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Building the “CYBERDUDEBIVASH-Shield”: Python Script Logic for Real-Time Defense

By Cyberdudebivash • Updated: 2025-12-19 • Focus: real-time detection + safe response

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This guide is defensive-only: monitoring, detection, safe containment, audit logging, and SOC-friendly alerting.

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TL;DR

What CYBERDUDEBIVASH-Shield is: A Python-based real-time defense agent that watches key system signals, scores risk, and triggers safe responses (isolate, alert, quarantine) without breaking production.
Core signals: process creation, suspicious parent-child chains, network connections, file writes in sensitive directories, persistence hooks, and user privilege shifts.
Core principle: do not “auto-kill everything.” Use a policy engine with allow-lists, suppression, and staged actions.
Output: structured JSON events for SOC/SIEM plus human-readable alerts for rapid triage.

Jump: TOC • Architecture • Script Logic • Hardening • FAQ

Risk Snapshot

Primary risk: false positives causing disruptions

Security risk: agent compromise if not isolated

Design goal: safe containment + auditability

KPI: actionable alerts vs noise, mean time to contain

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1) Context: What “Real-Time Defense” Should Mean

“Real-time defense” is often confused with “block everything instantly.” That approach breaks businesses. A real, production-grade defense agent does three things exceptionally well: observe relevant security signals, decide using explainable scoring, and act safely with reversible containment actions.

CYBERDUDEBIVASH-Shield is designed as a lightweight Python agent that can run on Windows and Linux hosts (or servers), generating structured events you can forward into your SOC. It is not a replacement for enterprise EDR. It is a defensive automation layer that can complement existing tools and provide visibility and containment workflows for environments that lack full EDR coverage.

The most important rule: no unsafe execution. The agent should never execute untrusted files. It should never “detonate” samples locally. If you need detonation, route artifacts to an isolated sandbox environment managed separately.

CyberDudeBivash Note: The difference between “security automation” and “automation chaos” is policy versioning, suppression, and audit trails.

2) Reference Architecture (Safe-by-Design)

Use a modular architecture so each capability can be enabled gradually. The safest designs isolate “collection” from “response” and make actions reversible.

Core modules

Collector: gathers signals (process, network connections, file changes, auth events).
Normalizer: converts OS-specific data into a stable event schema.
Scorer: assigns risk score with rationale (explainable policy engine).
Responder: triggers safe actions (alert, isolate, quarantine, ticket).
Exporter: outputs JSON to file, syslog, HTTP collector, or SIEM forwarder.
Audit: immutable logs and policy version snapshots.

Trust boundaries that matter

Least privilege: agent runs with the minimum permissions required to observe signals; “response actions” require explicit opt-in.
Policy gating: actions must be policy-driven and versioned; no ad-hoc “kill switches” without logging.
Fail safe: if policy engine fails or telemetry is incomplete, default to “alert-only” rather than disruptive actions.

3) Python Script Logic (Signals → Score → Action)

The blueprint below is designed for defensive monitoring. It uses safe telemetry (read-only collection) and a policy engine that can start in observe-only mode. The code samples are a skeleton you can harden and adapt to your environment.

Signal categories (practical, high-signal)

Process: new process start, parent-child chain, unsigned binaries in sensitive paths, suspicious command lines.
Network: unusual outbound destinations, new listening ports, unexpected connections by user apps.
Filesystem: writes to startup folders, scheduled task configs, service unit files, or browser extension directories.
Identity/auth: repeated failures, privilege changes, new local admin membership events.
Persistence hooks: registry run keys (Windows), cron/systemd timers (Linux), startup folders.

