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Get Started Free →Adversaries may attempt to get a listing of backup software or configurations that are installed on a system.
.claude/skills/cyberstrikeus-t1518-002-backup-software-discovery/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | 19% | 0% |
| case-01 | ✗→✓ | ▲ Improved | 13% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -61% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -72% | 0% |
| case-11 | ✗→✓ | ▲ Improved | -65% | 0% |
> Sub-technique of: T1518
Adversaries may attempt to get a listing of backup software or configurations that are installed on a system. Adversaries may use this information to shape follow-on behaviors, such as Data Destruction, Inhibit System Recovery, or Data Encrypted for Impact.
Commands that can be used to obtain security software information are netsh, reg query with Reg, dir with cmd, and Tasklist, but other indicators of discovery behavior may be more specific to the type of software or security system the adversary is looking for, such as Veeam, Acronis, Dropbox, or Paragon.
Platforms: Windows, macOS, Linux
> Note: No Atomic Red Team tests available for this technique. See Atomic Red Team GitHub for updates.
No specific mitigations documented for this technique.
| Finding | Severity | Impact | | ---------------------------------------------- | -------- | --------- | | Backup Software Discovery technique applicable | Medium | Discovery |
| CWE ID | Title | | ------- | --------------------------------- | | CWE-200 | Exposure of Sensitive Information |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-03 | fail→pass | 23,232 | 21,779 | -6% | 1 | 1 | 0% | 3,766 | 4,469 | +19% | 0 | 0 | — |
case-02 | fail→fail | 35,254 | 26,223 | -26% | 1 | 1 | 0% | 5,302 | 5,370 | +1% | 0 | 0 | — |
case-01 | fail→pass | 36,723 | 41,749 | +14% | 1 | 1 | 0% | 5,572 | 6,271 | +13% | 0 | 0 | — |
case-04 | pass→pass | 17,499 | 4,773 | -73% | 1 | 1 | 0% | 2,045 | 1,353 | -34% | 0 | 0 | — |
case-05 | pass→pass | 21,748 | 4,654 | -79% | 1 | 1 | 0% | 2,316 | 1,257 | -46% | 0 | 0 | — |
case-06 | pass→pass | 15,787 | 8,702 | -45% | 1 | 1 | 0% | 1,801 | 1,281 | -29% | 0 | 0 | — |
case-07 | fail→pass | 11,966 | 8,407 | -30% | 1 | 1 | 0% | 2,492 | 975 | -61% | 0 | 0 | — |
case-08 | pass→pass | 30,886 | 4,210 | -86% | 1 | 1 | 0% | 4,000 | 1,352 | -66% | 0 | 0 | — |
case-09 | fail→pass | 26,560 | 7,437 | -72% | 1 | 1 | 0% | 3,791 | 1,079 | -72% | 0 | 0 | — |
case-10 | pass→pass | 15,566 | 7,961 | -49% | 1 | 1 | 0% | 2,025 | 1,119 | -45% | 0 | 0 | — |
case-11 | fail→pass | 21,581 | 3,103 | -86% | 1 | 1 | 0% | 2,739 | 967 | -65% | 0 | 0 | — |
case-12 | fail→pass | 18,295 | 7,157 | -61% | 1 | 1 | 0% | 2,230 | 1,027 | -54% | 0 | 0 | — |
case-13 | pass→pass | 20,846 | 2,002 | -90% | 1 | 1 | 0% | 2,824 | 989 | -65% | 0 | 0 | — |
case-14 | fail→pass | 30,754 | 3,069 | -90% | 1 | 1 | 0% | 6,159 | 961 | -84% | 0 | 0 | — |
case-15 | fail→pass | 17,393 | 2,182 | -87% | 1 | 1 | 0% | 1,635 | 1,075 | -34% | 0 | 0 | — |
case-16 | pass→pass | 25,188 | 6,805 | -73% | 1 | 1 | 0% | 3,913 | 964 | -75% | 0 | 0 | — |
case-17 | pass→pass | 13,711 | 2,444 | -82% | 1 | 1 | 0% | 1,663 | 1,056 | -37% | 0 | 0 | — |
case-18 | pass→pass | 12,672 | 8,163 | -36% | 1 | 1 | 0% | 1,166 | 1,045 | -10% | 0 | 0 | — |
case-19 | pass→pass | 14,961 | 7,602 | -49% | 1 | 1 | 0% | 1,937 | 1,070 | -45% | 0 | 0 | — |
case-20 | fail→pass | 13,079 | 7,247 | -45% | 1 | 1 | 0% | 1,294 | 1,034 | -20% | 0 | 0 | — |
case-21 | pass→pass | 25,832 | 30,591 | +18% | 1 | 1 | 0% | 3,709 | 4,499 | +21% | 0 | 0 | — |
case-22 | pass→pass | 24,113 | 19,134 | -21% | 1 | 1 | 0% | 2,663 | 2,906 | +9% | 0 | 0 | — |
case-23 | pass→pass | 9,065 | 7,201 | -21% | 1 | 1 | 0% | 705 | 1,627 | +131% | 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. 23 cases were attempted. The headline lift of +39 percentage points is the difference between those two pass rates over the 23 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.