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Get Started Free →Adversaries may encode data with a non-standard data encoding system to make the content of command and control traffic more difficult to detect.
.claude/skills/cyberstrikeus-t1132-002-non-standard-encoding/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 42% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -1% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -34% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -27% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 3% | 0% |
> Sub-technique of: T1132
Adversaries may encode data with a non-standard data encoding system to make the content of command and control traffic more difficult to detect. Command and control (C2) information can be encoded using a non-standard data encoding system that diverges from existing protocol specifications. Non-standard data encoding schemes may be based on or related to standard data encoding schemes, such as a modified Base64 encoding for the message body of an HTTP request.
Platforms: ESXi, Linux, macOS, Windows
> Note: No Atomic Red Team tests available for this technique. See Atomic Red Team GitHub for updates.
Network intrusion detection and prevention systems that use network signatures to identify traffic for specific adversary malware can be used to mitigate activity at the network level. Signatures are often for unique indicators within protocols and may be based on the specific obfuscation technique used by a particular adversary or tool, and will likely be different across various malware families and versions. Adversaries will likely change tool C2 signatures over time or construct protocols in such a way as to avoid detection by common defensive tools.
| Finding | Severity | Impact | | ------------------------------------------ | -------- | ------------------- | | Non-Standard Encoding technique applicable | Low | Command And Control |
| CWE ID | Title | | ------- | ---------------------------------- | | CWE-300 | Channel Accessible by Non-Endpoint |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-19 | pass→pass | 15,987 | 15,749 | -1% | 1 | 1 | 0% | 1,545 | 2,544 | +65% | 0 | 0 | — |
case-01 | fail→fail | 25,079 | 43,114 | +72% | 1 | 1 | 0% | 3,727 | 6,776 | +82% | 0 | 0 | — |
case-02 | fail→pass | 30,222 | 40,627 | +34% | 1 | 1 | 0% | 5,235 | 7,447 | +42% | 0 | 0 | — |
case-03 | fail→fail | 34,094 | 47,172 | +38% | 1 | 1 | 0% | 4,565 | 6,798 | +49% | 0 | 0 | — |
case-04 | fail→pass | 21,063 | 12,834 | -39% | 1 | 1 | 0% | 2,903 | 2,884 | -1% | 0 | 0 | — |
case-05 | pass→pass | 30,969 | 3,771 | -88% | 1 | 1 | 0% | 5,536 | 1,445 | -74% | 0 | 0 | — |
case-06 | pass→pass | 5,970 | 8,807 | +48% | 1 | 1 | 0% | 1,190 | 1,488 | +25% | 0 | 0 | — |
case-07 | pass→pass | 9,319 | 4,428 | -52% | 1 | 1 | 0% | 1,579 | 1,488 | -6% | 0 | 0 | — |
case-08 | pass→pass | 18,169 | 14,280 | -21% | 1 | 1 | 0% | 2,453 | 2,128 | -13% | 0 | 0 | — |
case-09 | fail→pass | 10,370 | 9,484 | -9% | 1 | 1 | 0% | 1,900 | 1,261 | -34% | 0 | 0 | — |
case-10 | fail→pass | 14,707 | 7,019 | -52% | 1 | 1 | 0% | 1,674 | 1,228 | -27% | 0 | 0 | — |
case-11 | fail→pass | 12,124 | 7,029 | -42% | 1 | 1 | 0% | 1,207 | 1,248 | +3% | 0 | 0 | — |
case-12 | pass→pass | 16,601 | 8,616 | -48% | 1 | 1 | 0% | 1,445 | 1,258 | -13% | 0 | 0 | — |
case-18 | fail→pass | 13,965 | 3,540 | -75% | 1 | 1 | 0% | 1,480 | 1,191 | -20% | 0 | 0 | — |
case-13 | pass→pass | 21,529 | 27,846 | +29% | 1 | 1 | 0% | 3,051 | 4,104 | +35% | 0 | 0 | — |
case-14 | pass→pass | 7,946 | 8,321 | +5% | 1 | 1 | 0% | 341 | 1,050 | +208% | 0 | 0 | — |
case-15 | pass→pass | 23,932 | 23,756 | -1% | 1 | 1 | 0% | 2,671 | 3,704 | +39% | 0 | 0 | — |
case-16 | fail→pass | 23,508 | 18,372 | -22% | 1 | 1 | 0% | 2,795 | 2,887 | +3% | 0 | 0 | — |
case-17 | pass→fail | 14,789 | 6,612 | -55% | 1 | 1 | 0% | 1,720 | 1,771 | +3% | 0 | 0 | — |
case-20 | fail→pass | 8,331 | 7,953 | -5% | 1 | 1 | 0% | 1,200 | 1,219 | +2% | 0 | 0 | — |
case-21 | pass→pass | 21,417 | 14,527 | -32% | 1 | 1 | 0% | 2,377 | 2,656 | +12% | 0 | 0 | — |
case-22 | pass→pass | 15,965 | 20,300 | +27% | 1 | 1 | 0% | 2,622 | 3,522 | +34% | 0 | 0 | — |
case-23 | pass→pass | 16,019 | 15,326 | -4% | 1 | 1 | 0% | 2,122 | 2,745 | +29% | 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 +30 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.