BC performing-android-app-static-analysis-with-mobsf
Performs automated static analysis of Android applications using Mobile Security Framework (MobSF) to identify hardcoded secrets, insecure permissions, vulnerable components, weak cryptography, and code-level security flaws without executing the application. Use when assessing Android APK/AAB files for security vulnerabilities before deployment, during penetration testing, or as part of CI/CD security gates. Activates for requests involving Android static analysis, MobSF scanning, APK security assessment, or mobile application code review.
Performs automated static analysis of Android applications using Mobile Security Framework (MobSF) to identify hardcoded secrets, insecure permissions…
As a process C 55/100 · Has gaps — weak spots: result and completion, failures and branches, running it twice
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 2
✓ No critical or high findings
Medium and low: 2
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low Risky intent
intent-offensive-securitySKILL.md:7Offensive-security / dual-use content (legitimate for authorised testing; review intended use)vulnerabilities before deployment, during penetration testing, or as part of CI/CD
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low Risky intent
intent-offensive-securitySKILL.md:42Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- Performing initial triage of Android applications during penetration testing engagements
Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "domain" - note
frontmatter-keyunknown frontmatter key "subdomain" - note
frontmatter-keyunknown frontmatter key "nist_csf" - note
frontmatter-keyunknown frontmatter key "mitre_attack"
Process rating: all ten parameters 55/100
- 0Result and completion. Does not say what the result is
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 2 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 31 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1607 tokens
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- -43 reference files, but SKILL.md never points to them: the model will not open them
- -32 of 2 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 545: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 31 items
- +4Has examples (5 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.