Create a tool for determining the authenticity/falsification of a PDF file.

Budget: 5000 UAH Deadline: 30 days

To solve the problem of detecting counterfeits in text PDF files, it is not enough to simply compare text. A tool is needed that analyzes the internal structure of PDF objects, as any intervention through an editor leaves "digital traces" that are invisible to the eye but obvious to the code.

Technical implementation strategy (Python):

Metadata and signature analysis (Metadata & Producer check): Each institution uses specific software to generate statements (for example, IText, Quartz, ReportLab). If tags from Adobe Acrobat, NitroPDF, or Preview appear in the file, or if ModDate significantly differs from CreationDate — this is an immediate signal of intervention.

Object structure verification (Incremental Updates): PDF editors often save changes by adding new objects to the end of the file (incremental updates). The tool will check for the presence of multiple XREF tables and %%EOF markers. This allows for the detection of even those changes where the text has been altered to one of identical length.

Font and encoding control (Font & Encoding Consistency): Original systems usually use font subsets. When manually editing, the editor often substitutes a system font or changes character encoding. We will compare the hash sums of embedded fonts with "reference" ones for this institution.

Coordinate analysis (Layout X/Y Verification): Statement generation systems align text with an accuracy of thousandths of a pixel. Manual editing almost always leads to micro-shifts along the X or Y axes, which the tool will capture through the pdfminer.six library.

Economics and scalability:

Cost: Verification in Python (libraries PyMuPDF, pdfminer) is performed locally without involving third-party APIs or AI, so the cost of one verification is essentially equal to the cost of a few seconds of your server's work.

Versatility: The system is built on a modular principle. A separate "profile-mask" with reference characteristics of the structure is created for each new institution.

Clarifying question:
Do you have access to 10-20 guaranteed original statements from this institution to create an initial "digital snapshot" (reference) of the structure? Expand

Budget: 5001 UAH Deadline: 3 days

Hello. I can write a script in Python that will determine with 90%+ accuracy whether there were changes or not. The cost of verification will be constantly equal to 0. The script can be scaled to other institutions. We can discuss the details in private messages.

Budget: 700 UAH Deadline: 1 day

Hello! I am interested in your project. I have extensive experience in:

📄 Processing PDF and text data: Python, pdfplumber, PyPDF2, regular expressions
🔍 Change detection and content analysis: hashing, semantic comparison, NLP approaches
🤖 Document processing automation: parsing, extracting structured data
⚡️ Optimization and cost-effective processing: solutions without heavy servers, local tools
🛠 Scaling for different statement formats: adaptation to the specifics of institutions

I have a similar project that I implemented for a coursework, we can customize it to meet your requirements. Contact me to discuss the details and deadlines for the project!

Budget: 26990 UAH Deadline: 29 days

Good day!
My name is Valentin, and I represent Arctic Web Agency. We are a team that specializes in creating modern and effective solutions for business. I can provide examples of our similar work in personal messages. We are ready to take your project to work!

Sincerely,
Arctic Web Team
Freelancehunt

Budget: 10000 UAH Deadline: 7 days

I can implement a tool for automatic verification of third-party PDF files (PDF anomaly detector) for possible editing without access to the process of their creation. Since the digital signature is absent, the verification will be carried out through a comprehensive analysis of the structure of the PDF document: metadata, history of incremental updates, changes in the Producer field, XREF table, internal objects, and other technical signs of possible editing. The tool will be: written in Python, working locally or in CLI/API format, issuing a risk level of forgery (in percentages or as a status), scalable to formats of statements from multiple institutions. For one type of statements, after forming a technical profile (based on original examples), the accuracy of determination can reach 85-90%. The cost of verification will be minimal, without using third-party paid services. I am ready to discuss the implementation format, there are still a few questions, some technical requirements, and to receive file examples for testing and configuring the verification profile.

Budget: 4000 UAH Deadline: 1 day

Good day. I am ready to complete this project as I have extensive experience in application development.

Budget: 1000 UAH Deadline: 1 day

I am among the top 10 developers in the category of "Artificial Intelligence and Machine Learning" among ~2100 specialists on the platform.
I guarantee:
- Fast and quality execution of the task
- Clear adherence to deadlines
- Regular communication throughout the entire process
I would be happy to discuss the details of your project in private messages.

Budget: 5000 UAH Deadline: 3 days

Good day.
Yes, if the statement is official — it must contain a digital signature. Then the task is solved 100% correctly through the verification of the electronic signature and the integrity of the document.

I can implement a tool in Python that:
checks for the presence of a digital signature
validates the certificate
determines if the PDF has been altered after signing
automatically detects forgery
In case of text changes after signing — the verification will immediately show this.
The solution is fast, inexpensive to operate, and scalable to the formats of other institutions.

I am ready to implement it. Expand

Budget: 3200 UAH Deadline: 2 days

Hello! I have experience in developing PDF structure analysis tools in Python. The task is solved using digital forensics methods (analysis of XREF tables, metadata, and text layering).

Why this is beneficial:

- Accuracy 90%+: detection of technical traces of editing, invisible to the eye.

- Low cost: using open-source libraries will allow for local checks at zero cost (without paid APIs).

Preliminary estimate: 3200 UAH, deadline: 2 days. The price includes the creation of the system core, which can then be easily adapted for new types of statements.

To confirm the deadlines, please send samples of the original and the counterfeit (with hidden data).

Ready to start! Write to me! Expand

Budget: 2000 UAH Deadline: 3 days

Hello! I am creating a Python tool for analyzing PDF metadata. This will provide over 90% accuracy in detecting changes at minimal cost. Let's start with the MVP. I am waiting in private messages!

Budget: 5000 UAH Deadline: 1 day

Hello, Konstantin

There is a very simple solution through checksum to check the file; if it does not match the original, then the change is recorded.

Difficulty of the task: easy

Budget: 2200 UAH Deadline: 2 days

Hello, Konstantin!

I have reviewed the task. I have a clear algorithm on how to implement this tool in Python and ensure detection accuracy of fakes over 90%.

How it will work:
Instead of just "reading text," my script analyzes the hidden digital markers of the document. Any interference through a PDF editor (even changing one digit) inevitably breaks the original structure of the file generated by the bank or institution. Visually, the statement looks the same, but for my code, the forgery will be immediately noticeable.

Regarding your criteria:

Cost: $0 per verification. The script will operate autonomously without expensive paid APIs.

Scalability: I will make the architecture modular from the start. When new institutions need to be added, it will be done quickly and without rewriting the core of the program.

I look forward to collaborating! Expand

Budget: 4500 UAH Deadline: 5 days

Good day. It is possible to develop such a tool. However, there are nuances; it is necessary to process the PDF. Changing the text is not mandatory. Each company provides its brand, and the verification marks can be checked against them. I will develop it in node.js.

Budget: 2000 UAH Deadline: 3 days

Hello! Having studied your project with great interest, I am ready to start working on it. Let's discuss the details to achieve the best result.

Budget: 4000 UAH Deadline: 2 days

Good day. I can write in Go language. There is a script that is 80% written, it needs to be slightly adjusted to meet your needs. It will work very quickly. Please contact me.

Budget: 700 UAH Deadline: 1 day

Good evening, Konstantin!
In general, the task is clear, but for an accurate response regarding the deadlines and price, I would like to clarify some questions that arose after analyzing your task.
Please write in private messages – we will discuss the details and your wishes.