Evidential Integrity in the Age of Disinformation and Synthetic Media

In any investigation, maintaining digital evidential integrity is the discipline of ensuring that material can be relied upon as evidence: that it’s authentic, unaltered, and handled in a way that preserves its reliability from collection to court. This means being able to demonstrate how it was obtained, what it is, where it came from, and what happened to it along the way.

Disinformation and synthetic media have changed evidential integrity because they don’t just create fake evidence. They create plausible alternatives to reality, and they do so cheaply, quickly, and at scale. It’s one reason the World Economic Forum’s Global Risks Report now places misinformation and disinformation among the most immediate threats facing societies and institutions.

The uncomfortable implication is this: investigators, legal teams, and courts can no longer assume that digital material is inherently reliable simply because it is digital. In this article, we look at how disinformation undermines digital evidence, the challenge this poses, and best practices for maintaining evidential integrity in a time of deepfakes and GenAI.

The rise of synthetic media and scaled disinformation

Deepfake is often shorthand for synthetic media, but the category is broader and more complex.

It includes:

• AI-generated or AI-edited images
• Voice cloning
• Text generation
• Synthetic documents
• Hybrid artifacts where authentic media is recontextualised, cropped, subtitled, or recombined

The barrier to producing convincing false content has fallen fast. Check Point Research reviewed 36 parliamentary, regional and presidential elections in just six months (September 2023 to February 2024) around the globe and found reports of AI-generated materials used in disinformation campaigns in at least 10 cases, roughly a third of the sample.

And the most consequential examples are not theoretical. In early 2024, UK engineering firm Arup confirmed it was defrauded of HK$200 million (around £20 million) after an employee attended what appeared to be a legitimate video call featuring senior leaders; except the leaders were AI-generated fakes.

How disinformation undermines digital evidence

Manipulated content can enter investigations through:

• Open-source intelligence (OSINT) collection
• Social media submissions from witnesses or the public
• Internal reporting channels
• Secondary sources (screenshots of screenshots)

Once disinformation enters an evidential pipeline, the challenges aren’t limited to “is it fake?” The harder questions are often:

• Originality: Is this the first instance of the media, or a copy several generations removed?
• Context: Was it posted alongside other material that changes its meaning?
• Timing: When was it created, edited, uploaded, and reshared. Can that sequence be proven?

This is where “looks real” becomes a weak standard. A Reuters Institute analysis of publicly accessible AI detection tools found that relatively simple transformations such as cropping, scaling, or lowering resolution, could cause detectors to incorrectly judge manipulated content as authentic. In other words, the very processes that happen naturally when content is shared online can make verification harder even when you know what you’re looking for.

As OSINT is now central to every investigation, the contamination risk rises. Researchers and investigative organisations have documented how modern cases can hinge heavily on social media posts, sometimes becoming the primary source material for accountability processes. So it’s vital that there is a clear audit trail detailing how the material was sourced, and just as importantly, can it be proven.

The challenge for investigators and analysts

Investigators and analysts are now expected to do three jobs at once:

1. Investigate the event
2. Investigate the evidence
3. Investigate how evidence was captured and its provenance

That has real consequences:

• Resource pressure: Authenticity checks take time, tools, and repeatable methodology.
• Confirmation bias risk: When synthetic content aligns neatly with an existing theory, it can become a high-confidence proof.
• Late-stage collapse: If integrity is challenged near trial, teams can find themselves reconfirming provenance and context under extreme time pressure, often with missing artifacts or incomplete audit records.

In many organisations, these pressures collide. Most workflows were designed for an era where authenticity challenges were rarer and less sophisticated.

Evidential integrity in the courtroom

Defence strategies increasingly focus not on what the evidence shows, but on whether it can be trusted at all.

This is where deepfake awareness creates a paradox. The public now knows manipulation is possible, which is good. But that awareness can also produce what researchers have described as the “liar’s dividend”: the ability to dismiss genuine evidence by claiming it is fabricated or AI-generated.

Meanwhile, academic publications, aimed at judges and court administrators increasingly emphasises the need for education, technical validation, and careful handling of AI-generated or AI-manipulated evidence.

Safeguards and best practice for maintaining integrity

So, what does good look like in this environment?

It starts with fundamentals:

• Provenance and chain of custody for digital material, documented from the start to disclosure
• Early-stage verification
• Repeatable validation workflows
• Clear audit trail that can be explained and defended

Standards bodies and practitioners have been saying for years that digital evidence preservation has unique challenges, but also that there are powerful techniques for preventing and detecting change when evidence is handled properly.

At the workflow level, many teams are moving away from improvised collections of screenshots and shared drives toward purpose-built systems that make secure capture, controlled access, and auditable handling the default. In that context, platforms such as MeaConnexus and MeaFuse are less about tools and more about enforcing the standards your future self, or a court, will demand.

Integrity as the foundation of trust

Evidence credibility underpins investigative outcomes, legal decisions, and public confidence. The technology will keep advancing. The question is whether our evidential standards advance with it.

Evidential integrity must now be proactive. This includes provenance by design, validation early, and audit trails that stand up under scrutiny.

If a single piece of digital evidence can now be questioned simply because it could be manipulated, how confident are you that the evidence you rely on today would withstand scrutiny tomorrow?