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Get Started Free →An adversary may use a cloud service dashboard GUI with stolen credentials to gain useful information from an operational cloud environment, such as specific services, resources, and features.
.claude/skills/cyberstrikeus-t1538-cloud-service-dashboard/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | -38% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 20% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -25% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 45% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 37% | 0% |
An adversary may use a cloud service dashboard GUI with stolen credentials to gain useful information from an operational cloud environment, such as specific services, resources, and features. For example, the GCP Command Center can be used to view all assets, review findings of potential security risks, and run additional queries, such as finding public IP addresses and open ports.
Depending on the configuration of the environment, an adversary may be able to enumerate more information via the graphical dashboard than an API. This also allows the adversary to gain information without manually making any API requests.
Platforms: IaaS, SaaS, Office Suite, Identity Provider
> Note: No Atomic Red Team tests available for this technique. See Atomic Red Team GitHub for updates.
Enforce the principle of least-privilege by limiting dashboard visibility to only the resources required. This may limit the discovery value of the dashboard in the event of a compromised account.
| Finding | Severity | Impact | | -------------------------------------------- | -------- | --------- | | Cloud Service Dashboard technique applicable | High | 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-02 | fail→fail | 27,191 | 26,149 | -4% | 1 | 1 | 0% | 3,611 | 4,994 | +38% | 0 | 0 | — |
case-03 | fail→pass | 23,506 | 6,216 | -74% | 1 | 1 | 0% | 2,946 | 1,818 | -38% | 0 | 0 | — |
case-01 | fail→fail | 36,459 | 40,996 | +12% | 1 | 1 | 0% | 4,987 | 6,628 | +33% | 0 | 0 | — |
case-04 | pass→pass | 19,805 | 14,138 | -29% | 1 | 1 | 0% | 3,429 | 1,322 | -61% | 0 | 0 | — |
case-05 | pass→pass | 19,816 | 2,967 | -85% | 1 | 1 | 0% | 2,337 | 1,188 | -49% | 0 | 0 | — |
case-06 | fail→pass | 14,357 | 13,187 | -8% | 1 | 1 | 0% | 2,273 | 2,725 | +20% | 0 | 0 | — |
case-07 | fail→pass | 19,470 | 11,357 | -42% | 1 | 1 | 0% | 2,217 | 1,673 | -25% | 0 | 0 | — |
case-08 | pass→pass | 9,559 | 6,710 | -30% | 1 | 1 | 0% | 1,690 | 1,866 | +10% | 0 | 0 | — |
case-09 | fail→pass | 13,102 | 13,631 | +4% | 1 | 1 | 0% | 1,459 | 2,110 | +45% | 0 | 0 | — |
case-10 | pass→pass | 9,322 | 4,021 | -57% | 1 | 1 | 0% | 1,695 | 1,107 | -35% | 0 | 0 | — |
case-11 | pass→pass | 22,598 | 23,105 | +2% | 1 | 1 | 0% | 2,424 | 3,237 | +34% | 0 | 0 | — |
case-12 | pass→pass | 21,701 | 19,053 | -12% | 1 | 1 | 0% | 2,463 | 2,744 | +11% | 0 | 0 | — |
case-13 | pass→pass | 17,004 | 9,196 | -46% | 1 | 1 | 0% | 1,844 | 1,250 | -32% | 0 | 0 | — |
case-14 | fail→pass | 18,594 | 19,520 | +5% | 1 | 1 | 0% | 2,140 | 2,940 | +37% | 0 | 0 | — |
case-15 | pass→pass | 20,768 | 17,659 | -15% | 1 | 1 | 0% | 2,448 | 3,134 | +28% | 0 | 0 | — |
case-16 | pass→pass | 17,158 | 17,502 | +2% | 1 | 1 | 0% | 1,948 | 2,711 | +39% | 0 | 0 | — |
case-17 | fail→pass | 21,954 | 24,766 | +13% | 1 | 1 | 0% | 2,983 | 4,154 | +39% | 0 | 0 | — |
case-18 | pass→pass | 15,989 | 12,350 | -23% | 1 | 1 | 0% | 1,609 | 1,902 | +18% | 0 | 0 | — |
case-19 | pass→pass | 20,690 | 20,642 | -0% | 1 | 1 | 0% | 2,835 | 3,203 | +13% | 0 | 0 | — |
case-20 | pass→pass | 8,458 | 7,042 | -17% | 1 | 1 | 0% | 1,594 | 1,957 | +23% | 0 | 0 | — |
case-21 | pass→pass | 15,516 | 13,567 | -13% | 1 | 1 | 0% | 1,889 | 2,228 | +18% | 0 | 0 | — |
case-22 | pass→pass | 6,693 | 18,700 | +179% | 1 | 1 | 0% | 1,335 | 2,260 | +69% | 0 | 0 | — |
case-23 | pass→pass | 6,271 | 12,028 | +92% | 1 | 1 | 0% | 1,138 | 1,744 | +53% | 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 +26 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.