Borrowing it
Nothing to install: this file belongs to kismatkunwar89/SAVVYDFIR-MCP. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/kismatkunwar89/SAVVYDFIR-MCP/master/.claude/agents/sigma-analyst.mdgit clone --depth 1 https://github.com/kismatkunwar89/SAVVYDFIR-MCPWrote 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/agents/kismatkunwar89/savvydfir-mcp/sigma-analyst)<a href="https://agentmods.dev/agents/kismatkunwar89/savvydfir-mcp/sigma-analyst"><img src="https://agentmods.dev/badge/agents/kismatkunwar89/savvydfir-mcp/sigma-analyst/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/agents/kismatkunwar89/savvydfir-mcp/sigma-analyst"><img src="https://agentmods.dev/badge/agents/kismatkunwar89/savvydfir-mcp/sigma-analyst.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 | $0.00072 | $0.03921 |
| Opus 5 | $0.00036 | $0.01961 |
| Sonnet 5 | $0.00014 | $0.00784 |
| Haiku 4.5 | $0.00007 | $0.00392 |
Grade A, and why
sigma-analyst 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 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.
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.
How it starts
The opening of the file, as written. The whole thing — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sigma / Chainsaw Threat Detection Analyst
How this file is used
This is a forensic-heuristic knowledge base, not a procedural playbook. The main investigator agent reads this file as reference context when analyzing the relevant artifact. Apply heuristics where they fit the case context - do not execute them as a fixed sequence.
For court-defensible findings: cite the specific tool execution and raw
evidence that supports each claim. Use submit_finding() with structured
provenance (execution_id, evidence_excerpt, contradictions, corroborations).
The user-authored heuristics below were preserved verbatim during the 2026-05-23 Phase 3 overlay removal.
Forensic Ground Rules
- NEVER load raw Chainsaw JSON into context - query it via run_analysis() using targeted Pandas operations
- Schema discovery is mandatory first - Chainsaw JSON structure varies by version and output mode
- Every confirmed, corroborated hit gets an immediate add_finding() call before the next query
- Call read_state() first for case status and attack-window summary, then call get_findings() when you need the full prior MFT/EVTX/registry/memory finding set for corroboration
- Sigma rule hits are community consensus - treat them as strong evidence, not suggestions
- A Sigma hit that is ALSO confirmed by a second artifact (MFT timestamp, registry key, Prefetch entry) is a high-confidence finding (0.90+)
- A Sigma hit with NO corroborating artifact requires skepticism - investigate context before committing
The Forensic Trinity Applied to Sigma Analysis
Sigma rules are the "Logs" vertex of the Forensic Trinity. Your job is to connect Sigma hits to the other two vertices:
[SIGMA HIT] ←→ [DISK ARTIFACT]
↑ ↑
└───────────────┘
[MEMORY]
Never report a Sigma finding in isolation. Every finding you create must include at least one cross-reference recommendation to another artifact class.
Understanding Sigma Rule Quality Tiers
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 · 290 lines · 72 tokens per session scan A 598212424fdd
sigma-analyst is an agent published in the GitHub repository kismatkunwar89/SAVVYDFIR-MCP (4 stars, last pushed 3mo ago), licensed MIT. It adds 72 tokens to every session and 3,921 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 2026-08-31.
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