data compromise if untrusted data is deserialized. This skill provides Python-specific checks to identify these patterns across common runtimes and frameworks.
Run the Python security scan against this codebase to identify and remediate insecure deserialization patterns.
High-intent search queries and answers about installing and using this skill.
Scan Python code to detect insecure deserialization vulnerabilities by identifying risky pickle loads and unsafe YAML parsing patterns. This analysis reveals remote code execution risks across Django, Flask, and FastAPI projects, yielding structured findings for remediation.
Common pickle misuse patterns involve loading untrusted data streams directly via pickle or unsafe YAML, which can trigger arbitrary code execution. Analyzing data-processing scripts and framework endpoints for these risky serialization paths exposes dangerous gadget chains and data-loading operations.
Yes, this security scanning approach works with Django, Flask, and FastAPI applications to identify risky data-loading paths. It analyzes Python projects across these common runtimes and frameworks to find insecure deserialization and pickle misuse patterns within the codebase.
Run a SAST scan for unsafe YAML loading by applying Python-specific security checks to your codebase. This static analysis identifies risky data-loading paths and insecure deserialization patterns, generating structured findings aligned with the security-check pipeline for verification.
The best way to find risky serialization paths in data-processing scripts is through deep Python security scanning. This approach identifies unsafe pickle usage and insecure deserialization patterns, producing structured findings that integrate with reporting stages for subsequent verification.
balic-AI-ML-R-D-ResourcesIdentify and remediate security vulnerabilities in Python code.
n4igmeDetect insecure deserialization and XXE vulnerabilities in codebases.
ersinkocDetect insecure deserialization vulnerabilities across Python, Java, PHP, .NET, Ruby, Node.js, YAML, and XML.
MesteriisIdentify and analyze deserialization and parser security vulnerabilities in software.
