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Hunting Web Backdoors

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trilwu
hunting-web-backdoors

Hunt planted webshells and backdoors across a web source tree — PHP first (also JSP, ASP, Node) — triaging a directory at scale, statically decoding obfuscation layers without ever executing the payload, finding append-infections and fake plugins, and treating known shell families as leads rather than verdicts. Use when a web server is suspected compromised, cleaning a hacked WordPress/Magento/CMS site, vetting a downloaded PHP codebase or plugin for hidden malicious code, or when a file contains eval on decoded input.

Overview

Publishertrilwu
Repositorysecskills
Skill namehunting-web-backdoors
Stars
144
Forks
15
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by trilwu on GitHub. Read the source before you install it.

Installation

Install the Hunting Web Backdoors AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/trilwu/secskills.git /tmp/secskills
mkdir -p .claude/skills
cp -r /tmp/secskills/secskills-core/skills/hunting-web-backdoors .claude/skills/hunting-web-backdoors
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hunting Web Backdoors in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Hunting Web Backdoors on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Hunting Web Backdoors is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Hunting Web Backdoors

This is not a vulnerability audit. You are looking for code an attacker already planted — a webshell, a one-line eval backdoor, a fake plugin, a malicious line appended to a legitimate file. The weakness that let them in is auditing-php-applications' job; this skill finds what they left behind.

Two things make it hard. The malicious code is deliberately hidden — obfuscated, split, or buried in a tree of thousands of legitimate files — so a naive grep misses it. And the tells (eval, base64_decode, dynamic calls) appear in plenty of benign code, so a naive grep also drowns you in false positives. The work is the discrimination.

When to Use

  • A web server is suspected or confirmed compromised and you need every shell
  • Cleaning a hacked WordPress, Magento, Joomla, or custom PHP site
  • Vetting a downloaded plugin, theme, or codebase before deploying it
  • A file contains eval, assert, or system on decoded or request-derived input
  • Triaging a web root full of unfamiliar PHP for planted malice

When NOT to Use

  • Finding the vulnerability that allowed the upload — use auditing-php-applications
  • Deep single-sample analysis (a specific shell you want to fully reverse, its C2, its capabilities) — use analyzing-malware
  • The broader incident (scoping, timeline, containment) — use responding-to-incidents; this skill is the source-tree sweep within it
  • Malicious dependencies / package install scripts — use auditing-supply-chain
  • Host-level persistence (cron, systemd, LD_PRELOAD) — use analyzing-linux-persistence

Never Execute to Deobfuscate

The single rule that must not bend: the obfuscated code is the payload. Do not run it, do not "just let PHP decode it," do not replace eval( with echo( and execute the file, do not paste it into an online sandbox that runs it. Deobfuscation is a static transformation:

  • Decode the layers by hand or with a decode-only tool (base64_decode, gzinflate, gzuncompress, str_rot13, hex/\xNN, strrev) applied as string operations, not as executed PHP.
  • If you must automate, use a de-obfuscator that decodes without executing (UnPHP's decoder, a Python reimplementation of the decode chain) — never the PHP interpreter on the sample.
  • Replacing the final eval( with file_put_contents('out.php', ...) and running it is executing the payload if any prior layer has side effects. Decode statically, then read.

"Most webshells are three or four layers of encoding around ten lines of logic" — peel to the logic, do not detonate the wrapper.

Triage a Directory at Scale

You cannot read every file. Rank candidates by cheap signals, then read the top of the list:

bash
# 1. PHP where PHP should not be — uploads, cache, images, media dirs
find wp-content/uploads -name '*.php' -o -name '*.php[0-9]' -o -name '*.phtml' 2>/dev/null

# 2. Recently modified, clustered in time (attackers touch many files at once)
find . -name '*.php' -newermt '2026-07-01' -printf '%T+ %p\n' | sort

# 3. High entropy / long single lines — the shape of packed obfuscation
find . -name '*.php' -exec awk 'length>1000{print FILENAME": "length; nextfile}' {} \;

# 4. The dangerous-sink grep — leads, NOT verdicts (see the FP problem below)
grep -rnE '\b(eval|assert|system|passthru|shell_exec|proc_open|popen|create_function)\s*\(' --include='*.php' .
grep -rnE '(base64_decode|gzinflate|gzuncompress|str_rot13|hex2bin)\s*\(' --include='*.php' .

