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Get Started Free →Adversaries may use scripts automatically executed at boot or logon initialization to establish persistence.
.claude/skills/cyberstrikeus-t1398-boot-or-logon-initialization-scripts/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | 10% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 27% | 0% |
| case-06 | ✗→✓ | ▲ Improved | -37% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -15% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 18% | 0% |
Adversaries may use scripts automatically executed at boot or logon initialization to establish persistence. Initialization scripts are part of the underlying operating system and are not accessible to the user unless the device has been rooted or jailbroken.
Platforms: Android, iOS
Determine if the target mobile environment is susceptible to Boot or Logon Initialization Scripts by examining the target platforms (Android, iOS).
Review whether mitigations for T1398 are in place. If defenses are absent or misconfigured, this technique may be exploitable.
Security updates frequently contain fixes for vulnerabilities that could be leveraged to modify protected operating system files.
Android and iOS include system partition integrity mechanisms that could detect unauthorized modifications.
Device attestation could detect devices with unauthorized or unsafe modifications.
A locked bootloader could prevent unauthorized modifications to protected operating system files.
| Finding | Severity | Impact | | --------------------------------------------------------- | -------- | ----------- | | Boot or Logon Initialization Scripts technique applicable | Low | Persistence |
| CWE ID | Title | | ------- | ----------------------------- | | CWE-276 | Incorrect Default Permissions |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 29,359 | 32,033 | +9% | 1 | 1 | 0% | 4,122 | 4,860 | +18% | 0 | 0 | — |
case-02 | fail→fail | 24,679 | 28,486 | +15% | 1 | 1 | 0% | 2,957 | 3,725 | +26% | 0 | 0 | — |
case-03 | fail→pass | 30,875 | 29,075 | -6% | 1 | 1 | 0% | 4,260 | 4,671 | +10% | 0 | 0 | — |
case-04 | fail→pass | 22,854 | 23,659 | +4% | 1 | 1 | 0% | 2,663 | 3,383 | +27% | 0 | 0 | — |
case-05 | pass→pass | 16,627 | 12,045 | -28% | 1 | 1 | 0% | 2,670 | 1,740 | -35% | 0 | 0 | — |
case-06 | fail→pass | 10,796 | 9,853 | -9% | 1 | 1 | 0% | 1,902 | 1,205 | -37% | 0 | 0 | — |
case-07 | fail→pass | 8,011 | 9,116 | +14% | 1 | 1 | 0% | 1,495 | 1,265 | -15% | 0 | 0 | — |
case-08 | pass→pass | 17,068 | 12,037 | -29% | 1 | 1 | 0% | 2,189 | 1,501 | -31% | 0 | 0 | — |
case-09 | fail→pass | 11,574 | 9,719 | -16% | 1 | 1 | 0% | 1,093 | 1,295 | +18% | 0 | 0 | — |
case-21 | pass→pass | 24,609 | 20,975 | -15% | 1 | 1 | 0% | 2,719 | 2,877 | +6% | 0 | 0 | — |
case-10 | fail→pass | 31,947 | 7,576 | -76% | 1 | 1 | 0% | 6,013 | 987 | -84% | 0 | 0 | — |
case-11 | fail→pass | 10,567 | 5,114 | -52% | 1 | 1 | 0% | 1,758 | 1,123 | -36% | 0 | 0 | — |
case-12 | fail→pass | 38,806 | 7,868 | -80% | 1 | 1 | 0% | 7,610 | 991 | -87% | 0 | 0 | — |
case-13 | pass→pass | 20,519 | 18,296 | -11% | 1 | 1 | 0% | 2,074 | 2,315 | +12% | 0 | 0 | — |
case-14 | fail→pass | 26,437 | 28,312 | +7% | 1 | 1 | 0% | 3,289 | 4,023 | +22% | 0 | 0 | — |
case-15 | fail→pass | 13,932 | 9,942 | -29% | 1 | 1 | 0% | 2,352 | 1,351 | -43% | 0 | 0 | — |
case-16 | pass→pass | 19,260 | 4,466 | -77% | 1 | 1 | 0% | 2,525 | 1,321 | -48% | 0 | 0 | — |
case-17 | pass→pass | 31,238 | 34,510 | +10% | 1 | 1 | 0% | 4,291 | 4,785 | +12% | 0 | 0 | — |
case-18 | pass→pass | 24,031 | 35,624 | +48% | 1 | 1 | 0% | 3,800 | 5,474 | +44% | 0 | 0 | — |
case-19 | pass→pass | 23,240 | 21,855 | -6% | 1 | 1 | 0% | 3,099 | 3,834 | +24% | 0 | 0 | — |
case-20 | pass→pass | 32,055 | 23,866 | -26% | 1 | 1 | 0% | 3,304 | 3,544 | +7% | 0 | 0 | — |
case-22 | fail→pass | 18,154 | 10,620 | -42% | 1 | 1 | 0% | 2,067 | 1,369 | -34% | 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. 22 cases were attempted. The headline lift of +50 percentage points is the difference between those two pass rates over the 22 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.