Supported document type
Detect tampered and deepfake Proposal
A proposal can be altered in minutes with a free PDF editor, and the result passes visual inspection because the layout, letterhead, and typeface are all genuine. Only the values have moved. The edits that matter are almost always small: scope item prices and total, proposal and acceptance dates, and client signature block, changed on an otherwise authentic document. TamperCheck analyses a proposal forensically rather than visually, and names the specific field that was edited.
API slug: proposal
What a genuine proposal contains
Whatever the issuer or jurisdiction, a proposal carries a small set of load-bearing fields: scope item prices and total, proposal and acceptance dates, client signature block, and contractor name and contact details. These are the fields a reviewer reads, and the fields a forger edits.
They are also bound to one another and to the file that carries them. Dates sit in a plausible order, identifiers follow the issuer's format, and every field was laid down in a single production pass, so they share one compression history, one font rendering, and one noise profile. A genuine document satisfies all of those relationships at once. An edited one rarely does.
How proposal forgeries are made
Altering the scope item prices and total
The scope item prices and total are overwritten in place while the surrounding page is left untouched. The document still reads correctly, but the edited region no longer shares the compression history and font rendering of the surrounding text, and any total derived from it stops reconciling.
Altering the proposal and acceptance dates
Shifting the proposal and acceptance dates makes an old or out-of-scope document read as current. This is the cheapest forgery to attempt, changing only a handful of characters, and the one most often missed by reviewers checking content rather than chronology.
Altering the client signature block
The client signature block is scanned from a genuine document and composited onto a new page. A real impression and a reproduced one differ measurably in edge behaviour and ink absorption, so the two separate cleanly under analysis even when they look identical.
Altering the contractor name and contact details
Substituting the contractor name and contact details repurposes a genuine document so it describes a different person or organisation than the one it was issued to. Every other element is authentic, which is why visual review tends to pass it.
Fully synthetic generation
The whole document is produced by a generative model or an online template service rather than edited from a real source. Every field is internally consistent, so logical and arithmetic checks pass. These are caught by generation signatures instead.
Print and rescan laundering
The edited file is printed and then photographed or scanned to destroy the digital edit trail. This removes the original metadata, but resampling and reprinting introduce their own detectable artifacts.
What TamperCheck checks on a proposal
TamperCheck runs 200+ forensic checks across three layers and returns a risk score from 0 to 100 with plain-English findings tied to specific regions of the document. These three carry the most weight on this document class.
Arithmetic reconciliation
Stated totals are recomputed from their components, and running or cumulative figures are checked for continuity across periods. A single edited value breaks the chain even when the page still looks right.
Table structure integrity
Inserted and deleted rows leave structural artifacts behind: inconsistent spacing, misaligned columns, and formatting the visible table no longer accounts for.
Signature forgery analysis
Signature regions are assessed for ink consistency and for how the stroke sits on the page, which distinguishes a genuine pen stroke from a pasted image of one.
And many more checks
The three above are the layers that carry the most weight on a proposal. Every upload runs the full suite of 200+ checks regardless of document class, spanning file structure and metadata, pixel-level forensics, font and text rendering, optical and print characteristics, provenance signals, AI-generation signatures, and many more checks.
Who verifies a proposal, and why
Construction lenders, owners, general contractors, and procurement teams reviewing bids. In each case the document is being used to unlock money, access, or a legal status, which is exactly what makes it worth forging.
How to verify a proposal in 4 steps
Check the fields against each other
Read scope item prices and total, proposal and acceptance dates, and client signature block together rather than one at a time. Forgers typically change one value and leave the rest of the document describing the original.
Inspect the file metadata
Open the document properties and look at the producer, creation date, and modification date. A document produced by a consumer PDF editor, or created long after the date printed on its face, is worth a closer look.
Ask for a second document
Request a corroborating document from the same issuer or an adjacent period. Forgery effort concentrates on one file, so inconsistencies surface as soon as there are two to compare.
Run a forensic check
Manual review catches obvious edits but not field-level pixel manipulation or synthetic generation. TamperCheck runs 200+ forensic checks on a proposal and returns a risk score from 0 to 100 within seconds, at $0.50 per document.
Frequently asked questions
How do lenders check a contractor's signed proposal?
Start with the fields most often altered on this document class: scope item prices and total, proposal and acceptance dates, and client signature block. Check that they agree with one another and with the file's own metadata. Edits that survive that review are caught forensically, through per-field compression, font, and generation analysis.
Can a signed construction proposal be edited?
Yes. A proposal is only as trustworthy as the file carrying it, and both localised editing and full synthetic generation leave measurable traces. TamperCheck runs 200+ forensic checks and names the field that was altered.
What software detects proposal fraud?
TamperCheck analyses a proposal through a single REST endpoint. Upload a PDF or image and receive a JSON verdict with a risk score from 0 to 100 and findings tied to specific regions of the document. Pricing is $0.50 per document, with no subscription or minimum.
Can an AI-generated proposal be detected?
Yes. Fully synthetic documents are internally consistent, so logical and arithmetic checks pass on them. They are caught instead by generation signatures, because the noise and compression characteristics of generated imagery differ measurably from documents produced by real scanners, cameras, and printers.
TamperCheck analyses proposal uploads with a hybrid forensic and AI pipeline tuned for this document class. Upload endpoints accept PDF and common image formats; class is inferred automatically. See the API documentation for authentication, async jobs, and webhooks.