Minimal defensive agent skeleton (policy-driven, alert-first)

# CYBERDUDEBIVASH-Shield (Defensive Skeleton)
# Safe-by-design: observe -> score -> alert. Actions are gated and reversible.
# NOTE: For real production, run as a service, add signing, and enforce least privilege.

import os
import time
import json
import hashlib
from dataclasses import dataclass, asdict
from typing import Dict, Any, List, Optional

try:
    import psutil  # process + connections (read-only)
except Exception:
    psutil = None

POLICY_VERSION = "shield-policy-v1"

@dataclass
class Event:
    ts: int
    host: str
    category: str
    action: str
    score: int
    rationale: str
    data: Dict[str, Any]
    policy_version: str = POLICY_VERSION

def now() -> int:
    return int(time.time())

def host_id() -> str:
    return os.getenv("COMPUTERNAME") or os.uname().nodename

def sha256_text(s: str) -> str:
    return hashlib.sha256(s.encode("utf-8")).hexdigest()

def emit(event: Event, out_path: str = "shield-events.jsonl") -> None:
    line = json.dumps(asdict(event), sort_keys=True)
    with open(out_path, "a", encoding="utf-8") as f:
        f.write(line + "\n")

def score_process(proc: Dict[str, Any]) -> (int, str):
    score = 0
    why = []

    exe = (proc.get("exe") or "").lower()
    cmd = (proc.get("cmdline") or "").lower()
    parent = (proc.get("parent_name") or "").lower()
    name = (proc.get("name") or "").lower()

    # Simple heuristics (tune for your environment)
    if "\\appdata\\" in exe or "/tmp/" in exe:
        score += 20; why.append("exec_from_user_writable_path")

    if any(x in cmd for x in [" -enc ", " -encodedcommand ", " powershell "]) and "powershell" in cmd:
        score += 25; why.append("suspicious_powershell_flags")

    if parent in ["winword.exe", "excel.exe"] and any(x in name for x in ["cmd.exe", "powershell.exe", "wscript.exe", "cscript.exe"]):
        score += 30; why.append("office_spawn_shell")

    if any(x in cmd for x in ["reg add", "schtasks", "crontab", "systemctl enable"]):
        score += 15; why.append("persistence_intent_strings")

    # Cap
    score = min(100, score)
    return score, ";".join(why) if why else "low_signal"

def collect_process_snapshot() -> List[Dict[str, Any]]:
    if not psutil:
        return []
    out = []
    for p in psutil.process_iter(attrs=["pid","name","exe","cmdline","ppid","username","create_time"]):
        try:
            info = p.info
            cmdline = " ".join(info.get("cmdline") or [])
            # parent name (best effort)
            parent_name = ""
            try:
                parent_name = psutil.Process(info["ppid"]).name()
            except Exception:
                parent_name = ""
            out.append({
                "pid": info.get("pid"),
                "ppid": info.get("ppid"),
                "name": info.get("name") or "",
                "exe": info.get("exe") or "",
                "cmdline": cmdline,
                "user": info.get("username") or "",
                "parent_name": parent_name,
                "create_time": int(info.get("create_time") or 0)
            })
        except Exception:
            continue
    return out

def detect_new_processes(prev: Dict[int, str], current: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    # prev maps pid -> fingerprint
    new = []
    for p in current:
        pid = p.get("pid")
        fp = sha256_text(f"{p.get('exe')}|{p.get('cmdline')}|{p.get('create_time')}")
        if pid and pid not in prev:
            new.append(p)
            prev[pid] = fp
    # cleanup: drop old pids that no longer exist
    current_pids = {p.get("pid") for p in current if p.get("pid")}
    for pid in list(prev.keys()):
        if pid not in current_pids:
            prev.pop(pid, None)
    return new

def main_loop(poll_sec: int = 5):
    seen = {}  # pid -> fingerprint
    while True:
        snapshot = collect_process_snapshot()
        new_procs = detect_new_processes(seen, snapshot)

        for p in new_procs:
            score, rationale = score_process(p)
            action = "ALLOW"
            if score >= 70:
                action = "ALERT"
            elif score >= 40:
                action = "WATCH"

            evt = Event(
                ts=now(),
                host=host_id(),
                category="process_start",
                action=action,
                score=score,
                rationale=rationale,
                data=p
            )
            emit(evt)

        time.sleep(poll_sec)

if __name__ == "__main__":
    # Start in alert-only mode: do not auto-kill processes in v1
    main_loop(poll_sec=5)

Why this approach is safe

Observe-first: v1 generates alerts and watch events without disruptive actions.
Explainable scoring: every score has a rationale string (for SOC trust).
Idempotent outputs: JSONL logs can be shipped to a SIEM or stored for forensics.
Policy versioning: you can evolve rules without “mystery behavior.”

