Listen to this Post
Introduction:
As organizations rush to integrate large language models (LLMs) into their workflows, accidental exposure of sensitive data – credentials, IP addresses, hostnames, and personally identifiable information (PII) – has become a critical threat. A new class of transparent proxy, exemplified by the open-source tool “DontFeedTheAI,” intercepts outbound requests to AI endpoints, strips all sensitive metadata before it reaches the model, and seamlessly restores it on the return path, effectively preventing data leakage without breaking application logic.
Learning Objectives:
– Deploy a bidirectional transparent proxy to sanitize AI-bound traffic in real time.
– Implement regex‑based stripping of IPs, credentials, hostnames, and PII from HTTP/HTTPS requests.
– Restore stripped values in API responses to maintain full functionality while protecting privacy.
You Should Know:
1. Setting Up a Transparent Proxy Environment
Step‑by‑step guide – Linux (mitmproxy + iptables):
This configuration intercepts all outbound traffic on port 443 (HTTPS) and redirects it to mitmproxy running on port 8080.
Install mitmproxy sudo apt update && sudo apt install mitmproxy -y Enable IP forwarding sudo sysctl -w net.ipv4.ip_forward=1 Redirect all outbound HTTPS traffic to mitmproxy sudo iptables -t nat -A OUTPUT -p tcp --dport 443 -j REDIRECT --to-port 8080 Run mitmproxy in transparent mode (requires root) sudo mitmproxy --mode transparent --showhost
Windows (using Fiddler + netsh):
Fiddler can act as a reverse proxy. For system‑wide redirection, use `netsh` to route port 443 traffic to Fiddler’s listening port (e.g., 8888). Note that Windows requires additional loopback exemption for local traffic.
Add URL reservation for Fiddler netsh http add urlacl url=http://127.0.0.1:8888/ user=everyone Configure system proxy (manual; transparent mode is limited on Windows without third‑party drivers)
2. Stripping Sensitive Headers and Payloads
Core concept: Use a Python script inside mitmproxy to remove patterns from request headers, JSON bodies, and query strings.
strip_sensitive.py
import re
from mitmproxy import http
SENSITIVE_PATTERNS = [
(r'\b(?:[0-9]{1,3}\.){3}[0-9]{1,3}\b', '[bash]'), IPv4
(r'Authorization: Bearer [A-Za-z0-9\-_]+\b', 'Authorization: Bearer [bash]'),
(r'(?i)(password|api_key|token|secret)=[^&]+', r'\1=[bash]'), URL params
(r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b', '[bash]') Email
]
def request(flow: http.HTTPFlow) -> None:
Strip headers
for header in ['Authorization', 'Cookie', 'X-API-Key']:
if header in flow.request.headers:
flow.request.headers[bash] = '[bash]'
Strip body (JSON)
if flow.request.text:
for pattern, repl in SENSITIVE_PATTERNS:
flow.request.text = re.sub(pattern, repl, flow.request.text)
Strip query parameters
for param in ['password', 'token', 'api_key']:
if param in flow.request.query:
flow.request.query[bash] = '[bash]'
Run with: `mitmproxy -s strip_sensitive.py –mode transparent`.
3. Restoring Stripped Data on the Response Path
Challenge: The AI model returns content that may refer to the stripped values (e.g., echoing an IP back). To restore, cache the original values before stripping and re‑insert them when the response passes through.
store original mapping
original_map = {}
def request(flow):
original_ip = flow.request.client_conn.peername[bash]
original_map[flow.id] = {'client_ip': original_ip}
... perform stripping as above
def response(flow: http.HTTPFlow) -> None:
if flow.id in original_map:
Restore IP address in response body
if flow.response.text:
flow.response.text = flow.response.text.replace('[bash]', original_map[flow.id]['client_ip'])
Restore Authorization header in response if needed (rare)
del original_map[flow.id]
Important: For HTTPS, mitmproxy generates a CA certificate that must be trusted by the client application.
4. Testing with a Live AI API (OpenAI Example)
Use `curl` to verify that credentials and IPs are stripped before reaching the endpoint.
Without proxy – request contains real IP and API key
curl https://api.openai.com/v1/chat/completions \
-H "Authorization: Bearer sk-real-key" \
-H "Content-Type: application/json" \
-d '{"model":"gpt-3.5-turbo","messages":[{"role":"user","content":"My IP is 192.168.1.100"}]}'
With DontFeedTheAI proxy – check logs to confirm stripping
curl --proxy http://127.0.0.1:8080 https://api.openai.com/v1/chat/completions \
-H "Authorization: Bearer sk-real-key" \
-d '{"model":"gpt-3.5-turbo","messages":[{"role":"user","content":"My IP is 192.168.1.100"}]}'
Examine proxy logs – the outgoing request should show `Authorization: Bearer
` and body `[bash]`. 5. Cloud Hardening: Deploy as a Sidecar in Kubernetes For production AI pipelines, run the proxy as a sidecar container to filter traffic between the application pod and the AI service. [bash] sidecar-proxy.yaml apiVersion: v1 kind: Pod metadata: name: ai-client spec: containers: - name: app image: myapp:latest env: - name: HTTP_PROXY value: "http://127.0.0.1:8080" - name: HTTPS_PROXY value: "http://127.0.0.1:8080" - name: dontfeedtheai image: zeroc00i/dontfeedtheai:latest args: ["--strip-ips", "--strip-creds", "--restore"] securityContext: capabilities: add: ["NET_ADMIN"] For iptables redirection inside pod
Apply with `kubectl apply -f sidecar-proxy.yaml`. This ensures every outbound request from the application is sanitized before hitting the AI endpoint.
