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Generating Images from Text with C# and Open AI DALL-E

With the use of .NET C#, we can develop a POC (Proof of Concept) that uses the Open AI DALL-E model to generate images from text input. In this blog post, we will explore the steps to develop a C# Console Application using Open AI's…

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With the use of .NET C#, we can develop a POC (Proof of Concept) that uses the Open AI DALL-E model to generate images from text input.



In this blog post, we will explore the steps to develop a C# Console Application using Open AI's DALL-E model to generate images from text.



Also, check out my blog with other articles --> https://rmauro.dev






💬 What is DALL-E from Open AI



DALL-E can generate images of almost anything, from a yellow submarine to a pig with wings. It has been trained on a massive dataset of images and textual descriptions, allowing it to learn how to generate images from natural language input. In this article, we will explore how to integrate C# with DALL-E to generate images using code.



Generating Images from Text with C# and Open AI DALL-E




DALL-E Generated







🧵 Development with C



In this project we're going to use Visual Studio and C# with .NET 6 to create a Console Application.




💡 You may need to do some tweaks if you intend to use another.NET version.







Step 1: Console Application and dependencies



Let's create our Console Application with C# and .NET 6 let's install the dependencies.

Project Name : ConsoleAppOpenAI.DALL_E




dotnet add Microsoft.Extensions.Http

👇 these are for loading configuration from JSON files
dotnet add Microsoft.Extensions.Configuration
dotnet add Microsoft.Extensions.Configuration.Json

👇 this is optional
dotnet add Microsoft.Extensions.Configuration.UserSecrets







Commands to install the dependencies




Generating Images from Text with C# and Open AI DALL-E




Installed Dependencies







Step 2: IOpenAIProxy Interface



Within this interface, we'll expose only the methods to Generate and Download the images from Open AI.




namespace ConsoleAppOpenAI.DALL_E.HttpServices;

public interface IOpenAIProxy
{
//👇 Send the Prompt Text with and return a list of image URLs
Task<GenerateImageResponse> GenerateImages(
GenerateImageRequest prompt,
CancellationToken cancellation = default);

//👇 Download the Image as byte array
Task<byte[]> DownloadImage(string url);
}







IOpenAIProxy.cs File







Step 3: Generate Image Models



Let's define our models using records. Records simplify the reading since they are only POCO classes.




namespace ConsoleAppOpenAI.DALL_E.HttpServices
{
public record class GenerateImageRequest(
string Prompt,
int N,
string Size);

public record class GenerateImageResponse(
long Created,
GeneratedImageData[] Data);

public record class GeneratedImageData(string Url);
}








Generate Image Models DTO







Step 4: Create an Open AI Account



To use the OpenAI API, we need to create an account on the OpenAI platform. The registration process is straightforward and can be completed in a few minutes.



  • We just need to visit the OpenAI website at https://platform.openai.com/overview.

  • Then click on the "Sign Up" button in the top right corner.

  • Click on the button to start the registration process.




Step 5: Set up the Configuration File / appsettings.json



To access the DALL-E model, we'll need to set up the Subscription Id and API key for our application.



Collect them from these menus:



Generating Images from Text with C# and Open AI DALL-E



Update the appsettings.json or secrets.json file with the values.




{
"OpenAi": {

"OrganizationId": "{Subscription Id goes here}",
"ApiKey": "{API Key goes here}",

"Url": "https://api.openai.com",
"DALL-E": {
"Size": "1024x1024",
"N": 1
}
}
}







appsettings.json file



💡 Don't forget to set Copy to Output Directory as Copy if newer for appsettings.json.







Step 6: Open AI HTTP Service Implementation



Create a class named OpenAIHttpService with a single constructor receiving IConfiguration and read the configuration we just set in place.




using ConsoleAppOpenAI.DALL_E.HttpServices;
using Microsoft.Extensions.Configuration;
using System.Net.Http.Headers;
using System.Net.Http.Json;
using System.Text.Json;

namespace ConsoleAppOpenAI.DALL_E.Services;

public class OpenAIHttpService : IOpenAIProxy
{
readonly HttpClient _httpClient;

readonly string _subscriptionId;

readonly string _apiKey;

public OpenAIHttpService(IConfiguration configuration)
{
//👇 reading settings from the configuration file
var openApiUrl = configuration["OpenAi:Url"] ?? throw new ArgumentException(nameof(configuration));
_httpClient = new HttpClient { BaseAddress = new Uri(openApiUrl) };

_subscriptionId = configuration["OpenAi:SubscriptionId"];
_apiKey = configuration["OpenAi:ApiKey"];
}

public async Task<GenerateImageResponse> GenerateImages(GenerateImageRequest prompt, CancellationToken cancellation = default)
{
throw new NotImplementedException();
}

public async Task<byte[]> DownloadImage(string url)
{
throw new NotImplementedException();
}
}







Next should be the implementation of the GenerateImages() method:




public async Task<GenerateImageResponse> GenerateImages(GenerateImageRequest prompt, CancellationToken cancellation = default)
{
using var rq = new HttpRequestMessage(HttpMethod.Post, "/v1/images/generations");

var jsonRequest = JsonSerializer.Serialize(prompt, new JsonSerializerOptions
{
PropertyNamingPolicy = JsonNamingPolicy.CamelCase
});

//serialize the content to JSON and set the correct content type
rq.Content = new StringContent(jsonRequest);
rq.Content.Headers.ContentType = new MediaTypeHeaderValue("application/json");

//👇 Including the Authorization Header with API Key
var apiKey = _apiKey;
rq.Headers.Authorization = new AuthenticationHeaderValue("Bearer", apiKey);

