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Get Started Free →Adversaries may manipulate products or product delivery mechanisms prior to receipt by a final consumer for the purpose of data or system compromise.
.claude/skills/cyberstrikeus-t1474-001-compromise-software-dependencies-and-development-tools/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | -55% | 0% |
| case-08 | ✗→✓ | ▲ Improved | -60% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -43% | 0% |
| case-12 | ✗→✓ | ▲ Improved | -43% | 0% |
| case-14 | ✗→✓ | ▲ Improved | -54% | 0% |
> Sub-technique of: T1474
Adversaries may manipulate products or product delivery mechanisms prior to receipt by a final consumer for the purpose of data or system compromise. Applications often depend on external software to function properly. Popular open source projects that are used as dependencies in many applications may be targeted as a means to add malicious code to users of the dependency.
Platforms: Android, iOS
Determine if the target mobile environment is susceptible to Compromise Software Dependencies and Development Tools by examining the target platforms (Android, iOS).
Review whether mitigations for T1474.001 are in place. If defenses are absent or misconfigured, this technique may be exploitable.
Application developers should be cautious when selecting third-party libraries to integrate into their application.
| Finding | Severity | Impact | | --------------------------------------------------------------------------- | -------- | -------------- | | Compromise Software Dependencies and Development Tools technique applicable | Low | Initial Access |
| CWE ID | Title | | ------ | ------------------------- | | CWE-20 | Improper Input Validation |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 28,818 | 46,071 | +60% | 1 | 1 | 0% | 3,662 | 4,884 | +33% | 0 | 0 | — |
case-02 | fail→fail | 28,573 | 32,108 | +12% | 1 | 1 | 0% | 3,629 | 4,757 | +31% | 0 | 0 | — |
case-03 | fail→fail | 43,246 | 40,195 | -7% | 1 | 1 | 0% | 4,030 | 5,390 | +34% | 0 | 0 | — |
case-04 | pass→pass | 30,747 | 24,401 | -21% | 1 | 1 | 0% | 3,566 | 3,647 | +2% | 0 | 0 | — |
case-05 | pass→pass | 26,077 | 28,165 | +8% | 1 | 1 | 0% | 3,191 | 4,628 | +45% | 0 | 0 | — |
case-06 | pass→pass | 22,869 | 27,725 | +21% | 1 | 1 | 0% | 3,150 | 4,554 | +45% | 0 | 0 | — |
case-07 | fail→pass | 29,748 | 29,518 | -1% | 1 | 1 | 0% | 3,860 | 1,724 | -55% | 0 | 0 | — |
case-08 | fail→pass | 20,446 | 7,929 | -61% | 1 | 1 | 0% | 2,766 | 1,105 | -60% | 0 | 0 | — |
case-09 | fail→pass | 17,609 | 2,404 | -86% | 1 | 1 | 0% | 1,946 | 1,100 | -43% | 0 | 0 | — |
case-10 | pass→pass | 12,674 | 32,469 | +156% | 1 | 1 | 0% | 1,569 | 968 | -38% | 0 | 0 | — |
case-11 | pass→pass | 6,397 | 1,326 | -79% | 1 | 1 | 0% | 1,103 | 832 | -25% | 0 | 0 | — |
case-12 | fail→pass | 18,585 | 2,676 | -86% | 1 | 1 | 0% | 1,839 | 1,041 | -43% | 0 | 0 | — |
case-13 | pass→pass | 17,766 | 8,625 | -51% | 1 | 1 | 0% | 4,066 | 1,199 | -71% | 0 | 0 | — |
case-14 | fail→pass | 20,588 | 3,231 | -84% | 1 | 1 | 0% | 2,189 | 1,005 | -54% | 0 | 0 | — |
case-15 | pass→pass | 2,881 | 7,246 | +152% | 1 | 1 | 0% | 317 | 909 | +187% | 0 | 0 | — |
case-16 | pass→pass | 12,514 | 2,316 | -81% | 1 | 1 | 0% | 1,008 | 946 | -6% | 0 | 0 | — |
case-17 | fail→pass | 31,803 | 9,173 | -71% | 1 | 1 | 0% | 1,963 | 1,248 | -36% | 0 | 0 | — |
case-18 | fail→pass | 22,023 | 5,173 | -77% | 1 | 1 | 0% | 2,494 | 1,434 | -43% | 0 | 0 | — |
case-19 | pass→pass | 15,812 | 6,702 | -58% | 1 | 1 | 0% | 1,480 | 1,607 | +9% | 0 | 0 | — |
case-20 | pass→pass | 8,958 | 7,267 | -19% | 1 | 1 | 0% | 529 | 946 | +79% | 0 | 0 | — |
case-21 | pass→pass | 20,337 | 25,046 | +23% | 1 | 1 | 0% | 1,416 | 1,026 | -28% | 0 | 0 | — |
case-22 | pass→pass | 23,908 | 9,282 | -61% | 1 | 1 | 0% | 2,659 | 1,034 | -61% | 0 | 0 | — |
case-23 | fail→pass | 15,009 | 7,333 | -51% | 1 | 1 | 0% | 1,577 | 1,045 | -34% | 0 | 0 | — |
case-24 | fail→pass | 18,527 | 7,133 | -61% | 1 | 1 | 0% | 2,398 | 1,032 | -57% | 0 | 0 | — |
case-25 | pass→pass | 8,866 | 8,353 | -6% | 1 | 1 | 0% | 980 | 1,026 | +5% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 25 cases were attempted. The headline lift of +36 percentage points is the difference between those two pass rates over the 25 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.