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Get Started Free →Adversaries may look for details about the network configuration and settings, such as IP and/or MAC addresses, of devices they access or through information discovery of remote systems.
.claude/skills/cyberstrikeus-t1422-system-network-configuration-discovery/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-12 | ✗→✓ | ▲ Improved | -64% | 0% |
| case-13 | ✗→✓ | ▲ Improved | -32% | 0% |
| case-14 | ✗→✓ | ▲ Improved | -53% | 0% |
| case-23 | ✗→✓ | ▲ Improved | -46% | 0% |
| case-05 | ✓→✓ | ＝ Same ✓ | 20% | 0% |
Adversaries may look for details about the network configuration and settings, such as IP and/or MAC addresses, of devices they access or through information discovery of remote systems.
Adversaries may use the information from System Network Configuration Discovery during automated discovery to shape follow-on behaviors, including determining certain access within the target network and what actions to do next.
On Android, details of onboard network interfaces are accessible to apps through the java.net.NetworkInterface class. Previously, the Android TelephonyManager class could be used to gather telephony-related device identifiers, information such as the IMSI, IMEI, and phone number. However, starting with Android 10, only preloaded, carrier, the default SMS, or device and profile owner applications can access the telephony-related device identifiers.
On iOS, gathering network configuration information is not possible without root access.
Adversaries may use the information from System Network Configuration Discovery during automated discovery to shape follow-on behaviors, including determining certain access within the target network and what actions to do next.
Platforms: Android, iOS
Determine if the target mobile environment is susceptible to System Network Configuration Discovery by examining the target platforms (Android, iOS).
Review whether mitigations for T1422 are in place. If defenses are absent or misconfigured, this technique may be exploitable.
Android 10 introduced changes that prevent normal applications from accessing sensitive device identifiers.
| Finding | Severity | Impact | | ----------------------------------------------------------- | -------- | --------- | | System Network Configuration 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-01 | fail→fail | 42,037 | 36,293 | -14% | 1 | 1 | 0% | 4,969 | 5,456 | +10% | 0 | 0 | — |
case-02 | fail→fail | 32,422 | 24,070 | -26% | 1 | 1 | 0% | 4,457 | 3,706 | -17% | 0 | 0 | — |
case-03 | fail→fail | 32,918 | 41,545 | +26% | 1 | 1 | 0% | 4,375 | 5,942 | +36% | 0 | 0 | — |
case-04 | fail→fail | 21,236 | 24,326 | +15% | 1 | 1 | 0% | 2,294 | 2,020 | -12% | 0 | 0 | — |
case-05 | pass→pass | 23,676 | 26,631 | +12% | 1 | 1 | 0% | 2,930 | 3,502 | +20% | 0 | 0 | — |
case-06 | fail→fail | 20,927 | 26,981 | +29% | 1 | 1 | 0% | 2,674 | 3,774 | +41% | 0 | 0 | — |
case-07 | pass→pass | 13,266 | 7,508 | -43% | 1 | 1 | 0% | 1,332 | 950 | -29% | 0 | 0 | — |
case-08 | pass→pass | 16,938 | 15,800 | -7% | 1 | 1 | 0% | 1,761 | 2,136 | +21% | 0 | 0 | — |
case-09 | fail→fail | 22,022 | 19,068 | -13% | 1 | 1 | 0% | 2,525 | 2,867 | +14% | 0 | 0 | — |
case-10 | pass→pass | 4,538 | 7,763 | +71% | 1 | 1 | 0% | 631 | 893 | +42% | 0 | 0 | — |
case-11 | pass→pass | 10,970 | 9,561 | -13% | 1 | 1 | 0% | 1,847 | 997 | -46% | 0 | 0 | — |
case-12 | fail→pass | 19,940 | 7,787 | -61% | 1 | 1 | 0% | 2,822 | 1,028 | -64% | 0 | 0 | — |
case-18 | pass→pass | 20,821 | 10,453 | -50% | 1 | 1 | 0% | 2,136 | 2,182 | +2% | 0 | 0 | — |
case-13 | fail→pass | 9,185 | 3,072 | -67% | 1 | 1 | 0% | 1,472 | 995 | -32% | 0 | 0 | — |
case-14 | fail→pass | 18,268 | 7,038 | -61% | 1 | 1 | 0% | 1,927 | 897 | -53% | 0 | 0 | — |
case-15 | pass→pass | 16,364 | 22,360 | +37% | 1 | 1 | 0% | 2,726 | 3,874 | +42% | 0 | 0 | — |
case-16 | pass→pass | 21,258 | 18,647 | -12% | 1 | 1 | 0% | 2,302 | 2,528 | +10% | 0 | 0 | — |
case-17 | pass→pass | 9,399 | 7,263 | -23% | 1 | 1 | 0% | 501 | 853 | +70% | 0 | 0 | — |
case-19 | pass→pass | 16,543 | 11,331 | -32% | 1 | 1 | 0% | 1,670 | 1,498 | -10% | 0 | 0 | — |
case-20 | pass→pass | 24,964 | 19,954 | -20% | 1 | 1 | 0% | 2,616 | 3,020 | +15% | 0 | 0 | — |
case-21 | fail→fail | 30,170 | 22,217 | -26% | 1 | 1 | 0% | 3,331 | 3,555 | +7% | 0 | 0 | — |
case-22 | pass→pass | 18,162 | 17,453 | -4% | 1 | 1 | 0% | 2,243 | 2,230 | -1% | 0 | 0 | — |
case-23 | fail→pass | 22,961 | 10,344 | -55% | 1 | 1 | 0% | 2,438 | 1,313 | -46% | 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 +17 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.