Install any skill in seconds. Free to start, no credit card required.
Get Started Free →Adversaries may insert, delete, or manipulate data in order to influence external outcomes or hide activity, thus threatening the integrity of the data.
.claude/skills/cyberstrikeus-t1565-data-manipulation/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | 13% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 80% | 0% |
| case-14 | ✗→✓ | ▲ Improved | -3% | 0% |
| case-15 | ✗→✓ | ▲ Improved | -47% | 0% |
| case-16 | ✗→✓ | ▲ Improved | 11% | 0% |
Adversaries may insert, delete, or manipulate data in order to influence external outcomes or hide activity, thus threatening the integrity of the data. By manipulating data, adversaries may attempt to affect a business process, organizational understanding, or decision making.
The type of modification and the impact it will have depends on the target application and process as well as the goals and objectives of the adversary. For complex systems, an adversary would likely need special expertise and possibly access to specialized software related to the system that would typically be gained through a prolonged information gathering campaign in order to have the desired impact.
Platforms: Linux, macOS, Windows
> Note: No Atomic Red Team tests available for this technique. See Atomic Red Team GitHub for updates.
Consider encrypting important information to reduce an adversary’s ability to perform tailored data modifications.
Consider implementing IT disaster recovery plans that contain procedures for taking regular data backups that can be used to restore organizational data. Ensure backups are stored off system and is protected from common methods adversaries may use to gain access and manipulate backups.
Identify critical business and system processes that may be targeted by adversaries and work to isolate and secure those systems against unauthorized access and tampering.
Ensure least privilege principles are applied to important information resources to reduce exposure to data manipulation risk.
| Finding | Severity | Impact | | -------------------------------------- | -------- | ------ | | Data Manipulation technique applicable | Low | Impact |
| CWE ID | Title | | ------- | --------------------------------- | | CWE-400 | Uncontrolled Resource Consumption |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 30,013 | 43,509 | +45% | 1 | 1 | 0% | 3,843 | 7,239 | +88% | 0 | 0 | — |
case-02 | fail→fail | 25,428 | 39,818 | +57% | 1 | 1 | 0% | 3,523 | 6,567 | +86% | 0 | 0 | — |
case-03 | fail→fail | 29,879 | 43,356 | +45% | 1 | 1 | 0% | 4,126 | 6,580 | +59% | 0 | 0 | — |
case-04 | pass→pass | 28,093 | 24,403 | -13% | 1 | 1 | 0% | 3,815 | 4,195 | +10% | 0 | 0 | — |
case-05 | pass→pass | 23,678 | 22,021 | -7% | 1 | 1 | 0% | 2,740 | 4,134 | +51% | 0 | 0 | — |
case-06 | pass→pass | 25,842 | 14,602 | -43% | 1 | 1 | 0% | 3,087 | 3,353 | +9% | 0 | 0 | — |
case-07 | fail→pass | 27,065 | 23,264 | -14% | 1 | 1 | 0% | 3,410 | 3,869 | +13% | 0 | 0 | — |
case-08 | pass→pass | 7,594 | 2,021 | -73% | 1 | 1 | 0% | 1,363 | 1,285 | -6% | 0 | 0 | — |
case-09 | pass→pass | 14,365 | 11,519 | -20% | 1 | 1 | 0% | 2,337 | 2,025 | -13% | 0 | 0 | — |
case-10 | fail→pass | 5,071 | 4,323 | -15% | 1 | 1 | 0% | 917 | 1,652 | +80% | 0 | 0 | — |
case-11 | pass→pass | 13,239 | 8,760 | -34% | 1 | 1 | 0% | 1,348 | 1,505 | +12% | 0 | 0 | — |
case-12 | pass→pass | 11,483 | 2,820 | -75% | 1 | 1 | 0% | 1,109 | 1,416 | +28% | 0 | 0 | — |
case-13 | pass→pass | 14,517 | 3,033 | -79% | 1 | 1 | 0% | 1,326 | 1,515 | +14% | 0 | 0 | — |
case-14 | fail→pass | 20,127 | 14,438 | -28% | 1 | 1 | 0% | 2,650 | 2,570 | -3% | 0 | 0 | — |
case-15 | fail→pass | 23,287 | 10,571 | -55% | 1 | 1 | 0% | 3,719 | 1,989 | -47% | 0 | 0 | — |
case-16 | fail→pass | 18,910 | 14,553 | -23% | 1 | 1 | 0% | 2,283 | 2,543 | +11% | 0 | 0 | — |
case-17 | pass→pass | 6,201 | 2,443 | -61% | 1 | 1 | 0% | 1,153 | 1,389 | +20% | 0 | 0 | — |
case-18 | fail→fail | 17,333 | 27,554 | +59% | 1 | 1 | 0% | 2,834 | 2,903 | +2% | 0 | 0 | — |
case-19 | fail→pass | 22,678 | 2,199 | -90% | 1 | 1 | 0% | 3,097 | 1,325 | -57% | 0 | 0 | — |
case-20 | pass→pass | 16,374 | 13,183 | -19% | 1 | 1 | 0% | 1,745 | 2,305 | +32% | 0 | 0 | — |
case-21 | fail→pass | 36,943 | 8,731 | -76% | 1 | 1 | 0% | 3,118 | 1,561 | -50% | 0 | 0 | — |
case-22 | pass→pass | 15,951 | 22,088 | +38% | 1 | 1 | 0% | 2,367 | 3,242 | +37% | 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 +32 percentage points is the difference between those two pass rates over the 22 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.