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 hunting-anomalous-authentication-patternsgit 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/hunting-anomalous-authentication-patterns)<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/hunting-anomalous-authentication-patterns"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/hunting-anomalous-authentication-patterns/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/hunting-anomalous-authentication-patterns"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/hunting-anomalous-authentication-patterns.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 | $0.00071 | $0.00675 |
| Opus 5 | $0.00036 | $0.00338 |
| Sonnet 5 | $0.00014 | $0.00135 |
| Haiku 4.5 | $0.00007 | $0.00068 |
Grade A, and why
hunting-anomalous-authentication-patterns 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 8d 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
Hunting Anomalous Authentication Patterns
When to Use
- You have Windows logon success (4624) and failure (4625) events and want to detect password spraying (one password across many accounts), brute force (many failures per account), and suspicious source concentration.
- You are investigating credential-access attempts against accounts.
Do not use this for a single failed logon — it relies on aggregation across accounts/sources to find patterns, not individual events.
Prerequisites
- Logon events with account, source IP/host, status, and timestamp.
Workflow
Step 1: Aggregate auth outcomes
python scripts/analyst.py hunt logons.csv
Computes failures per account, distinct accounts targeted per source (spray signal), and failure→success transitions per account (possible compromise).
Step 2: Surface patterns
- Spray: one source failing against many distinct accounts.
- Brute force: many failures against one account from a source.
- Breakthrough: a burst of failures followed by a success.
Step 3: Confirm
Correlate sources with known infrastructure; check whether successes are legitimate.
Step 4: Operationalize
Set thresholds and write a detection (e.g., source touching ≥ N accounts within a window).
Validation
- Spray detection keys on distinct-account breadth per source, not raw failure count.
- Brute force keys on per-account failure concentration.
- Failure-then-success transitions are reported for follow-up.
Pitfalls
- Service accounts/misconfigured apps generating benign failure storms.
- NAT/proxy collapsing many users behind one source IP, mimicking spray.
- Time-window choice: too wide hides bursts, too narrow misses slow sprays.
References
- See
references/api-reference.mdfor the hunter. - ATT&CK T1110.003 and Event 4625/4624 docs (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.
- 8d ago First seen · 89 lines · 71 tokens per session scan A c625823186cc
hunting-anomalous-authentication-patterns is a skill published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 71 tokens to every session and 675 once invoked, about $0.0004 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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