6. Attackers’ Bypass Techniques & Mitigations
Even with a transparent proxy, determined adversaries can leak data through:
– DNS exfiltration – encode PII in subdomain queries (e.g., `[email protected]`).
Mitigation: Proxy must inspect and strip DNS over HTTPS (DoH) as well; use a DNS filter like `dnscrypt-proxy`.
– WebSocket tunneling – raw binary frames bypass HTTP header stripping.
Mitigation: Terminate WebSocket connections at proxy and enforce JSON‑only payloads.
– TLS‑encrypted inner tunnels – double encryption hides stripped fields.
Mitigation: Perform TLS termination at the proxy (requires a trusted CA installed on all clients).
Linux command to monitor bypass attempts:
sudo tcpdump -i eth0 'tcp port 443' -A -l | grep -E 'password|token|api_key'
7. Automating Deployment with Terraform (AWS)
Deploy a hardened EC2 instance running the proxy, with VPC flow logs to audit stripped data.
resource "aws_instance" "proxy" {
ami = "ami-0c55b159cbfafe1f0"
instance_type = "t3.micro"
user_data = <<-EOF
!/bin/bash
apt update && apt install mitmproxy -y
cat > /home/ubuntu/strip.py << 'SCRIPT'
(full stripping script from section 2)
SCRIPT
mitmproxy -s /home/ubuntu/strip.py --mode transparent &
EOF
iam_instance_profile = aws_iam_instance_profile.proxy_cloudwatch.name
}
resource "aws_cloudwatch_log_group" "proxy_audit" {
name = "/aws/proxy/dontfeedtheai"
}
After `terraform apply`, route AI‑bound traffic through the proxy instance using a route table or AWS Private Link.
What Undercode Say:
– Key Takeaway 1: Transparent proxies that strip and restore data offer a practical middle ground – you retain utility of AI APIs without handing over internal network metadata or user credentials.
– Key Takeaway 2: Implementing such a proxy requires careful handling of state (original↔redacted mapping) and HTTPS interception; missing restoration can break applications that rely on echo responses.
– Analysis (10 lines): The “DontFeedTheAI” concept addresses a growing compliance headache: GDPR, HIPAA, and SOC‑2 all restrict sharing PII with third‑party AI providers. By stripping before the request leaves the trust boundary, organizations avoid “data processing agreements” and cross‑border transfer issues. However, the proxy introduces latency and operational overhead – every TLS‑terminated request adds ~20‑50ms. Moreover, the restoration step is error‑prone: if the AI model returns transformed data (e.g., “[email protected]” becomes “user [bash] example [bash] com”), simple string replacement fails. Future iterations should integrate semantic redaction (NER models) and fuzzy restoration. From a red‑team perspective, this proxy can be abused: an attacker who compromises the proxy gains a perfect view of all stripped data plus the restoration mapping, effectively bypassing the intended protection. Thus, the proxy itself must be hardened (HSM for CA key, mutual TLS, immutable logs). Training courses should cover mitmproxy internals, regex crafting for PII, and Kubernetes sidecar patterns – all available on platforms like INE, TCM Security, and SANS SEC540.
Expected Output:
A correctly configured transparent proxy will show logs like this:
– Outgoing: `POST https://api.openai.com/v1/chat/completions` → Headers: `Authorization: [bash]`, Body: `{“messages”:[{“content”:”My IP is [bash]”}]}`
– Incoming: `200 OK` → Body: `{“choices”:[{“message”:{“content”:”Your IP is 192.168.1.100″}}]}` (restored)
No raw PII ever leaves the network.
Prediction:
– +1 Adoption of “strip‑and‑restore” proxies will become a standard AI security control, integrated into major API gateways (Kong, NGINX, Envoy) as built‑in filters by Q4 2025.
– +1 Open‑source tools like DontFeedTheAI will evolve to support LLM‑based dynamic redaction (e.g., using a small local model to identify sensitive spans).
– -1 Attackers will shift to exploiting the restoration logic – crafting responses that cause the proxy to leak cached original values via injection (e.g., “``”).
– -1 Without proper access controls on the proxy management API, internal malicious actors could disable stripping and exfiltrate data directly, turning the proxy into a single point of privacy failure.
– +1 Compliance frameworks (NIST AI RMF, ISO 42001) will explicitly recommend bidirectional sanitizing proxies for high‑risk AI use cases, driving enterprise demand for certified implementations.
▶️ Related Video (74% Match):
🎯Let’s Practice For Free:
🎓 Live Courses & Certifications:
[Join Undercode Academy for Verified Certifications](https://undercode.co.uk/certifications/)
🚀 Request a Custom Project:
Secure, high-velocity infrastructure and disruptive technological engineering. Contact our engineering team for high-tier development and proprietary systems:
[[email protected]](mailto:[email protected])
💎 Smart Architecture | 🛡️ Secure by Design | ⭐ Trusted by Thousands
IT/Security Reporter URL:
Reported By: [0xfrost Dontfeedtheai](https://www.linkedin.com/posts/0xfrost_dontfeedtheai-a-transparent-proxy-that-share-7466852285269106688-yYu9/) – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
🔐JOIN OUR CYBER WORLD [ CVE News • HackMonitor • UndercodeNews ]
[💬 Whatsapp](https://undercode.help/whatsapp) | [💬 Telegram](https://t.me/UndercodeCommunity)
📢 Follow UndercodeTesting & Stay Tuned:
[𝕏 formerly Twitter 🐦](https://x.com/undercodeupdate) | [@ Threads](https://www.threads.net/@undercodetesting) | [🔗 Linkedin](https://www.linkedin.com/company/undercodetesting/) | [🦋BlueSky](https://bsky.app/profile/undercode.bsky.social)