# 5. Request-driven code execution — the webshell core
grep -rnE '\$_(GET|POST|REQUEST|COOKIE|SERVER)\s*\[[^]]*\]\s*\(' --include='*.php' .
grep -rnE '(eval|assert|system|passthru)\s*\(\s*\$_(GET|POST|REQUEST|COOKIE)' --include='*.php' .

The most reliable single lead is variable execution of request data$_POST['x'](), ev[a]l($_GET[...]), ass[e]rt($_REQUEST[...]), call_user_func($_GET['f'], ...). Legitimate code almost never dispatches a function name straight from a superglobal.

The Grep Is Not Clean Just Because It Is Empty

A source tree that returns nothing for grep eval can still be backdoored. Attackers defeat the obvious grep deliberately:

  • Concatenation: $a='ev'.'al'; $a($code); or ('e'.'v'.'a'.'l')(...).
  • Variable variables / indirection: $f='system'; $f($_GET['c']);, ${'_'.'GET'}, $$x.
  • Char/hex/octal escapes: "\x65\x76\x61\x6c" is eval; chr(101).chr(118)....
  • Callback sinks: array_map, array_filter, usort, preg_replace_callback, register_shutdown_function, ob_start with a user-controlled callback.
  • String-eval that is not eval: assert($str) (pre-8.0), preg_replace('/./e', $str, ...) (pre-7.0), create_function('', $str) (pre-8.0), mb_ereg_replace with e.
  • Comment and whitespace insertion between token pieces to break naive regex.

So grep is a lead generator, not a coverage guarantee. When grep is empty and you still suspect infection, fall back to: entropy/long-line ranking, mtime clustering, and diffing against a known-good copy (below).

Append-Infections Are the Ones You Miss

The hardest infection is a backdoor appended to or inserted into a legitimate fileindex.php, wp-config.php, a theme's functions.php, vendor/ autoloaders. The file is 99% real, so it does not stand out by name, location, or entropy overall. Find these by comparison, not by inspection:

bash
# Diff the tree against a pristine copy of the same CMS/plugin version
# (download the exact version from wordpress.org / the vendor)
diff -rq ./site /known-good/wordpress-6.x/

# WordPress core/plugin integrity via checksums
wp core verify-checksums; wp plugin verify-checksums --all

# git/composer/npm: what changed vs the committed/locked state
git status --porcelain; git diff

If you have no known-good baseline, the tells are: code after the closing ?> of an otherwise-normal file, a lone eval/base64_decode line wedged at the top of a config file, or a <?php ... ?> block whose style clashes with the surrounding file.

Version-Gated Tells Date the Code

The presence of a removed language feature tells you something:

  • preg_replace with the /e modifier — removed in PHP 7.0. Its presence means the backdoor targets (or predates) PHP 5.x.
  • create_function() and string-argument assert() as code execution — removed in PHP 8.0. Common in older shells; on a PHP 8 server they would fault, which is itself a signal about when the code was planted.

Known Families Are Leads, Not Verdicts

Fingerprints speed triage but do not replace reading the code:

IOC strings in this section are bracket-broken — ev[a]l is eval, ass[e]rt is assert. Written literally they match Backdoor:PHP/Chopper and this file, a defensive hunting skill, gets quarantined on download. The grep patterns above are intact and safe to copy. See "Antivirus false positives" in the repo README.

  • China Chopper — a one-liner: <?php @ev[a]l($_POST['pass']);?> (or assert), often under 30 bytes. Tiny, so easy to miss and easy to append.
  • WSO, b374k, c99, r57, indoxploit — full-featured panels; grep their banner strings, characteristic function names, or auth-cookie names as leads.
  • Weevely — generates obfuscated, password-gated shells that change per build; signature matching is weak, so rely on the request-driven-execution and obfuscation signals instead.

A signature hit confirms a shell. It does not confirm you found them all — attackers plant several, and the second one rarely matches the first's family.

