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mobsfscan

mobsfscan is a static analysis tool that scans Android and iOS source code (Java, Kotlin, Swift, Objective-C) for insecure patterns. It integrates MobSF security rules with semgrep and libsast pattern matchers to identify mobile app vulnerabilities before deployment.

Source: GitHub — github.com/MobSF/mobsfscan
770
GitHub stars
121
Forks
Python
Primary language
LGPL-3.0
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
RepositoryMobSF/mobsfscan
OwnerMobSF
Primary languagePython
LicenseLGPL-3.0 — OSI-approved
Stars770
Forks121
Open issues19
Latest release0.4.5 (2024-11-14)
Last updated2026-03-12
Sourcehttps://github.com/MobSF/mobsfscan

What mobsfscan is

Python-based SAST tool that performs pattern matching and semantic analysis on mobile source code, generating findings mapped to CWE, CVSS, OWASP Mobile Top 10, and MSTG. Supports multiple output formats (JSON, SARIF, SonarQube, HTML) and multiprocessing strategies for performance.

Quickstart

Get the mobsfscan source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/MobSF/mobsfscan.gitcd mobsfscan# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

CI/CD mobile security gates

Integrate into build pipelines to block commits with high-severity insecure patterns (WebView SSL issues, hardcoded credentials, insecure crypto). Exit codes and SonarQube integration enable enforcement.

Pre-release code review for teams

Run across Android/iOS codebases before submission to app stores. HTML and JSON reports provide reviewable findings tied to MSTG and CWE references for developer remediation.

Security baseline and compliance scanning

Establish consistent mobile app security posture across portfolios. Supports both Android and iOS, enabling single tool adoption for cross-platform teams.

Implementation considerations

  • Requires Python 3.7+; install via pip. No Docker image or prebuilt binary mentioned; plan environment setup for CI runners.
  • Configure rule sets via .mobsf config file; default rules may not align with all organizational standards. Review severity mappings and suppress false positives strategically.
  • Multiprocessing mode (default, billiard, thread) impacts memory and CPU; test on typical codebase sizes to avoid CI timeout or resource exhaustion.
  • Output formats (JSON, SARIF, SonarQube, HTML) enable downstream integration but require parsing logic; validate output structure before automating.

When to avoid it — and what to weigh

  • Need binary or APK/IPA analysis — mobsfscan is source-code only. If you have compiled binaries or must analyze without source, tools like MobSF (the parent framework) or Frida offer complementary approaches.
  • Require advanced interactive testing — SAST alone cannot detect runtime vulnerabilities, logic flaws, or data-flow issues across network calls. Combine with dynamic testing (DAST) or penetration testing.
  • Expect zero false positives out-of-the-box — Pattern-based and regex-driven rules will have false positives. Plan for tuning and filtering in CI/CD; requires security expertise to maintain signal-to-noise ratio.
  • Need real-time IDE integration — mobsfscan is CLI/batch-oriented. IDE plugins or linting integrations are not mentioned in available data; developers run scans separately.

License & commercial use

Licensed under LGPL-3.0 (GNU Lesser General Public License v3.0). LGPL permits proprietary and commercial use with source-code availability requirements.

LGPL-3.0 is a copyleft license. Commercial use is permitted, but if you modify mobsfscan and distribute it, you must disclose source code and license derivative work under LGPL-3.0. Requires legal review if bundling into proprietary products. Standard LGPL commercial deployment (e.g., using unmodified binary in CI/CD) is generally supported but warrants due diligence.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationAdequate
License clarityClear
Deployment complexityLow
DEV.co fitGood
Assessment confidenceHigh
Security considerations

mobsfscan is a scanning tool, not a runtime defense. Pattern-based detection is bounded by rule completeness; zero-day or obfuscated vulnerabilities may be missed. Relies on semgrep and libsast maintenance for engine security. No explicit data sanitization or sandboxing documented for untrusted input scanning. Results should be treated as advisory; human review required before blocking deployments.

Alternatives to consider

MobSF (Mobile Security Framework)

Parent framework supports both source and binary analysis (APK/IPA), dynamic testing, and API fuzzing. More comprehensive but heavier; mobsfscan is the lighter source-only subset.

Semgrep (standalone)

General-purpose SAST engine with extensive rule sets. Requires custom rule authoring for mobile patterns; mobsfscan pre-bundles mobile-specific rules.

Checkmarx / Fortify

Enterprise SAST platforms with mobile support, managed rulesets, and integration ecosystems. Higher cost and operational overhead than open-source alternatives.

Software development agency

Build on mobsfscan with DEV.co software developers

Embed mobsfscan into your CI/CD pipeline to catch insecure patterns early. Ideal for teams building or maintaining Android and iOS apps at scale. Get started with pip install mobsfscan.

Talk to DEV.co

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mobsfscan FAQ

Can mobsfscan scan compiled APKs or IPAs?
No. mobsfscan requires source code. For binary analysis, use the parent MobSF framework or other binary analysis tools.
How do I suppress false positives?
Use the .mobsf config file to customize rules and severity levels. Data on specific suppression mechanisms (e.g., inline comments) is not provided; refer to MobSF documentation or config examples.
Does mobsfscan replace manual code review or penetration testing?
No. SAST detects common insecure patterns but cannot find logic flaws, business-logic exploits, or runtime vulnerabilities. Use as a gate before human review and dynamic testing.
Can I use mobsfscan in a CI/CD pipeline?
Yes. Exit codes, JSON/SARIF output, and SonarQube integration support standard CI/CD workflows. Configure --exit-warning or --no-fail based on your policy.

Software development & web development with DEV.co

From first prototype to production, DEV.co delivers software development services around tools like mobsfscan. Our software development agency staffs experienced software developers and web developers for custom software development, web development, integrations, and ongoing support across open-source security and beyond.

Strengthen Mobile App Security with Automated Analysis

Embed mobsfscan into your CI/CD pipeline to catch insecure patterns early. Ideal for teams building or maintaining Android and iOS apps at scale. Get started with pip install mobsfscan.