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MobSF

What ChatGPT, Claude, Gemini & Grok actually say · September 2026

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The verdict

MobSF appears in 1 AI-ranked category — best position #1 for mobile sast tools for ios and android codebases.

Claude #1Gemini #3

The de facto standard for mobile app analysis — open-source, covers both iOS and Android, combines static analysis (source and compiled IPA/APK) with a manifest/entitlement/secret/hardcoded-key scan and OWASP MASVS/MASTG-mapped output; huge community, CI-friendly REST API, and it handles the reality that most engagements start from a binary, not source. Best default for the typical mobile pentester or AppSec engineer.

Gemini The undisputed gold-standard open-source tool, offering completely free, self-hosted, and offline static analysis across Android (Java/Kotlin, APK) and iOS (Swift/Objective-C, IPA) codebases, with comprehensive baseline manifest, permission, and MASVS mapping without sharing proprietary code with external vendors.

Where MobSF falls short, per the models

  • Claude Its static engine is rule/pattern-based with meaningful false positives and shallow dataflow; it is a triage-and-coverage tool, not a deep taint-tracking SAST, and needs a skilled reviewer to separate signal from noise.
  • Gemini Relies heavily on regex and pattern matching rather than deep interprocedural data-flow analysis, resulting in higher false-positive rates and an inability to trace complex multi-step data leaks.

Top alternatives per the models: NowSecure · Semgrep · Oversecured · Checkmarx One

Watch MobSF

Boards re-poll weekly and the models change their minds. One short email only when MobSF's standing moves — a rank change, a rival overtaking, or new reasoning from the models. Nothing otherwise.

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MobSF ranks #1 for best mobile sast tools for ios and android codebases by AI-model consensus. Put the badge in your README, docs or site — it updates automatically as the models re-rank.

MobSF — ranked #1 for Best mobile SAST tools for iOS and Android codebases by AI models on ModelsAgree
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Rankings are computed from what the models answer, re-polled on demand · raw reasoning shown verbatim · methodology