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Get Started Free →Adversaries may search content delivery network (CDN) data about victims that can be used during targeting.
.claude/skills/cyberstrikeus-t1596-004-cdns/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-14 | ✗→✓ | ▲ Improved | -39% | 0% |
| case-15 | ✗→✓ | ▲ Improved | -75% | 0% |
| case-16 | ✗→✓ | ▲ Improved | -21% | 0% |
| case-19 | ✗→✓ | ▲ Improved | -45% | 0% |
| case-02 | ✓→✗ | ▼ Worse | 36% | 0% |
> Sub-technique of: T1596
Adversaries may search content delivery network (CDN) data about victims that can be used during targeting. CDNs allow an organization to host content from a distributed, load balanced array of servers. CDNs may also allow organizations to customize content delivery based on the requestor’s geographical region.
Adversaries may search CDN data to gather actionable information. Threat actors can use online resources and lookup tools to harvest information about content servers within a CDN. Adversaries may also seek and target CDN misconfigurations that leak sensitive information not intended to be hosted and/or do not have the same protection mechanisms (ex: login portals) as the content hosted on the organization’s website. Information from these sources may reveal opportunities for other forms of reconnaissance (ex: Active Scanning or Search Open Websites/Domains), establishing operational resources (ex: Acquire Infrastructure or Compromise Infrastructure), and/or initial access (ex: Drive-by Compromise).
Platforms: PRE
> Note: No Atomic Red Team tests available for this technique. See Atomic Red Team GitHub for updates.
This technique cannot be easily mitigated with preventive controls since it is based on behaviors performed outside of the scope of enterprise defenses and controls. Efforts should focus on minimizing the amount and sensitivity of data available to external parties.
| Finding | Severity | Impact | | ------------------------- | -------- | -------------- | | CDNs technique applicable | Low | Reconnaissance |
| 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 | 32,686 | 26,650 | -18% | 1 | 1 | 0% | 3,679 | 3,703 | +1% | 0 | 0 | — |
case-02 | pass→fail | 28,439 | 35,628 | +25% | 1 | 1 | 0% | 4,193 | 5,695 | +36% | 0 | 0 | — |
case-03 | fail→fail | 33,137 | 25,687 | -22% | 1 | 1 | 0% | 5,400 | 3,965 | -27% | 0 | 0 | — |
case-04 | pass→pass | 17,435 | 13,203 | -24% | 1 | 1 | 0% | 1,997 | 2,077 | +4% | 0 | 0 | — |
case-05 | pass→pass | 10,133 | 8,569 | -15% | 1 | 1 | 0% | 779 | 1,089 | +40% | 0 | 0 | — |
case-06 | pass→pass | 9,127 | 7,236 | -21% | 1 | 1 | 0% | 747 | 1,055 | +41% | 0 | 0 | — |
case-07 | pass→pass | 18,447 | 10,979 | -40% | 1 | 1 | 0% | 2,001 | 1,704 | -15% | 0 | 0 | — |
case-08 | pass→pass | 22,039 | 7,329 | -67% | 1 | 1 | 0% | 2,190 | 1,028 | -53% | 0 | 0 | — |
case-09 | pass→pass | 22,229 | 10,485 | -53% | 1 | 1 | 0% | 3,032 | 2,493 | -18% | 0 | 0 | — |
case-10 | pass→pass | 7,914 | 6,538 | -17% | 1 | 1 | 0% | 504 | 958 | +90% | 0 | 0 | — |
case-11 | pass→pass | 14,105 | 17,282 | +23% | 1 | 1 | 0% | 1,338 | 2,561 | +91% | 0 | 0 | — |
case-12 | fail→fail | 18,601 | 13,630 | -27% | 1 | 1 | 0% | 2,440 | 2,818 | +15% | 0 | 0 | — |
case-13 | fail→fail | 17,218 | 10,225 | -41% | 1 | 1 | 0% | 1,912 | 2,415 | +26% | 0 | 0 | — |
case-14 | fail→pass | 16,961 | 7,428 | -56% | 1 | 1 | 0% | 1,848 | 1,125 | -39% | 0 | 0 | — |
case-20 | pass→pass | 12,830 | 9,523 | -26% | 1 | 1 | 0% | 1,889 | 2,165 | +15% | 0 | 0 | — |
case-15 | fail→pass | 32,539 | 2,909 | -91% | 1 | 1 | 0% | 5,033 | 1,283 | -75% | 0 | 0 | — |
case-16 | fail→pass | 8,396 | 2,627 | -69% | 1 | 1 | 0% | 1,282 | 1,016 | -21% | 0 | 0 | — |
case-17 | fail→fail | 24,506 | 22,812 | -7% | 1 | 1 | 0% | 2,686 | 3,193 | +19% | 0 | 0 | — |
case-18 | pass→pass | 16,523 | 13,357 | -19% | 1 | 1 | 0% | 1,694 | 2,040 | +20% | 0 | 0 | — |
case-19 | fail→pass | 15,782 | 2,213 | -86% | 1 | 1 | 0% | 1,851 | 1,023 | -45% | 0 | 0 | — |
case-21 | pass→pass | 25,727 | 28,274 | +10% | 1 | 1 | 0% | 3,255 | 4,535 | +39% | 0 | 0 | — |
case-22 | pass→pass | 21,990 | 24,090 | +10% | 1 | 1 | 0% | 2,530 | 3,582 | +42% | 0 | 0 | — |
case-23 | pass→pass | 22,377 | 22,283 | -0% | 1 | 1 | 0% | 2,959 | 3,645 | +23% | 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 +13 percentage points is the difference between those two pass rates over the 23 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
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.