When You Confirm One, Assume More

  1. Preserve before you delete. A confirmed shell is evidence — copy it (hash it) to a holding location before removing it, per responding-to-incidents. Deletion alone loses the timeline and, if you miss the entry point, the attacker re-plants within hours.
  2. Find the entry point. A shell got there somehow — a vulnerable upload, a known-CVE plugin, stolen credentials. Hand that to auditing-php-applications (source) or responding-to-incidents (logs); a cleaned site with the hole still open is re-infected by morning.
  3. Keep hunting. One shell found is a reason to raise suspicion of the whole tree, not to close the case. Re-run the sweep after removing the obvious one.

Rationalizations to Reject

  • "grep for eval came back clean, so the tree is clean." Concatenation, hex escapes, and callback sinks all evade it. Empty grep is not coverage — fall back to entropy, mtime, and diff-against-known-good.
  • "I'll just run it to see what it decodes to." That is executing the payload. Decode statically, always.
  • "It uses eval, so it's a backdoor." Templating engines, caches, and frameworks use eval legitimately. The tell is eval on decoded or request-derived input, not eval itself.
  • "It's heavily obfuscated, so it's malicious." Commercial plugins ship obfuscated (ionCube, Zend Guard, licensing). Obfuscation raises suspicion; it does not convict. Decode and read the logic.
  • "I found the shell and deleted it, done." You found a shell. Preserve it, find the entry point, and re-sweep — attackers plant redundancy.
  • "The file is a core CMS file, it must be safe." Append-infections live in exactly those files precisely because you assume that. Verify by checksum.
  • "No known-shell signature matched." Weevely and custom shells match nothing. Signatures are leads; behaviour (request-driven execution, obfuscation) is the evidence.

Reading External Sources

Fetch public advisories, specifications, and vendor reports as Markdown:

bash
curl -sL "https://defuddle.md/<url>"      # scheme in the path is optional

This strips page boilerplate — roughly 78% fewer tokens on a prose page — and returns the full text rather than a summary, so you can grep it and trust a negative result.

Three things it is not for. Fetch JSON and API responses raw, because readability extraction mangles structured data. Fetch authenticated or JavaScript-rendered pages directly, because it retrieves them anonymously. And never route adversary infrastructure (phishing links, C2, malware hosting), client-owned hosts, or engagement URLs through it — the request leaves your machine to a third party, and for live adversary infrastructure it also tips off the operator.

Some sites block the extractor and return an error blob rather than the page — {"error":"Failed to fetch: 418 I'm a teapot"} from freedesktop.org, for instance. That is the fetch being refused, not the source saying the thing does not exist. Re-fetch the URL directly before drawing any conclusion from it.

References

  • auditing-php-applications — the vulnerability that let the shell in
  • analyzing-malware — deep reverse of a single recovered shell, its C2 and capabilities
  • responding-to-incidents — evidence handling, scoping, and the wider IR this sweep sits inside
  • analyzing-linux-persistence — host-level persistence beyond the web root
  • writing-yara-rules — turning a confirmed family into a reusable signature

Frequently asked questions

What does the Hunting Web Backdoors AI skill do?

Hunt planted webshells and backdoors across a web source tree — PHP first (also JSP, ASP, Node) — triaging a directory at scale, statically decoding obfuscation layers without ever executing the payload, finding append-infections and fake plugins, and treating known shell families as leads rather than verdicts. Use when a web server is suspected compromised, cleaning a hacked WordPress/Magento/CMS site, vetting a downloaded PHP codebase or plugin for hidden malicious code, or when a file contains eval on decoded input.

Why use Hunting Web Backdoors on TypingMind?

Because you install it once and use it with any model. Hunting Web Backdoors is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Hunting Web Backdoors in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/trilwu/secskills/tree/main/secskills-core/skills/hunting-web-backdoors. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hunting Web Backdoors?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Hunting Web Backdoors?

As many as you like. As long as a model supports skills, you can use Hunting Web Backdoors with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Hunting Web Backdoors AI skill free?

Yes. It is published on GitHub by trilwu under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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