ingest

A command that reads reconnaissance files—notes and collected information about a target—and extracts vulnerability findings and engagement context. It accepts a file or directory containing Markdown, JSON, or text files.

In plain words
What is it for?
Use it to ingest a report folder or individual file, process its contents, and build or update engagement context.
Why use it?
It turns scattered reconnaissance material into information the rest of the assessment workflow can use.

Command

Install

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.

agentmods
npx agentmods add commands/ogrodev/fsociety/ingest
Clone the repo
git clone --depth 1 https://github.com/ogrodev/fsociety
Per session 11 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,033 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00011 $0.02033
Opus 5 $0.00005 $0.01017
Sonnet 5 $0.00002 $0.00407
Haiku 4.5 $0.00001 $0.00203

Measured 2d ago against content hash 2f2142bc7532, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ingest 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 2d 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.

elliot/commands/ingest.md · 294 lines

How it starts

The opening of the file, as written. The whole thing — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Storage Policy: ALL output files MUST be saved in the project directory. NEVER write to /tmp/ or any system temporary directory.

Ingest Reconnaissance Files

You are ingesting reconnaissance files to extract vulnerability findings and build engagement context. The target path is: $ARGUMENTS


Step 1: Validate Path

If $ARGUMENTS is empty or blank, print this and stop:

Usage: /ingest <path-to-file-or-directory>

Examples:
  /ingest /path/to/recon-notes
  /ingest ./ATTACK-VECTORS.md
  /ingest ./reports/

Use Bash to validate the path exists and resolve it to an absolute path:

realpath "$ARGUMENTS"

Determine if the path is a file or directory using test -f / test -d.


Step 2: Discover Files

If single file: Skip to Step 4 (process directly).

If directory: Use Glob to find all ingestible files:

  • **/*.md — markdown files
  • **/*.json — JSON files (but NOT findings-db.jsonl)
  • **/*.txt — text files

Exclude these from results:

  • findings-db.jsonl
  • engagement-context.md
  • Any file starting with .

Count the files. If zero, print "No ingestible files found" and stop.


Step 3: Decide Processing Mode

  • ≤3 files: Process directly — Read each file yourself and extract findings + context inline (go to Step 4)
  • 4+ files: Batch into groups of 5 files and spawn parallel Task subagents (go to Step 5)

Step 4: Direct Processing (Single File or ≤3 Files)

Read each file with the Read tool.

For each file, extract:

A. Vulnerability Findings

Identify every distinct vulnerability or security issue mentioned. For each one, extract:

  • endpoint: The URL path or endpoint (e.g., /api/auth/reset-password, POST /api/payments/generate)
  • vuln_type: Category — idor, sqli, xss, auth-bypass, rce, info-leak, config, rate-limit, user-enum, ssrf, lfi, ssti, xxe, type-confusion, or other
  • param: The vulnerable parameter name, or none if not parameter-specific
  • severity: CRITICAL, HIGH, MEDIUM, LOW, or INFO
  • title: Brief descriptive title (max 80 chars)

Read the full file on GitHub · 294 lines

Changes

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.

  1. 2d ago First seen · 294 lines · 11 tokens per session scan A 2f2142bc7532

Subscribe to this mod's changes

ingest is a command published in the GitHub repository ogrodev/fsociety (20 stars, last pushed 5mo ago), licensed MIT. It adds 11 tokens to every session and 2,033 once invoked, about $0.0001 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 2026-08-30.