I have been configuring a Python Flask endpoint to intercept incoming utterances from NICE Cognigy.AI prior to them reaching the primary dialog flow. The operational reasoning behind this architecture is quite methodical. Initially, the webhook captures the raw user text payload. Subsequently, I execute a preliminary scan targeting prompt injection patterns. Should the input exhibit suspicious characteristics, I systematically redact the malicious sequences while preserving the underlying intent structure. Following that step, I append a SAFETYFLAG to the Cognigy context object. Ultimately, any session flagged as high-risk must be routed to a fallback human agent flow via the DIALOG API, and I maintain a log of these injection attempts for downstream threat intelligence analysis.
At this stage, the webhook triggers correctly upon message receipt, yet the context update consistently fails, either being dropped entirely or returning a 500 Internal Server Error from the Cognigy DIALOG API. To walk through the handler structure step by step: the incoming request contains the raw text, which I route through a basic regex-based scanner for the current proof of concept. Immediately after, I attempt to modify the conversation context by issuing a PUT request to the /api/v2/dialog/sessions/{SESSIONID}/context endpoint.
from flask import Flask, request, jsonify
import requests
import re
app = Flask(__name__)
COGNIGY_API = "https://api.nice.com/api/v2/dialog"
AUTH_TOKEN = "sk_test_..."
@app.route('/webhook/cognigy-input', methods=['POST'])
def handle_utterance():
data = request.json
user_text = data.get('utterance', '')
session_id = data.get('sessionId')
injection_pattern = re.compile(r'(?i)(ignore previous instructions|system prompt|act as|pretend to be)')
is_suspicious = bool(injection_pattern.search(user_text))
if is_suspicious:
clean_text = re.sub(injection_pattern, '[REDACTED]', user_text)
else:
clean_text = user_text
context_payload = {
"safetyFlag": "high_risk" if is_suspicious else "clear",
"sanitizedInput": clean_text
}
headers = {"Authorization": f"Bearer {AUTH_TOKEN}", "Content-Type": "application/json"}
resp = requests.put(f"{COGNIGY_API}/sessions/{session_id}/context", json=context_payload, headers=headers)
print(f"Context update status: {resp.status_code}")
return jsonify({"processed": clean_text, "risk": is_suspicious})
The console output consistently logs a 500 status code each time I execute that PUT call. I have cross-referenced the official Cognigy documentation, which indicates the endpoint requires a strictly defined context structure. I am currently evaluating whether I am incorrectly nesting the payload variables or if the SESSION STATE is temporarily locked during the webhook execution window. I attempted wrapping the entire payload under a VARIABLES key, but that approach immediately triggers a 400 Bad Request response.
I also need to address the routing configuration component. Once the SAFETYFLAG evaluates to high_risk, the objective is to initiate a human handoff via the DIALOG API. My current hypothesis is that I should invoke the /api/v2/dialog/sessions/{SESSIONID}/route endpoint with a TARGETTYPE parameter set to agent. However, our existing routing rules are strictly bound to specific QUEUE ID values. I need to determine whether I should explicitly pass the QUEUE ID within the routing request body, or if the DIALOG API automatically resolves it from the underlying dialog configuration.
The logging mechanism currently relies on a straightforward local file write, which is functioning without issue. I have not observed any direct correlation between the payload size and the recurring failure. Over the past two days, I have been iteratively adjusting the payload structure and cross-referencing the Europe/London office time logs to rule out any asynchronous processing delays, but no clear pattern has emerged. Given that the webhook enforces a strict 5-second timeout if a 200 response is not returned, it is highly probable that the context update operation must be executed asynchronously, or I am omitting a mandatory AUTHORIZATION header. The integration with the advanced threat detection model remains pending, so I am relying on regex for this initial proof of concept. I have left the terminal session active to continuously monitor the log output.