detecting-process-injection-techniques

detecting-process-injection-techniques is a skill for Claude Code, Codex from adriannoes/awesome-agentic-ai. It costs 78 tokens per session (3,459 once invoked), scanned A, original, MIT.

A malware-analysis workflow for detecting code placed inside another running process without its cooperation. It covers techniques such as DLL injection, process hollowing, APC injection, thread hijacking, and reflective loading.

In plain words
What is it for?
Analyzing memory dumps, monitoring Windows API activity, reviewing process memory, and creating detection logic for process injection.
Why use it?
It helps investigators find malware that hides inside trusted processes and may otherwise evade ordinary file-based checks.

Skill for Claude CodeCodex

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

Good fit Analyzing memory dumps, monitoring Windows API activity, reviewing process memory, and creating detection logic for process injection.

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Install with agentmods
npx agentmods add skills/adriannoes/awesome-agentic-ai/detecting-process-injection-techniques
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-process-injection-techniques
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-process-injection-techniques

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/detecting-process-injection-techniques"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/detecting-process-injection-techniques.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,459 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to critical

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • critical YARA Match · line 363
    YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).
    Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
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 $0.00078 $0.03459
Opus 5 $0.00039 $0.01729
Sonnet 5 $0.00016 $0.00692
Haiku 4.5 $0.00008 $0.00346

Measured 6d ago against content hash ba4c5a849c88, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

detecting-process-injection-techniques scanned grade A with 1 finding 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 6d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/agent.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.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

result = subprocess.run(
cursor-claude-codex/skills/anthropic-cybersecurity-skills/skills/detecting-process-injection-techniques/SKILL.md · 372 lines

How it starts

The opening of the file, as written. The whole thing — 372 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Detecting Process Injection Techniques

When to Use

  • EDR alerts on suspicious API call sequences (VirtualAllocEx + WriteProcessMemory + CreateRemoteThread)
  • A legitimate process (explorer.exe, svchost.exe) exhibits unexpected network connections or file operations
  • Memory forensics reveals executable code in memory regions that should not contain it
  • Investigating living-off-the-land attacks where malware hides inside trusted processes
  • Building detection logic for specific injection techniques in EDR or SIEM rules

Do not use for standard DLL loading analysis; injection implies unauthorized code placement in a process without that process's cooperation.

Prerequisites

  • Volatility 3 for memory forensics analysis of injection artifacts
  • Sysmon configured with Event IDs 8 (CreateRemoteThread) and 10 (ProcessAccess)
  • API Monitor or x64dbg for observing injection API calls in real-time
  • Process Hacker or Process Explorer for inspecting process memory regions
  • Understanding of Windows memory management (VirtualAlloc, VAD, page protections)
  • Isolated analysis environment for safe malware execution and monitoring

Workflow

Step 1: Identify Injection via Memory Forensics

Use Volatility to detect injected code in process memory:

# malfind: Primary injection detection plugin
vol3 -f memory.dmp windows.malfind

# malfind detects:
# - Memory regions with PAGE_EXECUTE_READWRITE (RWX) protection
# - PE headers (MZ signature) in non-image VAD entries
# - Executable memory not backed by a file on disk

# Filter by specific process
vol3 -f memory.dmp windows.malfind --pid 852

# Dump injected memory regions for analysis
vol3 -f memory.dmp windows.malfind --dump

# Check VAD (Virtual Address Descriptor) tree for anomalies
vol3 -f memory.dmp windows.vadinfo --pid 852

# Detect hollowed processes (mapped image doesn't match disk)
vol3 -f memory.dmp windows.hollowfind

Step 2: Classify the Injection Technique

Identify which injection method was used based on artifacts:

Read the full file on GitHub · 372 lines

Files

What ships with it

3 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. 6d ago First seen · 372 lines · 78 tokens per session scan A ba4c5a849c88

Subscribe to this mod's changes

detecting-process-injection-techniques is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 12d ago), licensed MIT. It adds 78 tokens to every session and 3,459 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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