detecting-email-forwarding-rules-attack

detecting-email-forwarding-rules-attack is a skill for Claude Code, Codex from adriannoes/awesome-agentic-ai. It costs 34 tokens per session (798 once invoked), scanned A, original, MIT.

A security investigation guide for finding malicious email-forwarding rules created by attackers inside an organization's mail system.

In plain words
What is it for?
Use it during threat hunting, incident response, security assessments, and investigations triggered by endpoint or SIEM alerts.
Why use it?
It helps uncover attackers who secretly copy email conversations for intelligence gathering or business email fraud.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it during threat hunting, incident response, security assessments, and investigations triggered by endpoint or SIEM alerts.

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Install with agentmods
npx agentmods add skills/adriannoes/awesome-agentic-ai/detecting-email-forwarding-rules-attack
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.

Any agent
npx skills add adriannoes/awesome-agentic-ai --skill detecting-email-forwarding-rules-attack
Clone the repo
git clone --depth 1 https://github.com/adriannoes/awesome-agentic-ai

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for detecting-email-forwarding-rules-attack

README.md
[![agentmods](https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/detecting-email-forwarding-rules-attack/github.svg)](https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/detecting-email-forwarding-rules-attack)
Your own site
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/detecting-email-forwarding-rules-attack"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/detecting-email-forwarding-rules-attack/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.

agentmods 80×15 button for detecting-email-forwarding-rules-attack

Your own site · 80×15
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/detecting-email-forwarding-rules-attack"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/detecting-email-forwarding-rules-attack.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 798 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00034 $0.00798
Opus 5 $0.00017 $0.00399
Sonnet 5 $0.00007 $0.00160
Haiku 4.5 $0.00003 $0.00080

Measured 8d ago against content hash c081e7d3d4b3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

detecting-email-forwarding-rules-attack 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 8d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/agent.py, scripts/process.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

cursor-claude-codex/skills/anthropic-cybersecurity-skills/skills/detecting-email-forwarding-rules-attack/SKILL.md · 104 lines

How it starts

The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Detecting Email Forwarding Rules Attack

When to Use

  • When proactively hunting for indicators of detecting email forwarding rules attack in the environment
  • After threat intelligence indicates active campaigns using these techniques
  • During incident response to scope compromise related to these techniques
  • When EDR or SIEM alerts trigger on related indicators
  • During periodic security assessments and purple team exercises

Prerequisites

  • EDR platform with process and network telemetry (CrowdStrike, MDE, SentinelOne)
  • SIEM with relevant log data ingested (Splunk, Elastic, Sentinel)
  • Sysmon deployed with comprehensive configuration
  • Windows Security Event Log forwarding enabled
  • Threat intelligence feeds for IOC correlation

Workflow

  1. Formulate Hypothesis: Define a testable hypothesis based on threat intelligence or ATT&CK gap analysis.
  2. Identify Data Sources: Determine which logs and telemetry are needed to validate or refute the hypothesis.
  3. Execute Queries: Run detection queries against SIEM and EDR platforms to collect relevant events.
  4. Analyze Results: Examine query results for anomalies, correlating across multiple data sources.
  5. Validate Findings: Distinguish true positives from false positives through contextual analysis.
  6. Correlate Activity: Link findings to broader attack chains and threat actor TTPs.
  7. Document and Report: Record findings, update detection rules, and recommend response actions.

Key Concepts

Concept Description
T1114.003 Email Forwarding Rule
T1114.002 Remote Email Collection
T1098.002 Additional Email Delegate Permissions

Tools & Systems

Tool Purpose
CrowdStrike Falcon EDR telemetry and threat detection
Microsoft Defender for Endpoint Advanced hunting with KQL
Splunk Enterprise SIEM log analysis with SPL queries
Elastic Security Detection rules and investigation timeline
Sysmon Detailed Windows event monitoring
Velociraptor Endpoint artifact collection and hunting
Sigma Rules Cross-platform detection rule format

Read the full file on GitHub · 104 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 8d ago First seen · 104 lines · 34 tokens per session scan A c081e7d3d4b3

Subscribe to this mod's changes

detecting-email-forwarding-rules-attack is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 13d ago), licensed MIT. It adds 34 tokens to every session and 798 once invoked, about $0.0002 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 2026-09-03.

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