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 trilwu/secskills --skill hunting-threatsgit clone --depth 1 https://github.com/trilwu/secskillsWrote 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/trilwu/secskills/hunting-threats)<a href="https://agentmods.dev/skills/trilwu/secskills/hunting-threats"><img src="https://agentmods.dev/badge/skills/trilwu/secskills/hunting-threats/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/trilwu/secskills/hunting-threats"><img src="https://agentmods.dev/badge/skills/trilwu/secskills/hunting-threats.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 128 YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
- high Prompt Injection · line 206 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- medium Rogue Agent · line 127 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00078 | $0.03384 |
| Opus 5 | $0.00039 | $0.01692 |
| Sonnet 5 | $0.00016 | $0.00677 |
| Haiku 4.5 | $0.00008 | $0.00338 |
Grade A, and why
hunting-threats scanned grade A with 1 finding 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 12d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| Execution via LOLBins | `rundll32`, `regsvr32`, `mshta`, `certutil`, `bitsadmin`, `msiexec` with network or unusual arguments; `curl`/`wget` piping to a shell on Linux | Copies of this mod
1 near-identical copy found in the catalogue:
- hunting-threats — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 286 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hunting Threats
Hunting starts from an assumption of failure: the controls are deployed, no alert has fired, and the adversary may still be present. The output is not usually a compromise — it is a detection, a telemetry gap, or a documented negative result. Hunts that only count as successful when they find something degrade into confirmation bias.
When to Use
- Proactively searching for compromise that detection missed
- Testing a specific hypothesis about attacker behaviour in your environment
- Operationalizing a threat intel report against your telemetry
- Validating that a control or detection actually works in production
- Baselining an environment to enable future outlier analysis
When NOT to Use
- Working an alert queue rather than a hypothesis — use
triaging-security-alerts; a hunt starts from a question, triage from a queue - Confirmed incident in progress — use
responding-to-incidents - Writing the rule for what you found — use
engineering-detections - Sample analysis — use
analyzing-malware - A packet capture to work through — use
analyzing-network-traffic - A confirmed AWS compromise to investigate — use
investigating-aws-incidents - Pivoting on indicators, tracking an actor, or producing a finished intel
product — use
producing-threat-intelligence; a hunt consumes intelligence, it does not produce it - Offensive testing of defenses — use the red team skills
Hypothesis Before Query
An unstructured search through logs is browsing, not hunting. Every hunt gets a written hypothesis in this shape:
Hypothesis: An adversary with [access level] is using [technique] to [objective], which would produce [observable] in [data source], which is distinguishable from normal because [discriminator].
If true, I expect to see: ... If false, I expect: ... Telemetry required: ... (verified present: yes/no)
If you cannot name the discriminator — what makes the malicious instance look different from the thousands of benign ones — the hunt is not ready. Go find the discriminator first; that research is the hunt.
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.
- 12d ago First seen · 286 lines · 78 tokens per session scan A 13c9a1234790
hunting-threats is a skill published in the GitHub repository trilwu/secskills (138 stars, last pushed 8d ago), licensed MIT. It adds 78 tokens to every session and 3,384 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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