//👇 Including the Subscription Id Header
var subscriptionId = _subscriptionId;
rq.Headers.TryAddWithoutValidation("OpenAI-Organization", subscriptionId);

var response = await _httpClient.SendAsync(rq, HttpCompletionOption.ResponseHeadersRead, cancellation);

response.EnsureSuccessStatusCode();

var content = response.Content;

var jsonResponse = await content.ReadFromJsonAsync<GenerateImageResponse>(cancellationToken: cancellation);

return jsonResponse;
}






Last the DownloadImage() method implementation:




public async Task<byte[]> DownloadImage(string url)
{
var buffer = await _httpClient.GetByteArrayAsync(url);

return buffer;
}









Step 7: Consuming the APIs



Back to Program.cs file let's wire everything together and start calling the APIs to generate images.




using ConsoleAppOpenAI.DALL_E.HttpServices;
using ConsoleAppOpenAI.DALL_E.Services;
using Microsoft.Extensions.Configuration;
using System.Reflection;

Console.WriteLine("Starting commandline for DALL-E [Open AI]");

var config = BuildConfig();

IOpenAIProxy aiClient = new OpenAIHttpService(config);

Console.WriteLine("Type your first Prompt");
var msg = Console.ReadLine();

var nImages = int.Parse(config["OpenAi:DALL-E:N"]);
var imageSize = config["OpenAi:DALL-E:Size"];
var prompt = new GenerateImageRequest(msg, nImages, imageSize);

var result = await aiClient.GenerateImages(prompt);

foreach (var item in result.Data)
{
Console.WriteLine(item.Url);

var fullPath = Path.Combine(Directory.GetCurrentDirectory(), $"{Guid.NewGuid()}.png");
var img = await aiClient.DownloadImage(item.Url);

await File.WriteAllBytesAsync(fullPath, img);

Console.WriteLine("New image saved at {0}", fullPath);
}

Console.WriteLine("Press any key to exit");
Console.ReadKey();

static IConfiguration BuildConfig()
{
var dir = Directory.GetCurrentDirectory();
var configBuilder = new ConfigurationBuilder()
.AddJsonFile(Path.Combine(dir, "appsettings.json"), optional: false)
.AddUserSecrets(Assembly.GetExecutingAssembly());

return configBuilder.Build();
}






With all of this, we should have a running POC integrating with DALL-E model.






Generate our very first Image



Here is the output of my first try.




Prompt: Wide and green garden with a lot of flowers, with sunflowers, and a small dog running around






Take a look at this beautiful image generated by our application and DALL-E.



Generating Images from Text with C# and Open AI DALL-E
DALL-E Generated






Conclusion



Integrating C# with DALL-E is a straightforward process that allows us to generate images programmatically.



By using Open AI's API, we can easily send textual descriptions and receive high-quality images in response.



This integration opens up many possibilities, such as generating images for data visualization, creating custom artwork, or automating image creation tasks. As DALL-E continues to improve, we can expect even more exciting applications in the future.



Source code at: https://github.com/ricardodemauro/OpenAILabs.Console



Posted at: https://rmauro.dev/generating-images-from-text-with-csharp-and-open-ai-dall-e/

1. Sofort-Triage & Abwehrmaßnahmen

SOC Incident Playbook: Remote Code Execution (RCE) Defense
Syntax validiert (0 Fehler)
title: Detect Exploitation - Generating Images from Text with C# and Open AI DALL-E
id: c9de1340-26e9-4575-8cae-5dba4bf46388
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-26
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
Syntax validiert (0 Fehler)
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-26"
        description = "YARA Signature for "
    strings:
        $str = "Generating Images from Text wi" ascii wide
    condition:
        any of them
}
Syntax validiert (0 Fehler)
index=security sourcetype IN ("cisco:asa", "pan:traffic", "zeek_conn", "suricata", "WinEventLog:Security")
("Generating Images from Text with C and O")
| stats count earliest(_time) as first_seen latest(_time) as last_seen by src_ip, dest_ip, dest_host, signature
| eval first_seen=strftime(first_seen, "%Y-%m-%d %H:%M:%S"), last_seen=strftime(last_seen, "%Y-%m-%d %H:%M:%S")
| sort - count
Syntax validiert (0 Fehler)
message: "*Generating Images from Text with C and O*"
Syntax validiert (0 Fehler)
CommonSecurityLog
| where Message has "Generating Images from Text with C and O"
| summarize EventCount = count(), FirstSeen = min(TimeGenerated), LastSeen = max(TimeGenerated) by SourceIP, DestinationIP, DestinationPort, Activity
| extend DetectionRule = "iShareStuff-CTI-Compiled"
| sort by EventCount desc

2. Cyber Threat Intelligence & Forensik

CTI Threat Relationship Graph3 Knoten / 2 Relationen
CVE / Incident Software MITRE ATT&CK CWE Weakness IoC
🎯
MITRE ATT&CK Matrix Navigator 14 Taktiken
Reconnaissance
-
Resource Development
-
Initial Access
Execution
Persistence
-
Privilege Escalation
Defense Evasion
Credential Access
-
Discovery
-
Lateral Movement
-
Collection
-
Command and Control
Exfiltration
-
Impact
tsecurity.de Cognitive Threat RAG
Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich Generating Images from Text with C# and .... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

🛡️ Angriffsfläche & Exposure

Netzwerk/Remote-Zugriff ohne Vorauthentifizierung möglich.

⚡ Empfohlene Sofortmaßnahmen
  • 1. Perimeter-Inspektion: Relevante Portfreigaben und exponierte Endpunkte unverzüglich scannen.
  • 2. Patch-Applikation: Hersteller-Hotfix einspielen oder betroffene Daemons in isolierte DMZ-Segmente überführen.
  • 3. Telemetrie & EDR-Alerts: Prozessaufrufe und Child-Processes auf anomale Shell-Spawns überwachen.
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