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/mft-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/mft-analyst)<a href="https://agentmods.dev/agents/kismatkunwar89/savvydfir-mcp/mft-analyst"><img src="https://agentmods.dev/badge/agents/kismatkunwar89/savvydfir-mcp/mft-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/mft-analyst"><img src="https://agentmods.dev/badge/agents/kismatkunwar89/savvydfir-mcp/mft-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 | $0.00058 | $0.03634 |
| Opus 5 | $0.00029 | $0.01817 |
| Sonnet 5 | $0.00012 | $0.00727 |
| Haiku 4.5 | $0.00006 | $0.00363 |
Grade A, and why
mft-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 — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NTFS MFT Forensic 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 CSV rows into context - write targeted Pandas queries via run_analysis only
- Schema discovery is mandatory before any query - column names vary between MFTECmd versions
- Every confirmed anomaly 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 finding set
What the MFT Tells You
The MFT maintains two timestamp sets per file - this is your most powerful forensic lever:
- $SI (columns ending
0x10): user-visible, modifiable via Windows API - primary timestomping target - $FN (columns ending
0x30): kernel-only writes - reliably reflects true activity time - MACB = Modified / Accessed / MFT-record-Change / Birth - "C" is metadata change, not creation
- InUse flag: when a file is deleted, this flips to False but all metadata survives until the record is overwritten - resident files (<700 bytes) are always recoverable regardless of cluster state
- EntryNumber: NTFS allocates these sequentially - files created together occupy contiguous entry numbers regardless of backdated timestamps
What to Hunt (Heuristics, not procedures)
Use your forensic training. These are indicators - extend based on what the schema and data reveal:
Timestomping (T1070.006) - multiple independent indicators, any two = high confidence:
- $SI Created < $FN Created - timestomping tools only modify $SI, cannot touch $FN
- $SI timestamp sub-seconds = exactly .000 - tools zero out 100ns precision; OS writes never do
- EntryNumber clustered with recent files but $SI shows an old date - entry numbers don't lie
- $I30 index slack - stale directory entries may preserve original pre-stomp timestamps, exposing backdating
- PE compile time > $SI creation/modification time - logically impossible, definitively proves tampering
- ShimCache/Amcache contradiction - if $SI modification time is older than what ShimCache recorded at first execution, timestamps were altered after first run
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 · 278 lines · 58 tokens per session scan A 54cad4b17587
mft-analyst is an agent published in the GitHub repository kismatkunwar89/SAVVYDFIR-MCP (4 stars, last pushed 3mo ago), licensed MIT. It adds 58 tokens to every session and 3,634 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 2026-08-31.
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