Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add meltedinhex/analyst-ai-pack --skill profiling-a-threat-actor-from-ttpsgit clone --depth 1 https://github.com/meltedinhex/analyst-ai-packWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/profiling-a-threat-actor-from-ttps)<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/profiling-a-threat-actor-from-ttps"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/profiling-a-threat-actor-from-ttps/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/profiling-a-threat-actor-from-ttps"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/profiling-a-threat-actor-from-ttps.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00068 | $0.00635 |
| Opus 5 | $0.00034 | $0.00318 |
| Sonnet 5 | $0.00014 | $0.00127 |
| Haiku 4.5 | $0.00007 | $0.00064 |
Grade A, and why
profiling-a-threat-actor-from-ttps scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Profiling a Threat Actor From TTPs
When to Use
- You have a set of observed ATT&CK techniques from an intrusion and want to build a TTP profile and compare it against known-group technique sets for candidate attribution.
- You are estimating similarity, not asserting attribution.
Do not use technique overlap as confirmed attribution — many groups share common techniques. Present candidates with similarity scores and the need for corroborating intel.
Prerequisites
- Observed technique IDs from the intrusion and a reference of group→techniques (CSV/JSON).
Workflow
Step 1: Build the observed TTP profile
Collect the deduplicated set of observed ATT&CK technique IDs (including sub-techniques).
Step 2: Compare against known groups
python scripts/analyst.py compare --observed observed.txt --groups groups.json
Computes Jaccard and overlap-coefficient similarity between the observed set and each group's technique set, ranking candidate groups.
Step 3: Weigh distinctive techniques
Prioritize matches on less-common techniques (shared rare TTPs are stronger signals than ubiquitous ones).
Step 4: Document
Report ranked candidates with similarity scores, the overlapping techniques, and an explicit low/medium confidence — never definitive attribution from TTPs alone.
Validation
- Similarity is computed on technique-ID sets (sub-techniques included).
- Candidates are ranked by both Jaccard and overlap coefficient.
- Output states confidence and lists the overlapping techniques.
Pitfalls
- Over-attributing on common techniques (T1059, T1027) shared by most groups.
- Reference group data being incomplete or out of date.
- Treating a single high overlap as proof without corroborating intel.
References
- See
references/api-reference.mdfor the comparison tool. - ATT&CK Groups and Navigator references (linked in frontmatter).
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 86 lines · 68 tokens per session scan A 315685dd969d
profiling-a-threat-actor-from-ttps is a skill published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 68 tokens to every session and 635 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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