Logsift

pip install cognis-logsift
logsift scan .            # → prioritized findings in seconds

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ logsift-emit --version
logsift 0.1.0

$ logsift-emit --help
usage: logsift [-h] [--version] {scan} ...

Defensive auth-log triage: detect brute-force, spray, and anomalous logins.
Analysis/detection only.

positional arguments:
  {scan}
    scan      scan an auth log file (use - for stdin)

options:
  -h, --help  show this help message and exit
  --version   show program's version number and exit

Blocks above are real logsift output — reproduce them from a clone.

Usage — step by step

1. Install (Python 3.8+, stdlib only):

   pip install logsift
   

2. Scan an auth/SSH log for brute-force, spray, and distributed-login patterns:

   logsift scan /var/log/auth.log
   

   scan exits 1 when findings exist, 0 when clean, 2 on usage/IO errors.
3. Tune the detectors to your environment:

   logsift scan auth.log --bruteforce-threshold 8 --spray-threshold 10 \
                         --distributed-threshold 6 --window-minutes 15
   

4. Read the output as JSON (or pipe a live log via stdin with -):

   tail -n 5000 /var/log/auth.log | logsift scan - --format json | jq '.findings[]'
   

   JSON includes summary (events_parsed, failures, distinct_ips, findings) and findings[].
5. Gate a CI / cron security check — fire an alert when anything is detected:

   logsift scan auth.log || curl -X POST "$SLACK_WEBHOOK" -d 'auth-log findings detected'
   

Contents

• Why logsift? · Features · Quick start · Example · Architecture · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing

Why logsift?

auth-log triage

logsift is single-purpose, scriptable, and self-hostable: point it at a target, get prioritized results in the format your workflow already speaks (table · JSON · SARIF), gate CI on it, and let agents drive it over MCP.

Features

• ✅ Parse Line
• ✅ Parse Lines
• ✅ Analyze
• ✅ Summarize
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

Quick start

pip install cognis-logsift
logsift --version
logsift scan .                       # scan current project
logsift scan . --format json         # machine-readable
logsift scan . --fail-on high        # CI gate (non-zero exit)

Example

$ logsift scan .
  [HIGH    ] LOG-001  example finding             (./src/app.py)
  [MEDIUM  ] LOG-002  another signal              (./config.yaml)

  2 findings · risk score 5 · 38ms

Architecture

flowchart LR
  IN[input] --> P[logsift<br/>analyze + score]
  P --> OUT[report]

Use it from any AI stack

logsift is interoperable with every popular way of using AI:

• MCP server — logsift mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe logsift scan . --format json into any agent or LLM
• LangChain · CrewAI · AutoGen · LlamaIndex — wrap the CLI/JSON as a tool in one line
• CI / scripts — exit codes + SARIF for non-AI pipelines

How it compares

	Cognis logsift	fail2ban
Self-hostable, no account	✅	varies
Single command, zero config	✅	⚠️
JSON + SARIF for CI	✅	varies
MCP-native (AI agents)	✅	❌
Polyglot ports (JS/Go/Rust)	✅	❌
Open license	✅ COCL	varies

Built in the spirit of fail2ban, re-framed the Cognis way. Missing a credit? Open a PR.

Integrations

Pipes into your stack: SARIF for code-scanning, JSON for anything, an MCP server (logsift mcp) for AI agents, and a webhook forwarder for SIEM/Slack/Jira. See docs/INTEGRATIONS.md.

Install — every way, every platform

pip install "git+https://github.com/cognis-digital/logsift.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/logsift.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/logsift.git" # uv
pip install cognis-logsift                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/logsift:latest --help        # Docker
brew install cognis-digital/tap/logsift                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/logsift/main/install.sh | sh

Linux	macOS	Windows	Docker	Cloud
scripts/setup-linux.sh	scripts/setup-macos.sh	scripts/setup-windows.ps1	docker run ghcr.io/cognis-digital/logsift	DEPLOY.md (AWS/Azure/GCP/k8s)

Related Cognis tools

• portfan — Summarize and diff nmap XML into prioritized, attackable findings
• subhunt — Aggregate & dedupe subdomain enumeration from multiple sources
• dirsight — Analyze web content-discovery output (ffuf/gobuster) into ranked endpoints
• jwtinspect — Decode JWTs and lint for alg=none, weak secrets, and missing claims
• corsaudit — Detect permissive/misconfigured CORS from headers or a config
• headerscan — Grade HTTP security headers (CSP/HSTS/XFO) A-F from a response dump

Explore the suite → 🗂️ all 170+ tools · ⭐ awesome-cognis · 🔗 cognis-sources · 🤖 uncensored-fleet · 🧠 engram

Contributing

PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.

⭐ If logsift saved you time, star it — it genuinely helps others find it.

Interoperability

{} composes with the 300+ tool Cognis suite — JSON in/out and a shared OpenAI-compatible /v1 backbone. See INTEROP.md for the suite map, composition patterns, and reference stacks.

License

Source-available under the Cognis Open Collaboration License (COCL) v1.0 — free for personal, internal-evaluation, research, and educational use; commercial / production use requires a license ([email protected]). See LICENSE.

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