4) Safe Response Actions (Contain, Do Not Destroy)

When you move from alerting to automated action, you must avoid irreversible damage. The safest “v2 actions” are containment-focused: isolate a host from the network (policy-controlled), block outbound to known-bad destinations (centrally), or quarantine a file by moving it to a protected directory with restricted permissions.

Recommended action ladder

Level 0: Alert-only (default)
Level 1: Alert + create ticket + capture forensic snapshot (process info, hashes, recent connections)
Level 2: Quarantine suspicious file writes (move to isolated folder; do not delete)
Level 3: Host isolation (network ACL/EDR isolation) triggered only with multi-signal confirmation

CyberDudeBivash Note: “Automatic kill process” is high-risk and should be gated behind allow-lists, maintenance windows, and strict SOC approval, especially on servers.

5) Data Model + Telemetry for SOC/SIEM

Your events should be consistent enough to query across OS types. Keep a stable schema: timestamp, host, category, action, score, rationale, and a nested data object containing raw details.

Minimum viable event fields

ts (unix), host, category, score, action, rationale
policy_version (so your SOC can correlate behavior with policy changes)
dedupe_key (optional) to suppress repeats in downstream alerting
correlation_id (optional) to group events in a timeline

6) Hardening the Agent (Zero Trust + OWASP Mindset)

A defense agent is a high-value target. Harden it like production infrastructure. Assume an attacker will try to disable it, tamper with logs, or spoof signals. The Shield must be resilient under pressure.

Security controls checklist

Least privilege: run with minimal permissions; separate “collector” and “responder” roles if possible.
Integrity: sign releases, hash binaries, and verify integrity at startup.
Secure config: policy file is read-only for normal users; changes are logged with a policy version bump.
Tamper alerts: if logs are deleted or agent stops unexpectedly, create a high-severity alert.
Secrets: store tokens/keys in OS key vault or a secrets manager, never in code.
Safe updates: staged rollouts, rollback support, pinned dependencies, SBOM, and dependency scanning.
Output hygiene: JSON logs are append-only; forward to remote collector for immutability.

OWASP-style risk mapping (practical)

Injection: never execute anything derived from telemetry or external inputs.
Broken access control: lock down policy edits and responder actions.
Security misconfiguration: default to alert-only, deny risky actions unless explicitly enabled.
Logging/monitoring failures: ship logs off-host; alert on missing heartbeat.

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7) 30–60–90 Day Rollout Plan

0–30 Days: Observe

Deploy alert-only agent to a pilot group
Establish suppression rules and allow-lists
Ship JSON logs to central collector
Measure false positives and tune scoring

31–60 Days: Automate

Ticket creation + correlation timelines
Policy versioning process and approvals
Add file-watch signals for persistence paths
Introduce safe forensic snapshots

61–90 Days: Contain

Enable quarantine actions for high-confidence cases
Host isolation integrated with network/EDR
Tabletop exercise for agent tampering
Formalize detection engineering outputs

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FAQ

Q1: Is CYBERDUDEBIVASH-Shield an EDR replacement?
A: No. It is a defensive automation agent that can complement EDR, add visibility in gaps, and produce structured telemetry for SOC workflows.

Q2: What is the safest default action mode?
A: Alert-only. Then add containment actions gradually with allow-lists, suppression, and staged rollouts.

Q3: How do I avoid breaking production?
A: Use an action ladder, keep actions reversible, require multi-signal confirmation for containment, and log every decision with a policy version.

References

OWASP Top 10: secure-by-design principles for agent services and APIs
Windows Event Logging and Linux audit/journald concepts for host telemetry
General defensive engineering patterns: least privilege, policy versioning, immutable logging

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